Creation Questions

Tag: science

  • Speciation Is Macroevolution?

    Speciation Is Macroevolution?

    A frequent belief, usually touted as a rebuttal towards creationists, amongst common ancestry proponents is that speciation is macroevolution. Because creationists usually say that they hold to both microevolution and speciation, but not macroevolution, there arises a significant point of confusion from skeptics. Speciation is what happens when organisms have diverged from a lineage population but are separated by niche, geography, habit, or genetics. Macroevolution is a change at or above the species level.

    The term macroevolution was coined in 1927 by the Russian entomologist Iuri’i Filipchenko in Variabilität und Variation. He defined it thus*:

    “In such a state of affairs, it must be admitted that the decision regarding the question of the factors of the broad features of evolution, i.e., what we call macroevolution, must occur independently of the results of contemporary genetics…” (Page 94)

    So macroevolution, according to the original author, does not participate in the class of observable evolutionary processes. Specifically, Filipchenko rejects the notion that macroevolution is speciation:

    “…insofar as it is no longer a matter of the ‘origin of species,’ but of characteristics, so to speak, of a higher order, by which we understand characteristics of larger genera, families, orders, classes, etc…” (Page 90)

    What Filipchenko is getting at is a notion that microevolutionary processes, simply the processes we observe, are distinct from the kinds which arrive at new body-plans. The changes that he observed could account for variation of parts within their delicate integrated-whole units, but could they account for the origin of novel integrations? Filipchenko argues that any effort in his day to answer that question must be speculative. However, he grants that we may see those events take place and we may accrue evidence which bolsters the hypothesis within the field of genetics.

    Yet instead of rising to the challenge to support the macroevolutionary hypothesis, contemporary evolutionary researchers have opted to redefine the term. Macroevolution is speciation. Or at the very least, speciation is the most microcosmic example of this higher macroevolutionary scale. 

    Their rationale: the modern synthesis has proven that all macroevolution events are just culminations of microevolutionary clusters. There is fundamentally no difference between what goes on in the fossil record and what is going on now.

    It stands to reason that if they are satisfied with this redefinition, they must have surely come across some satisfactory evidence that there are no fundamental differences between changes in allele frequencies and changes in higher order structures of the genome. And sure enough, the founders of the MS (Theodosius Dobzhansky, Ernst Mayr, George Gaylord Simpson) did believe they had the evidence to back up their view. 

    Their evidence came from many lanes, but ultimately it can be boiled down to the simple principle of a nested hierarchy. That there was a consistency of genetic rates of mutations with new taxa in geological history and that there was vast latent diversity within populations to capitalize on new niches quickly. From their perspective, if speciation is the branching point of the nested hierarchy, then speciation is the fundamental unit of macroevolution.

    Demonstrating that organisms fit into a nested hierarchy and that gene frequencies shift quickly under selection proves that lineages diverge. But as Filipchenko pointed out in 1927, showing that a system can vary its existing integrated parts across a continuous spectrum is conceptually distinct from demonstrating how a fundamentally new organizational plan is assembled without disrupting the embryonic viability of the organism.

    One attempt to further progress in demonstrating this view came from evolutionary development (evo-devo for short). In that area, they appealed to homeotic genes which are genes that facilitate whole organs and structures of the body. These genes are executive genes which can drastically change how an organism is built. A significant factor in its defense is their ubiquity in nature, where large swaths of organismal groups share identical homeotic genes. For example, the Pax-6 gene initiates eye development in insects, mollusks, and vertebrates. All these eyes are vastly different, so perhaps dramatic changes are possible with a base program.

    And to credit the modern evolutionary theorists, this work is a valiant attempt. Yet it simply doesn’t justify the semantical shift to Filipchenko’s original thesis. Speciation doesn’t demonstrate changes to fundamental architectures of organisms. Speciation is equally predicted in a world where no large-scale evolutionary epochs exist.  

    The discovery of shared master switches like Pax-6 offered a compelling glimpse into developmental mechanics, proving that nature can deploy a single executive signal to initiate radically different organ structures—that is not in dispute.

    However, this deep homology presents a double-edged blade for the redefined macroevolutionary framework. Because Pax-6 itself is conserved across hundreds of millions of years, the gene cannot be the source of the profound structural differences between an insect’s compound eye and a mammalian camera eye. Those differences reside in the dense, highly integrated downstream Gene Regulatory Networks (GRNs) that process the signal during early embryogenesis. These core regulatory networks operate as tightly coupled developmental hubs; altering their foundational wiring routinely triggers catastrophic embryonic lethality rather than viable structural innovation. Because early developmental pathways are so rigidly canalized, modifying the underlying GRN topology without destroying the viability of the developing organism remains a formidable mechanical hurdle.

    Equating speciation with macroevolution addresses the branching of lineages, but it sidesteps the fundamental challenge Filipchenko raised nearly a century ago: how integrated developmental networks can be restructured to yield novel body plans without destroying embryonic viability. Speciation—the divergence of populations through reproductive isolation, geographic drift, or niche specialization—is fully predictable in a framework where structural variation occurs only within established architectural boundaries.

    Therefore, it seems a very real possibility that the definition change was a concerted effort to obfuscate where the real clash or debate lies—where the real uncertainty lies in evolutionary theory. If a creationist accepts macroevolution, then the proponent of common ancestry rides off in celebratory parade. If a creationist accepts speciation, then they accept macroevolution, therefore QED. Somewhere along the line of that reasoning, something is being smuggled into the conversation that the creationist did not actually agree to. If that is not the case, the macroevolution is a meaningless phrase. Indeed the evolutionist Dobzhansky, in his book Genetics and the Origin of Species, concluded that one may “reluctantly put an equal sign” between micro- and macro- evolution. 

    If these terms are rendered useless in this way, then it is only because the evolutionist is begging the question. In order for the evolutionist to say “Speciation is Macroevolution” they must provide evidence that lineage splitting inherently accounts for the origin of novel, integrated developmental architectures. By substituting lineage splitting for structural transformation, modern biological rhetoric may have redefined the term, but the underlying mechanical question remains as vital today as it was in 1927.

    *Variabilität und Variation is written in German and the original sentences read as following in order of appearance:

    “Bei einer solchen Sachlage muß zugegeben werden, daß die Entscheidung der Frage über die Faktoren der großen Züge der Evolution, d. h. dessen, was wir Makroevolution nennen, unabhängig von den Ergebnissen der gegenwärtigen Genetik geschehen muß…”

    “…insofern es sich schon nicht mehr um die ‘Entstehung der Arten’ handelt, sondern der Merkmale sozusagen höherer Ordnung, worunter wir Merkmale der größeren Gattungen, Familien, Ordnungen, Klassen usw. verstehen…”

    References

    Hautmann, M. (2019). What is macroevolution? Palaeontology, 63(1), 1–11. https://doi.org/10.1111/pala.12465

    I︠U︡riĭ Aleksandrovich Filipchenko. (1927). Variabilität und variation von jur. Philiptschenko … Gebrüder Borntraeger.

    Nehm, R. H., & Kampourakis, K. (2013). History and philosophy of science and the teaching of macroevolution. International Handbook of Research in History, Philosophy and Science Teaching, 401–421. https://doi.org/10.1007/978-94-007-7654-8_14

    Plutynski, A. (n.d.). Speciation and Macroevolution Anya Plutynski Blackwell’s companion. Blackwell’s Companion. Retrieved August 12, 2026, from https://philarchive.org/archive/PLUQAM

  • The Problem With Transitional Forms

    The Problem With Transitional Forms

    Today I stumbled on an interesting article from 2016 entitled, “Debunking creationism: a visual comparison of “micro” and “macroevolution”“. What initially struck me about the article was a very peculiar picture representing a smooth gradation from ancient lizard ribcage-skeletons to the modern turtle shell. The author notes that, apart from A1, “B6, A15, C22, B30, and D37” are real fossils that “perfectly match the expectations” for transitional forms (Milleretta, Eunotosaurus, Pappochelys, Odontochelys, Chelydra). For reference, I have highlighted those real fossils and drawn a line connecting them as a visual aid.

    The main thesis of his argument is that the distinction that creationists draw of macro- vs micro- evolutionary processes is an arbitrary one. He writes,

    “this distinction is completely arbitrary and meaningless because the exact same evolutionary mechanisms… In other words, macroevolution is simply the accumulation of microevolutionary steps, and one inherently leads to the other.”

    This is such a common idea. One that I feel I have probably harped on before, but a summary could go something like: Micro-evolutionary processes are insufficient to cause Macro-evolutionary advancements because micro-evolutionary processes introduce no novelty into an organism. No new protein family, no new regulatory system, no new addition to gene function. We do see many examples of real functional changes that are predicated by the surrounding informational and structural elements—take epigenetics or evo-devo for example. But we have yet to find an example of a genome either becoming more robust or more diverse.

    Modification should at least in part be additive. It’s not necessary that it is all the time, but at least a fair minority of the time it should be. We should observe newness in biology for there to be a coherence to a macro-evolutionary model. In my 2025 article, “Mutation is not Creation”, I formulated an extensive argument for these claims.

    My real interest today, like the author of this article, is in exploring the implications of a pictorial challenge. As he states, “I decided to take a different approach for this post and provide a visual explanation.” He credits these photos to Dr. Tyler Lyson’s video, “Evolution of the Turtle Shell.

    You may notice, if you’ve seen these visuals before (in video form or in picture slides), that the version of the presentation I have included is immediately less compelling by nature of simply highlighting which images included are observed. There’s a lot that can be said on the impact that visual story-telling and ad hoc narratives play on our minds, hijacking our rational ability to evaluate the evidence. Evolutionary theory is certainly good at it. Whether we’re looking at the frauds of embryology or the constant barrage of natural selection-laced “this one would survive better” statements.

    Setting aside the fact that it is actually not at all obvious that light sensors that are curved ever-so-slightly more inward are an advantage concrete enough for any selection effect, we must acknowledge the elephant (you know, the one that mysteriously vanished from the room?). That is, differential survival means absolutely nothing when you have no mechanisms to reliably build the new iterations. If this fossil transitions sheet tells us anything, it’s that we should expect many more forms in the fossil record.

    And what do we do with forms such as Psephochelys polyosteoderma that are identical to modern turtles, but contemporary to Pappochelys found on A15? Before Odontochelys (C22) had time to develop a full shell, Psephochelys had already “converged” on that form, i.e., it already had a turtle shell before turtles existed. Which raises the question: On what basis do we take one pile of bones to be “turtles” and another to be “fakes”, when the very argument of smooth transitions in this article depends on bones, and only bones, to make their arguments? In other words, it raises the question: Are they begging the question?

    It seems an awful lot like supporting evolution by looking for evolutionary connections…

    Unfortunately the author of this blog, Fallacy Man (which is as apropos of a name as I’ve ever heard), fails to recognize the clear discontinuities and only aims to defend against the weaker argument (but still deadly): the dramatic leaps within the hypothetical diagram. He writes:

    “Finally, the argument that this pathway is meaningless because it is partially hypothetical misses the point because it is absolutely fine to use hypotheticals to defeat absolute claims. Creationists claim that macroevolution cannot happen, and this pathway shows that it can happen. In other words, to defeat the claim that macroevolution is impossible, I don’t need to prove that this pathway actually occurred; rather, I simply have to show that a pathway is possible, which it clearly is.”

    I just had to laugh when I read this—not at Fallacy Man of course, but at the fallacy. In strict modal logic, proving that something is possible does technically defeat the claim that it is impossible. But Fallacy Man’s argument suffers from a massive epistemic equivocation on the word “possible”. He is conflating visual conceivability with mechanistic biological possibility. Drawing a hypothetical sequence of bones only proves that a structural pathway can be imagined. Demonstrating that a morphological gradient can be mapped out on paper completely fails to refute the claim that the generative biological mechanisms required for macroevolution are actually viable. We need more than a conceptual staircase to prove a biological engine exists to climb it.

    He offers the final challenge:

    In short, if you are going to insist that macroevolution is impossible, then I want you to look at the evolution of the turtle and tell me which step is impossible (and justify that claim).

    And to be fair, there are some transitional forms in the diagram that we do not see today which need to be accounted for. Albeit, there are clear turtle forms before and during those transitions in the fossil record, it’s still true that we have no turtles without hard shell backs today like the Odontochelys… No wait. Even that’s not true. Check out the softshell turtle.

    It is a turtle that exists today and has a shell of leathery skin (instead of hard keratin) that could very easily be destroyed when fossilized. That means the skeleton a very similar structure to the Odontochelys and could very feasibly be fossilized without its outer carapace.

    So we come to this conundrum: All the transitional forms are still around. They arrive in the fossil record out of order. There are absolutely no clear gradations between them—only self-admitted hypotheticals. So what exactly is this challenge, then?

    Because I fail to see any legitimate steps at all.

    Citations

    Coleman, W. (2025, November 7). Mutation is not Creation. Creation Questions. https://creationquestions.blog/2025/11/07/mutation-is-not-creation/

    Fallacy Man. (2016, September 6). Debunking creationism: a visual comparison of “micro” and “macroevolution”. The Logic of Science. https://thelogicofscience.com/2016/09/06/debunking-creationism-a-visual-comparison-of-micro-and-macroevolution/

    Lyson, T. (2013, May 30). Evolution of the Turtle Shell (Illustrated) [Video]. YouTube. https://www.youtube.com/watch?v=NphNApmSZ0U

  • THE SOURCE-PARTICULAR MODEL

    THE SOURCE-PARTICULAR MODEL

    [FREE PREVIEW]

    A Clarifying Synthesis for Scientific Methodology

    CHAPTER 2: An Overview of the Source-Particular Model

    The Source-Particular model is an attempt to ground empirical and theoretical frameworks within a system that justifies their existence. It is not meant to be revolutionary; rather, it is a method for producing knowledge revolutions. I first built it under the tutelage of my college advisor, Dr. Charley Dewberry, a philosopher and marine ecologist, and it has since grown from a sixty-page undergraduate thesis into more than two hundred pages of model-building. I am deeply grateful to the professors at Gutenberg College, and to Charley especially, for the grounding in the history of philosophy and the great books that made this work possible. Reading thinkers such as Thomas Reid, Michael Polanyi, Alasdair MacIntyre, David Hume, Immanuel Kant, Karl Popper, Aristotle, George Berkeley, and Charles Sanders Peirce — and this is far from an exhaustive list — gave me the raw material for a new synthesis. If that synthesis seems significant, the credit belongs less to any originality on my part than to the excitement of reconciling and extending ideas that have already stood the test of centuries.

    I have always been fascinated by science, and a question I keep returning to is this: how should science operate — that is, if it is meant to give us knowledge (justified true belief) about the world? That is the methodological question: what is our scientific method? But that question quickly opens onto a deeper one: what makes a methodology good in the first place? If our scientific method turns out to be nothing more than an arbitrary convention, we are in dangerous territory, because arbitrariness is never a sound foundation for a model of anything.

    Consider an example from the history of physics. Albert Einstein criticized Euclidean geometry for the way it abstracts away from any physical embodiment of its figures — Euclid, the Alexandrian mathematician working around 300 BC, produced the ancient world’s definitive book of geometric proofs without a single physical measurement in it (Euclid, Elements). When Einstein discussed Euclid’s Elements, he argued that a genuinely useful model of physical space needs some point of contact with physical evidence, not just internally consistent axioms (Einstein, Geometry and Experience, 1921). I do not want to overcorrect in the other direction and claim that abstract theories are only valid when they are tied directly to a dataset — quite the opposite. I raise Einstein’s critique only because it shows a thinker refusing to let a geometrical system drift into complete arbitrariness, which is a healthy instinct. My concern in this book, however, is with the far more common mistake, which runs the opposite direction: most scientific projects go astray not because they are too tied to physical assumptions, but because researchers discard their own biases and background assumptions at the laboratory door, as though those assumptions were not doing real work in shaping what counts as evidence in the first place.

    If science is the foundation for many other fields of empirical, verifiable knowledge, then a poor foundation in science can cause the whole structure built on top of it to collapse. My aim in this book, then, is to provide a clearer foundation that can (1) ground our paradigm, (2) guide our research, (3) help us discover errors, and (4) guide the correction of those errors. Many methodologies fail to offer that fourth piece — a genuine procedure for error correction — even though it is essential to getting back on track in any field once something has gone wrong. Karl Popper’s falsificationism, for example, is an excellent tool for recognizing that some part of a theory is wrong, or that the theory is unfalsifiable and therefore empirically empty (Popper, The Logic of Scientific Discovery, 1934). In brief, falsificationism says that a theory only counts as scientific if it forbids some possible observation — if there is no experiment that could, even in principle, prove it false, then it is not doing scientific work. But Popper’s method, useful as it is, gives us no diagnostic tools for figuring out what specifically has been falsified within a theory, or whether the theory is worth salvaging in modified form, or whether we made a more basic mistake somewhere upstream. That gap was not Popper’s project — he was primarily responding to the logical positivists of his day — but it remains a serious absence in the methodological literature.

    This lack of diagnostic capability becomes obvious once we look at real disputes in the history of science. Two examples, which I take up in depth in Chapter 11, are Werner Heisenberg’s rejection of Kantian causality and Albert Einstein’s rejection of Hendrik Lorentz’s ether. Heisenberg believed that quantum indeterminacy could overturn the Kantian assumption that every effect must have a determinate cause (Heisenberg, Physics and Philosophy, 1958). Einstein, for his part, kept Lorentz’s mathematical equations — which had originally been derived on the assumption that light traveled through a physical medium called the “luminiferous ether” — but stripped away the ether and gave the same equations an entirely new interpretation in his theory of special relativity (Einstein, “On the Electrodynamics of Moving Bodies,” 1905). I will develop both cases further later in the book, but the point to note now is that in neither case did the decisive shift turn simply on new observational evidence; something more like a change in background philosophical commitments was doing the work. Beyond this, most methodologies also fail to give the working scientist room to be a skilled craftsman and artist within a specialty — a skill that matters at every stage, from generating theories, to testing them, to evaluating them through peer review. I devote two full chapters to this idea (Chapters 8 and 9).

    The inevitable result of trying to build a “method for methodologies” is that we are forced to answer both ontological questions (concerning the real essence of things, both internal and external to the self) and epistemological questions (concerning the theories by which we try to access that ontological reality). Philosophers usually treat ontology and epistemology as two separate specialties that can, in principle, be pursued independently. I do not think that separation holds up. The reason is simple: we cannot learn about what does not exist, and we cannot claim that something exists without some reason for the claim. There may be a degree of circularity built into this — we use our eyes to diagnose the eyes of others, and we use our own rationality to evaluate whether other people are reasoning well — but I think we should accept some circularity here rather than pretend we can escape it. The Source-Particular Model is likewise circular in this sense: we have to use the very tools the model provides in order to evaluate whether those tools are fit for purpose.

    That circularity brings us to the heart of the model: an ontological taxonomy, or ranking system with built-in dependencies, that organizes our account of scientific theories. I call it the Source-Particular Model, and the name simply describes the groups of real things I have identified as meaningfully distinct from one another. To visualize the model, picture a three-by-three grid. Reading across, there are three levels, running from most foundational to most contingent: Metaphysical, Physical, and Surphysical.

    Reading down, there are three categories that recur within each level: Source, Particulars, and Framework

    A quick clarification before the grid itself: levels differ from one another in kind — the metaphysical, physical, and surphysical are different sorts of reality altogether. Categories, by contrast, differ only in aspect within a single level — the Source and the Particulars belonging to a given level are always the same basic kind of reality as each other, just playing different roles. I recognize the terminology is a lot to take in at once, but it becomes intuitive with practice, and three full chapters (3, 4, and 5) are devoted to walking through each level in turn. Here is the grid, with a short gloss of each cell:

    MetaphysicalPhysicalSurphysical
    Source (the container)MindSpacetimeEnvironment
    Particulars (the contained)VariablesMatterComplexes
    Framework (the emergent metaphor)PropositionMotionNarrative

    Levels run left to right, from most foundational (Metaphysical) to most contingent (Surphysical). Categories run top to bottom: Source is the container, Particulars are the contained, and Framework is the new, non-literal thing that emerges when a Source and its Particulars are combined.

    Let us build up an intuition for this grid from the “observer’s” point of view, following a path Immanuel Kant helped clear. Kant argued that human thought comes equipped with certain built-in structures — space, time, causality, and so on — that we bring to experience rather than derive from it. He called the world as it actually is, independent of our perceiving it, the noumenon (plural noumena), and he argued that we never have direct access to it. What we do have direct access to is the phenomenon: the world as it appears to us once it has been filtered through the built-in structures of our minds and the raw data of our senses. In Kant’s view, we never encounter objects “in themselves”; we only ever encounter our own interpretation of the effects those objects have on us (Kant, Critique of Pure Reason, 1781). Kant himself was fairly pessimistic about how much this phenomenal picture actually tells us about the noumenal world behind it. I want to push back gently on that pessimism. Drawing on the Scottish philosopher Thomas Reid, I think we have good reason to treat our senses as broadly reliable translators, not just an opaque screen: our senses take what are, at bottom, electrical signals firing in the brain and turn them into meaningful reports about states of affairs in the external world (Reid, Essays on the Intellectual Powers of Man, 1785). We all share this basic translating apparatus and our confidence in it — this is what “common sense,” in Reid’s technical use of the term, actually names. Reid’s translation still runs through the very same mental and sensory machinery Kant describes; the difference between the two thinkers is a difference in how much trust to place in that machinery, not a disagreement about whether it exists. Either way — whether we lean toward Reid’s confidence or Kant’s caution — using our senses at all requires a kind of prior faith, or at least a metaphysical commitment, that they are basically trustworthy. That is why I place our mental properties — the mind and its contents — at the foundation of the whole model, in the Metaphysical level.

    This starting point matters enormously. If our metaphysical assumptions shape how we interpret everything we subsequently observe, then flawed metaphysical assumptions will produce a flawed science downstream, no matter how careful the experiments are. Fortunately, metaphysical claims work differently — and, in one sense, more securely — than physical ones. At the metaphysical level we can achieve genuine deductive certainty. To be precise about what I mean: I am not claiming that acquiring rational insight is as mechanical as solving an equation, nor that simply having a metaphysical assumption makes it true. What I am claiming is narrower: metaphysical reasoning is the only kind of reasoning capable of producing strictly deductive arguments — arguments in which true, certain premises guarantee a true conclusion by logical necessity. Only the metaphysical level yields “proofs” in this strong sense. Take a simple case: how certain can we be that 1 + 1 = 2? Totally certain — it follows from the definitions of the terms involved. Or take the law of non-contradiction, that a proposition X cannot be true and false (not-X) at the same time and in the same respect: this is close to true by definition. More elaborate claims, if they are deductively derived step by step from starting-points this basic, inherit the same certainty as their premises.

    One useful way to test a metaphysical claim’s certainty is the reductio ad absurdum — showing that denying the claim leads to self-contradiction. Take the claim that our senses are basically trustworthy. Suppose we deny it and say our senses are entirely unreliable. To even assert that claim to someone else, we would need language, memory, and reasoning that are themselves delivered to us via our senses and cognitive faculties — so the very act of arguing against the reliability of our faculties presupposes enough reliability in those faculties to construct and communicate the argument. The claim undercuts itself. Or take a more radical skeptical scenario: perhaps a deceptive demon, or a simulator running our minds like software, manipulates all our beliefs (this scenario is most famously associated with Descartes, but far older versions of it appear even in Augustine’s City of God, Book XI). Suppose we grant, for the sake of argument, that such a deceiver exists. Even so, in order for the deceiver to deceive or manipulate someone, that someone has to exist as a subject capable of being deceived. So even under the worst-case skeptical scenario, we cannot be deceived about the bare fact that we exist. This is the famous Cartesian starting point — “I think, therefore I am” (cogito, ergo sum) — and from that single certain foothold, Descartes tried to build up further certainties one careful step at a time (Descartes, Meditations on First Philosophy, 1641). The Source-Particular Model borrows this same Cartesian starting point as its own metaphysical bedrock.

    Before going further, I want to be precise about what I mean by “metaphysics,” since the term gets used in wildly different ways across the history of philosophy. I will use it to mean: whatever exists or holds true prior to experience — that is, whatever is not itself derived from empirical observation. To a committed naturalist, calling something “prior to experience” might sound like a polite way of saying it is second-rate, merely speculative philosophy dressed up as knowledge. I want to resist that inference. Every piece of scientific work is filtered through a subjective interpretive lens before it becomes “data” at all, and that lens itself can only be evaluated using arguments that have no empirical content of their own, even though those arguments are still substantive and rationally binding. The rationalist tradition is correct that our knowledge about evidence — what counts as good evidence, what a fair test looks like, what makes one explanation better than another — exists prior to any particular piece of evidence, whether we recognize that background framework consciously or only implicitly. Even if a rationalist turns out to be wrong about the strict order of events — even if, say, our sense of what counts as good evidence is itself an abstraction built up gradually from accumulated experience rather than something we are born with — it remains true that whatever metaphysical commitments we hold will shape how we read the evidence in front of us. Evidence gets fitted into an interpretive framework that already exists prior to the evidence’s arrival.

    Here is a concrete historical illustration. Suppose I hold the geocentric belief that the Earth sits at the center of the universe. When I then observe planets tracing strange, looping paths across the night sky, I do not immediately conclude that my underlying belief is mistaken. Instead, I fit that data into the box marked “things moving around the Earth,” no matter how many extra epicycles — small looping sub-orbits bolted onto the main orbit — I have to add to make the model work. This is, in fact, exactly what happened historically: ancient and medieval astronomers added epicycle upon epicycle to the Ptolemaic (Earth-centered) model to keep it consistent with new observations. The geocentric framework was only seriously questioned once Nicolaus Copernicus argued, on largely aesthetic and metaphysical grounds, that a good and orderly God would more plausibly have arranged the planets in a simpler, more harmonious pattern than the baroque, ever-more-complicated geocentric scheme required (Copernicus, De Revolutionibus Orbium Coelestium, 1543). Notice that the initial case for heliocentrism was not first and foremost a matter of new telescopic data — telescopes did not exist yet — but a metaphysical judgment about beauty, simplicity, and divine orderliness. Beauty, parsimony, coherence, correspondence to a wider theory, and every other quality we use to assign value to a body of data are themselves metaphysical assumptions that precede the evidence they are used to evaluate.

    The Cartesian “I think, therefore I am” is, again, the clearest possible example of a purely metaphysical claim. It assumes that there exists a mind — our mind — capable of holding and evaluating variables. By “variables,” I mean placeholders that are capable of later receiving specific empirical content (think of the x, y, and z of an algebraic equation: on their own they carry no empirical content, but real-world observations can subsequently be plugged into the slots they mark out). Variables come logically prior to any actual, concrete phenomena; they are the empty slots waiting to be filled, not the filling itself. If the mind is the container in which these variables reside, then the variables are the things contained within the metaphysical realm. Translating this into the model’s vocabulary: the mind is the Source, and the variables are the Particulars.

    The Source-Particular (or, if you prefer more familiar language, container-contained) relationship recurs at every level of the model, as later chapters will show. One caution is worth flagging immediately: the container/contained language is a spatial metaphor standing in for what is really a non-spatial relation of dependency. Do not import literal container-logic — spatial containment, or debates about the curvature of physical space in general relativity — into the metaphysical level; the metaphor is meant to illuminate the dependency relation, not to claim that the mind is a literal box with variables literally rattling around inside it. If the container/contained language still feels confusing, feel free to substitute the more literal terms “prerequisite” and “dependent.” I prefer “Source,” though, because it foregrounds the asymmetry that matters most here: every Particular requires its Source in order to exist at all, but no Source requires any of its Particulars in order to exist — though, as I will explain shortly, a Source does need at least some Particulars in order to have any determinate meaning.

    So what happens when the mind gets to work sorting through its variables? We arrive at axioms — the laws of logic, of mathematics, of causality, of sensory awareness, and of personal identity, through which all of our sense-data gets filtered. In the model’s vocabulary, this resulting propositional content is called the Framework, because it is what makes sense of the otherwise unrelated combination of a mind (the Source) and a variable (the Particular). Frameworks are, in Michael Polanyi’s sense, “metaphors”: new meanings that emerge from combining two or more ingredients that do not, taken purely literally, belong together at all (Polanyi, Meaning, 1975). Consider the ordinary sentence “the classroom was a zoo.” Taken completely literally, this sentence is absurd — there are no actual zebras, giraffes, ticket booths, or entry fees anywhere in the classroom. And yet an emergent meaning arises easily out of the cultural association most people share between “zoo” and “chaotic, noisy, and hard to control”: we instantly understand that the classroom was loud and unruly. The metaphor works precisely because it forces together two concepts — “classroom” and “zoo” — that do not literally overlap, generating a third meaning that belongs to neither concept alone. This is exactly the kind of move the Source-Particular Model makes at every level: combining a Source and its Particulars, which are different in kind from one another, to generate a Framework that is different in kind from either.

    For the Metaphysical level specifically, “Source-Particular” describes the pairing of mind and variable. The mind, on its own, is not itself particular in any way; it is the general capacity to hold and relate variables. But putting mind and variable together produces new information that neither one supplies on its own — namely, propositions. A proposition, in this technical sense, is the mind’s own self-organization: its ontology, or, as Aristotle would say, its account of being qua being (being simply as being, considered in its own right, apart from any more specific subject matter) (Aristotle, Metaphysics, Book IV). This proposition-level meaning is a metaphor in Polanyi’s sense as well, though with one qualification: for Polanyi, metaphors are strictly statements that cannot be taken literally, not necessarily a pairing of two categories that cannot literally be reconciled with each other. Even so, I think the underlying mechanism is the same: our subsidiary (background, half-noticed) awareness of the parts metaphorically constructs a single focal (foreground, fully attended) awareness of the whole.

    Focal awareness is whatever we are directly and consciously attending to at a given moment; it is the meaning that the various parts, taken together, communicate. Consider what it is like to ride a bicycle. Your focal awareness while riding is not the mechanical act of pushing each pedal, nor the constant small shifts of your weight to stay balanced, nor the tiny corrective turns of the handlebars. All of those actions are subsidiary — present, and even necessary, but not directly what you are attending to. Your focal awareness is instead something like “getting down this path” or “not falling over,” the larger purpose that all those unnoticed micro-adjustments are quietly serving. For Polanyi, this means the bicycle functions as a tool: an extension of your own body (Polanyi, Personal Knowledge, 1958). This point generalizes well beyond bicycles. Any tool — a hammer, a pair of glasses, a map, a textbook — is, in this sense, an extension of the body, because it extends the reach of our senses, our physical actions, or our reasoning. Tools change our very relationship to the world by widening the sphere of things we are able to act on or understand. And crucially, our focal awareness is never directed at the tool itself; it is directed at the point where the tool meets the world. When you write with a pen, you attend to the words forming on the page, not to the precise pressure of your fingers on the barrel.

    We can also see this dynamic in cases where subsidiary awareness gets wrongly promoted to focal awareness, with poor results. Consider trying to drive a nail with a hammer while consciously fixating on exactly how your fingers are wrapped around the wooden handle. Because your attention is on the grip rather than on the nail, your swing becomes stiff and poorly aimed, and you are far more likely to miss. Once you have practiced enough that the grip becomes properly subsidiary again — something your hand simply “knows” without your having to think about it — your aim on the nail improves immediately. Strengthening our subsidiary skills, in other words, strengthens the focal performance those skills are quietly supporting.

    With those three ideas in hand — metaphor, focal awareness, and subsidiary awareness — we can return to the Source-Particular Model itself. Our own everyday focal awareness naturally sits at the highest level and category of the model: the Surphysical Framework of Narrative, where we process our experience in its richest and most meaningful form. This is, experientially, the level closest to lived life. But how we process that experience is quietly governed by the more foundational, more abstract levels beneath it — levels we can only access by deliberately turning our attention away from our ordinary focal awareness and toward the usually-subsidiary machinery underneath. This produces a kind of mirror-image structure in the model: certainty runs from the lower levels up to the higher ones (the Metaphysical level is the most certain, the Surphysical level the least), while focal, lived awareness runs from the higher levels down (we live our lives at the Surphysical level, only rarely attending consciously to the Metaphysical assumptions beneath it).

    To round out this set of Polanyian tools, we need one more concept: tacit knowledge, meaning the kind of pre-understanding that lets us do things we cannot fully articulate (Polanyi, Personal Knowledge, 1958). Tacit knowledge explains why we can ride a bicycle without being able to state the physics of gyroscopic stability that keeps us upright, or the precise sequence of muscular corrections our body is making thirty times a second. We might hold only a vague, intuitive picture of what riding involves, or we might be trained mechanical engineers who understand the physics and material science of bicycles in exhaustive technical detail — the metallurgy of the frame, the manufacturing history of the brand, the record times of the best competitive riders, and so on. All of that additional knowledge can enrich our understanding of “riding a bicycle” to varying degrees, but none of it, by itself, constitutes the actual riding. Riding a bicycle is not identical to the physics of the bicycle’s motion, nor to the anatomy of the rider’s muscles. Riding a bicycle, in the vocabulary of this model, is a Narrative — a higher-level Framework that draws on, without being reducible to, everything beneath it.

    But is “riding a bicycle” really a metaphor in the relevant sense? After all, what is incoherent or non-literal about the plain sentence “I am riding a bike”? We really are the ones riding it — aren’t we? Here is the twist: what is actually happening, according to the model, is that a mind is interpreting a stream of phenomena as “riding a bike.” The physical matter involved really is arranged into shapes we call a bicycle and a rider. But neither “the bicycle” nor “the rider,” considered as unified, meaningful wholes with a function and a story, exists at the purely metaphysical level (which contains only mind and variables) or at the purely physical level (which contains only spacetime and matter, without any reference to purpose or function). The bicycle-and-rider-as-a-meaningful-unit is therefore a distinctly Surphysical construct. “A biker” implicitly invokes particular complexes (a physical bicycle object, a physical human body) together with a Source that makes those complexes cohere into a single meaningful whole — namely, an environment: the trail, situated within a park, situated within a city, that gives the whole scene its point. Understood this way, “biking” is indeed a metaphor — not the everyday kind that a literal reading of the sentence would obviously flag, but the deeper kind revealed once we notice the ontological gap the sentence is quietly papering over.

    This bicycle example reveals something about the model I have not yet stated outright: the Source-Particular structure applies not only within each level, but across the three levels taken together, on a larger scale. Metaphysics, Physics, and Surphysics themselves form a Source, a Particular, and a Framework at the macro-scale of the whole model. Metaphysics provides the container (mind) within which physical things can first be conceived of and related to one another at all. The relating of physical things, in turn, gives rise to environments, complexes, and narratives — the Surphysical Framework layer. I recognize this may be a large claim to absorb this early in the book, and I will return to unpack it more fully in later chapters.

    Return once more to the cyclist. Nothing resembling a bicycle or a biker exists at the purely Metaphysical level; that level exists prior to any physical thing being singled out as an object at all. And yet the bicycle example shows that even though our only immediate access is to the Narrative level of our own lived experience, that experience is always quietly informed and constrained by the more foundational levels beneath it. The rider is not focally aware that he is pedaling, yet some form of understanding of pedaling is clearly present and available to further reflection or practice. In the same way, we are not ordinarily, focally aware of our own metaphysical assumptions — but we can bring them into view and examine them through models like this one, which are designed to make visible the usually-hidden subsidiaries beneath our knowledge. This has always been one of philosophy’s central and most valuable roles: not to replace our lived experience, but to clarify, piece by piece, the largely invisible scaffolding that makes that experience possible in the first place.

    CHAPTER 3: The Metaphysical Level

    No thinker illustrates the Metaphysical level better than Aristotle. Although the title of his treatise Metaphysics arose from a fairly arbitrary bit of ancient library cataloguing — it was simply shelved “after the Physics” (meta ta physika, literally “after the physical things”) — the subject matter turns out to be deeply relevant to physics itself. Aristotle describes this “new science” as the discipline that investigates first principles and causes: the discipline concerned with the attributes of being as such, what he calls ousia, or substance, and what later commentators summarize as the study of “being qua being” (Aristotle, Metaphysics, Book IV, Ch. 1). Aristotle notes, somewhat wryly, that this kind of inquiry tends to flourish historically whenever a society has enough leisure to support philosophers who can pursue it for its own sake rather than for immediate practical need. Early in the Metaphysics, he calls this inquiry into substance the discipline closest to the divine, on the grounds that it is exactly what a god would be occupied with: a god, on Aristotle’s view, is above all the ultimate cause and knower of all things.

    Aristotle’s word “science” here should not be confused with our modern, narrower sense of “science” as controlled empirical experimentation. For Aristotle, episteme (often translated “science”) simply means any organized discipline aimed at genuine knowledge, whatever its subject matter. Aristotle explicitly holds that some knowledge is never going to be empirical knowledge at all — that some categories of reality cannot, even in principle, be reduced to matter. His entire Metaphysics is an attempt to work out this non-empirical kind of knowledge in detail. In fact, Aristotle argues that truly knowing something requires more than identifying the matter it is made of: we also need to identify its efficient cause (what brought it about), its formal cause (what shape or structure makes it the kind of thing it is), and its final cause (what it is for). I will unpack all three shortly with a concrete example. Much of the Metaphysics, whether explicitly or implicitly, works out a whole family of a priori concepts — concepts known prior to or independent of experience — including the four causes, the law of non-contradiction, the idea of an uncaused first cause, and criteria like parsimony (preferring simpler explanations), consilience (the way independent lines of evidence converge on the same conclusion), pragmatism, correspondence (truth as matching reality), coherence (truth as fitting together consistently with everything else we hold), the puzzle of infinite regresses, and the basic nature of truth and cognition.

    To treat any of these concepts as ultimately reducible to matter, Aristotle argues, is to commit a category error — to mistake one kind of thing for a fundamentally different kind of thing. He makes this point vividly: “wood does not manufacture a bed” (a paraphrase of the reasoning found across Metaphysics, Book VII). Consider a wooden bed built by a craftsman. First, a purely materialist account is missing an efficient cause: what actually moved the wood into the shape of a bed? Wood does not spontaneously assemble itself; some agent — the carpenter — had to act on it. Second, it is missing a formal cause: what, exactly, is “the form of a bed”? That form cannot simply be identified with any one of the bed’s physical constituent parts (the planks, the nails, the fabric), since those same materials could just as easily have been assembled into a chair or a ladder. If matter were truly all there is, then no arrangement of matter would have any privileged claim to be “the shape of a bed” rather than any other shape. Third, it is missing a final cause: there is no built-in purpose, function, or reason for a bed’s existence written into the wood itself. If a random pile of particles happened by pure accident to take on the shape of a bed, it would only count as “a bed” because a mind was there to recognize and use it as one — not because bed-ness is a real property the particles possess independently of anyone’s noticing it. For Aristotle, natural things like an acorn carry their final cause within themselves — an acorn naturally develops into an oak tree, without anyone designing it to do so — whereas artifacts like beds have their final cause located instead in the mind of the person who made them. Whichever kind of case we are dealing with, Aristotle’s broader point stands: a purely materialist account cannot even formulate the question of purpose, let alone answer it, because it has no vocabulary in which purpose could be expressed as a real feature of the world. On this view, matter alone cannot account for change, form, or purpose.

    It would therefore be a mistake to assume that empirical, laboratory-style knowledge is automatically more certain or more solid than this kind of philosophical knowledge — that assumption misunderstands what human reasoning is actually doing. We take it for granted, for instance, that a single thing cannot both exist and not exist in the very same respect at the very same time (the law of non-contradiction) — yet this is not itself an empirical discovery made in a lab; no experiment could ever confirm or disconfirm it, because it is presupposed by the very possibility of running and interpreting any experiment at all. We likewise take for granted that composite objects — a human body, a river, a nation — retain a stable identity even as their individual parts are gradually replaced or altered over time. And we take for granted that causes really do produce effects (a point Kant develops with particular care). All of these are metaphysical commitments, quietly operating beneath every empirical inquiry we conduct.

    Accepting commitments like these, I want to argue, inevitably implies the existence of a mind as their ultimate source. Within the Source-Particular Model’s three-part structure, the mind functions as the epistemic cause underlying all other causes we might identify: it is the container that makes all other knowledge possible, and in that sense it is the most fundamentally real thing in the system, both ontologically (in terms of what actually exists) and epistemologically (in terms of what we can actually know). One of the broadest points of agreement across the whole history of philosophy — as Georg Wilhelm Friedrich Hegel likewise observed — is simply that there is something rather than nothing, and that philosophical inquiry has to start from whatever is immediately given to us, rather than from some further, more basic starting point (Hegel, Science of Logic, 1812). Exactly who or what “the observing party” ultimately is remains open to debate. But if that observing party is describable as an “I” at all, then that “I” cannot be mistaken about its own existence — that is the one thing it is logically impossible to be deceived about, since being deceived already presupposes a subject there to be deceived. This is not merely deductive certainty (certainty that follows from prior premises); the Source-Particular Model treats it as axiomatic certainty — certainty so basic that it functions as a starting point rather than a conclusion.

    And yet, notably, we did not arrive at this truth by reasoning it out in advance of any experience at all. Metaphysics, on my account, studies the ontological conditions that make all other knowledge possible — but we typically arrive at an explicit grasp of those conditions only by reflecting backward from experience we have already had, not by deducing them from nothing beforehand. On Kant’s account, we never have unmediated access to either pure reason on its own or pure raw experience on its own; instead, we receive an already-fused phenomenal synthesis, and it is only by careful philosophical analysis afterward that we can distinguish the contribution of the mind’s own structuring from the contribution of whatever lies “outside.” Even so, for all practical purposes, the resulting phenomenon — the world as it appears to us — is the real substance we actually care about and can meaningfully discuss. It is a common misconception that this Kantian picture is flatly opposed to Reid’s realism. On closer inspection, Reid actually agrees with Kant that we lack any direct access to things exactly as they are “in themselves”; both thinkers hold that, as finite subjects, we have only our own cognition to work with, and that we must extract whatever metaphysical conclusions we can from the accumulated deliverances of experience. The real difference between them is a difference in the degree of trust each is willing to place in that experience as genuinely corresponding to an independent reality. For Reid, our senses and our shared natural language are gifts specifically suited to letting us understand the external world by means of the “signs” our senses present to us; Reid is explicit, in his writings on the philosophy of common sense, that God designed our faculties precisely so that we could correctly interpret the signs of the world beyond our own minds, and this theological confidence is what underwrites Reid’s greater trust in the senses compared to Kant’s more guarded position.

    Within the Source-Particular Model, then, “experience” is never merely the isolated mind turned in on itself; it is the entire chain running from mind, to observation, to narrative. We have to postulate that the Physical level — much like Kant’s noumenal world — is genuinely real, even though it is never directly accessible to us in an unmediated way. Whichever picture one ultimately prefers, Reid’s or Kant’s, both end up tracking the very same three-part structure this model proposes. I will not spell out the full mapping in detail quite yet, except to flag it briefly: the Metaphysical level corresponds to the a priori structures of natural language and common sense; the Physical level corresponds to the noumena, the reality that is signified but never directly seen; and the Surphysical level corresponds to the phenomena, the signs through which that reality is indirectly communicated to us.

    When we turn to describing the Metaphysical level in the model’s own vocabulary, three categories with their own distinctive qualities come into play — as is true at every level: Source, Particulars, and Framework. Because this is fundamentally a mental realm, the mind plays the crucial role of Source: the space within which the Particulars can exist at all. It plays this role not by creating the Particulars from nothing, the way an author might invent a fictional character, but rather by sustaining them — serving as their ongoing “life-blood,” the condition without which they could not persist. Strictly speaking, we could imagine each of the model’s categories in total isolation from the wider contingency structure, but in practice it becomes very difficult indeed to imagine concepts existing with no mind to hold them, or physics operating outside of any spacetime, or a subject existing with no context at all. The Source is, in this sense, always implicitly assumed by our very language, whether we notice it or not.

    Take the word “nothing” as an illustrative case. “Nothing” is meant to describe the absence of either a container or its contents. And yet we cannot construct a linguistically coherent use of “nothing” that makes no reference, even implicitly, to some Source. If I say “nothing is here,” or “nothing happened,” or “nothing happened here,” each of these statements is implicitly framed against a background of spacetime — a “here” or a “when” against which the absence is being measured. Even if I retreat further and try to speak of “nothing” in a purely abstract sense, entirely apart from physical substance, that abstract “nothing” is still occurring as a thought — which is to say, it is still something occurring within a mind. Even the total absence of any thought presupposes a thinker capable of having (or, in this case, not having) that thought, in the same way that the absence of light only makes sense relative to some possible source of light. If this reasoning holds, then not even “nothing” — let alone any particular “thing” — can be conceived apart from some mental context in which it is conceived.

    If a mind really exists, and we ask what exactly it is, the most straightforward way to answer is to look at what it does: it senses, remembers, experiences, acts, exercises skill, and so on — in short, it has thoughts. And the crucial feature of a thought, for our purposes, is not merely that it occurs, but that it is about something; philosophers call this feature “intentionality,” or “aboutness.” A thought that is about something is already implicitly a system of variables organized into candidate proofs — proofs that are capable, in principle, of corresponding to real states of affairs, and that are, in a real sense, themselves genuinely existing entities once true. And yet, importantly, at the purely Metaphysical level there is no correspondence relation available to us at all (no way to check a claim directly against an external physical fact) — there is only internal coherence, meaning consistency among the claims themselves. This is precisely why claims at the Metaphysical level are not falsifiable in Popper’s sense: falsifiability requires that some possible empirical observation could count against a claim, but no empirical observation of any kind bears on purely metaphysical claims like the law of non-contradiction.

    The only way to test claims that belong exclusively to the mind, then, is to test them against the absurdity of their opposites (the reductio ad absurdum technique introduced earlier) and to build further propositions from them by strict deduction. This procedure can strike many readers as arbitrary or even circular. In fact, I want to argue the opposite: this Metaphysical mode of reasoning yields the most certain and most secure knowledge available at any level of the model.

    The Particulars at this level are variables: the smallest indivisible units out of which logic, mathematics, grammar, and reasoning generally are built. They are the most basic, “irreducible” elements available within our mental constructs. On their own, variables signify nothing at all except pure relation — a placeholder standing ready to be related to other placeholders according to some rule. All the metaphysical truths available to us share this same character: they are pure relations, in the sense that they are not yet tied down to any particular external object or physical construct. “Relation” here means holding some determinate value or ordering with respect to other variables. In this sense, the Metaphysical level is specifically the level of value and of the ordering of values. Because values and their orderings can apply equally well, in principle, to any number of different objects, variables themselves never automatically “particularize” into any specific material form; they remain generic until something further fills them in.

    Ethics offers an interesting borderline case here. In one sense, ethics genuinely participates in metaphysics: “good” and “bad,” considered purely in the abstract, are themselves a kind of value, and values belong at the Metaphysical level. But there is clearly more to concrete moral judgment than abstract value alone. Moral claims certainly have to conform to basic metaphysical considerations, but they must also correspond to specific actions, carried out by a particular agent, working through a physical medium, within a specific environment and context. Ethics, understood this way, moves beyond the tidy certainties of the Metaphysical level into the messier, richer, and less certain territory of Narrative — which, in this model, belongs to the Surphysical level. Meanwhile, other purely metaphysical items, like numbers or the rules of semantics, seem to have no direct bearing on physical laws or chemical reactions and yet somehow still apply cleanly to them whenever we use them to describe the physical world. In one sense, a variable is applied to some physical or surphysical concept only somewhat arbitrarily, as a matter of notational convenience — and yet, in another sense, real meaning is clearly being communicated when we do this. If that were not so, it would be impossible for two people to genuinely agree or disagree about a mathematical or logical claim concerning the physical world; disagreement itself presupposes shared, meaningful content to disagree about.

    This raises an obvious question: what exactly is this abstract realm that can be laid over our empirical findings — organizing them, illuminating them, and helping us judge them true or false — while apparently existing quite separately from the physical world itself? Many mathematicians have puzzled over exactly this question. In his celebrated paper on the subject, the physicist Eugene Wigner argued that the sheer effectiveness of mathematics in describing the physical world is genuinely puzzling — “a wonderful gift which we neither understand nor deserve,” bordering on the mysterious (Wigner, “The Unreasonable Effectiveness of Mathematics in the Natural Sciences,” 1960). In response, others, such as the mathematician Richard Hamming, have suggested that mathematics only looks so effective because we quietly discard whatever mathematics turns out not to correspond well to nature, keeping only the successful cases and thereby creating a kind of survivorship bias (Hamming, “The Unreasonable Effectiveness of Mathematics,” 1980). But this response, I think, only pushes the question back a step: it still has to explain why there is any body of mathematics that corresponds this well to nature in the first place, and to such a strikingly serendipitous degree.

    If mathematics really were a completely abstracted discipline, entirely foreign to our material existence, such that its correspondence to nature were simply a coincidence, then that coincidence would indeed be a genuinely inexplicable anomaly. The Source-Particular Model, however, offers a different diagnosis: it denies that abstract mathematical concepts are somehow derived by abstraction from physics and surphysics in the first place. Instead, on this model, the abstract Metaphysical level is precisely the interpretive lens through which we filter and organize our sense experience to begin with — it is not extracted from experience after the fact, but is presupposed by experience from the start. A committed materialist could, in fact, accept a version of this same point: our brains have simply evolved to interpret the world in a way that happens to line up well with how the world actually behaves, so it should be no surprise, on this view, that our mathematical interpretation of the world maps onto the world reasonably well. On this reading, the correspondence between mathematics and nature is close to a tautology, since we use mathematics to organize our experience of nature in the first place, prior to doing any formal natural science with it at all.

    This may be part of why Kant himself remained skeptical about our ability to know the noumenal world directly: not only do we lack any unmediated experience of it, but what we do experience turns out to be suspiciously well matched to the very interpretive tools we bring to the table beforehand, which should perhaps make us cautious rather than confident. And yet, paradoxically, this same striking correspondence might instead give comfort to a realist like Reid: if our senses and our intuitions line up with the physical world this well, one very natural explanation is that they were specifically designed to line up that way. Which conclusion one is drawn to — Kantian caution or Reidian confidence — will likely depend on one’s prior views about divine design, and on one’s general willingness to accept an outcome that looks, on its face, highly improbable. At the very least, we can say with confidence that we possess a set of variables that reliably track our analyses of matter and of the higher-level complexes built out of matter.

    More specifically, these variables line up with higher-level reality through the alignment of Frameworks across levels. Picture a set of transparent anatomical overlays of the human body — one sheet showing the digestive system, another the nervous system, another the skeleton — that can be layered on top of one another to build up a single, complete picture of the whole body. In much the same way, the different levels of reality in this model line up and overlay one another to produce a fuller, more complete account of reality as a whole.

    At this exact juncture, I think, the real limitations of pure naturalism come clearly into view. Whether one chooses to interpret the “unreasonable effectiveness” of mathematics as a tautological by-product of evolutionary history, or instead as a meaningful piece of evidence for cosmic design, depends entirely on the metaphysical commitments one brings to the question beforehand — the raw empirical correlation between mathematics and nature is, by itself, silent about its own ultimate origin. For the naturalist, the alignment is simply a brute material necessity that requires no further explanation; for the teleologist (someone who thinks the universe exhibits genuine purpose, or telos), that same alignment is a significant sign pointing toward design. Our underlying Frameworks inevitably govern how we interpret every individual piece of data we encounter, which shows that we do not simply derive our metaphysical grounding from scientific observation, as a strict empiricist might hope; rather, we conduct our science by means of metaphysical commitments we already hold. If this is correct, then the naturalist, in order to exclude a metaphysical origin for reality, has no choice but to rely on metaphysical commitments of their own to rule that possibility out — which means the naturalist is not actually avoiding metaphysics at all, but only reducing it, by stipulation, to purely material terms. In effect, naturalists cede the genuine ground of metaphysics through what they actually do in practice, even while officially disclaiming metaphysics in their stated doctrines.

    At this point it is worth pausing to explain more carefully how Frameworks operate at the Metaphysical level, and in the model generally. First, it is important to be clear that a Framework is not “emergent” in the sense of being built up piece by piece out of its Particulars, the way a wall is built up out of individual bricks. Instead, a Framework is the relationship that holds between two otherwise irreconcilable categories, forming a proper “Source-Particular” pairing: it is a genuinely new, emergent property arising from the interaction between the two prior categories within a single level of reality, rather than something assembled additively from parts. The Framework, in other words, arises from a metaphor, not from mere aggregation. At the Metaphysical level specifically, the mind is categorically distinct from the variables it contains, even though those variables depend on the prior existence of the mind as their Source. The mind is not literally made up of a collection of variables, in the way a wall is made up of bricks; nor are variables literal pieces of the mind, the way a brick is a piece of a wall. And no particular arrangement of mind and variables, however elaborate, can by itself push their relationship into a higher category than the Metaphysical. The laws of logic, for instance, do not depend solely on any particular mind’s actually operating them at a given moment; rather, the operation of minds in general is what makes it possible for categories — that is, stable units and unified groupings — to exist and be used at all. The mind facilitates model-building in general. But without variables — without something for the mind to categorize in the first place — there would be nothing for any Framework to organize, and so no Framework could arise.

    Throughout this book I draw on several concepts from Michael Polanyi, especially from his posthumously published work Meaning (1975), which I have not yet fully unpacked. These concepts — metaphor, focal/subsidiary awareness, and tacit knowledge — recur throughout the model, since so much of my own thinking here has been shaped directly by Polanyi’s influence. To restate the definition of metaphor precisely: a metaphor arises when (1) the literal meaning of a statement is absurd or incoherent on its face, prompting the mind to seek out a new, non-literal meaning instead, and (2) that new meaning takes on distinctively subjective, symbolic qualities drawn from shared cultural or experiential context. Returning to our earlier example, “the classroom was a zoo” counts as a metaphor precisely because its literal meaning is absurd (there are, again, no actual zebras or entry fees involved), yet an emergent meaning is readily available from the shared cultural association between “zoo” and “chaotic, noisy, animal-filled place.” A metaphor like this builds directly on our prior, independent understanding of both of its component concepts — “zoo” and “classroom” — fusing them into a single new meaning that neither concept, alone, could supply.

    The Metaphysical level’s own “Source-Particular” pairing — mind and variable — is doing a structurally similar kind of work. We are merging two ideas that, taken purely literally, do not belong together: a mind is not itself a variable, and a variable is not itself a piece of mind. And yet their combination generates genuinely new information in our thinking — namely, propositions. Propositions, again, are abstract: they are the mind’s own self-organization, its account of its own being, or, to use Aristotle’s phrase once more, its grasp of “being qua being” — that is, whatever must hold true for anything at all to exist, prior to any further specification of what particular kind of thing it is. This, I am suggesting, is itself a kind of metaphor, though I should flag one difference from Polanyi’s own usage: for Polanyi, metaphors are specifically statements that resist a literal reading, not necessarily any pairing of two categories that cannot be literally reconciled with one another. Still, in a broader sense, I think all of our subsidiary awareness works by metaphorically constructing a single focal awareness out of parts that, considered on their own, do not obviously add up to that focal whole.

    Bring this back once more to the model as a whole. Our own immediate, everyday focal awareness sits at the model’s highest level and category — the Surphysical Framework of Narrative — where we process our experience in its richest, most integrated, and most meaningful form. This is, in that sense, the level truest to lived experience. And yet how we process that experience is quietly dictated by the more foundational levels beneath it, levels we can only bring into view by deliberately attending to what is more and more abstract, moving in the opposite direction from our ordinary focal awareness. Even though our everyday awareness sits about as far as possible from the mind considered in its bare, Metaphysical sense, that same bare mind remains the single most certain and most foundational element of the whole model — both epistemically (in terms of what we can be most sure of) and ontologically (in terms of what actually grounds everything else). This produces the mirrored structure I mentioned earlier: certainty increases as we move from the higher levels down toward the Metaphysical level, while immediacy and focal awareness increase as we move from the Metaphysical level up toward the Surphysical.

    We have now covered metaphor, focal awareness, and subsidiary awareness. Understanding tacit knowledge is the key to understanding how the Source-Particular Model actually operates in practice. Tacit knowledge is a kind of pre-understanding: it explains why we are able to ride a bicycle without knowing the underlying mechanics or techniques involved, simply by performing the act successfully. We might carry only a fuzzy, intuitive picture of what riding a bicycle involves — or we might be trained engineers, fully versed in the physics and engineering of bicycles and in how a rider’s body ought to move in response. We might even know the specific metals, plastics, and fabrics that go into a given bicycle at the level of chemistry; we might know the various manufacturers who produce them and how; we might know the best and worst competitive riders in the sport’s history, along with the whole array of formal and informal competitions built around cycling, and whatever further trivia one could imagine. All of this additional knowledge can enrich — sometimes considerably — our focal awareness of what it means to ride a bicycle. But none of it, individually or collectively, simply is the riding itself. Riding a bicycle is not reducible even to the complete physics of the bicycle’s motion, or to the complete anatomy of the muscles involved in pedaling and balancing. Riding a bicycle, on this model, is therefore best understood as a kind of Narrative.

    But is riding a bicycle really a metaphor at all? How exactly is the plain statement “I’m riding a bike” incoherent, or non-literal, on its face? We really are the ones riding the bike — aren’t we? The answer, on this model, is: not quite, or at least not in the naively literal sense the sentence suggests. What is actually happening is that a mind is undergoing a stream of phenomena that it interprets as “riding a bike.” The physical matter involved really is arranged into the shapes we call a bicycle and a human body. But strictly speaking, neither “the bike” nor “the rider,” understood as unified, meaningful, functioning wholes, exists purely at the Metaphysical level (mind and variables alone) or purely at the Physical level (spacetime and matter alone). What we are calling “a biker,” then, is a genuinely Surphysical construct. “A biker” implies particular complexes — the physical bicycle, the physical rider — together with a Source that makes those complexes cohere into a single meaningful whole: namely, the environment of the trail, situated within the park, situated within the city, that gives the whole activity its point and context. If this analysis is correct, then “biking” really is a metaphor after all — not the everyday, obviously non-literal kind of metaphor a casual reading of the sentence would flag, but a deeper metaphor rooted in the ontological gap between the model’s separate levels, one that ordinary language quietly papers over without our noticing.

    In working through this example, I have already shown you something about the Source-Particular Model that I have not yet stated explicitly. There is one further, special layer to the model. The three levels themselves — Metaphysics, Physics, and Surphysics — form their own Source, Particular, and Framework at a larger, macro scale. Metaphysics provides the container within which physical things can first be held and related to one another as objects of thought at all. The relating of those physical things to one another, in turn, gives rise to environments, complexes, and narratives — the full Surphysical layer. I recognize this may feel like getting ahead of ourselves this early in the book; I will return to develop the point more fully in later chapters.

    Return once more to the cyclist. Nothing resembling a bicycle, or a biker, exists at the purely Metaphysical level — that level exists prior to any physical thing’s being singled out as a determinate object at all. And yet the bicycle example shows that even though our only truly immediate access is to the Narrative level of our own lived experience, that experience is always quietly informed by the more foundational levels beneath it. The rider need not be focally aware that he is pedaling in order for some understanding of pedaling to be genuinely present, available for further reflection or refinement through practice. In the same way, we are not ordinarily, focally aware of our own metaphysical assumptions — yet we can bring them into explicit view through models like this one, which are built precisely to surface the ordinarily hidden subsidiaries beneath our knowledge. By acquiring a fuller and more accurate picture of these subsidiaries, we put ourselves in a position to build better diagnostic tools for correcting our errors and navigating toward truth. This has been philosophy’s central and most valuable role since its very beginning.

    CHAPTER 4: The Physical Level

    The Physical level is, in one sense, the most obvious and intuitive of the three, and in another sense the most controversial. Even though this level (along with, occasionally, the Surphysical) is often the only level of reality a strict materialist is willing to accept as real at all, there is nonetheless real hesitation, even among materialists, about how exactly to divide this level into its own Source, Particular, and Framework. What is the ultimate substratum of physics? Is it quantum fields? Is it spacetime itself? Is it some more abstract mathematical vector space? Is matter best understood as the curvature of spacetime, in the manner of general relativity, or as the excitation of underlying quantum fields? And what, at bottom, is physics itself — is it something fundamental that exists prior to the universe, or is it, like some naturalists claim about logic and mathematics, merely a convenient after-the-fact abstraction, built up to fit the patterns of observation the philosopher David Hume described as mere habit or custom? These are serious questions that any genuinely ontological model has to confront directly rather than sidestep.

    We can say a few things at the outset about how the Physical level differs from the Metaphysical level already discussed. Two differences stand out in particular: (1) the Physical realm is finite, where the Metaphysical realm (of pure logical and mathematical relation) is not, and (2) the Physical realm proceeds by induction — drawing general conclusions from a limited set of specific observations, always open to revision by future evidence — rather than by the strict deduction available at the Metaphysical level. This means that whatever we identify as the Physical level’s Source, Particular, and Framework, physical reality as a whole must exhibit finitude, and therefore changeability, and therefore falsifiability — which, recall from Chapter 2, is the gold standard for any genuinely empirical, inferential body of knowledge.

    With those two constraints in view, we can ask what the Physical Source actually is. We are looking for something finite that is nonetheless capable of holding finite particulars within it. The best candidate is spacetime. A pure mathematical vector space will not do, because vector spaces are typically infinite in extent, whereas we need something bounded. Quantum fields will not do either, because fields themselves already presuppose some more basic physical setting they operate within and depend on — they are too narrow a candidate to serve as the ultimate container. Spacetime, by contrast, satisfies both requirements: both space and time, as we ordinarily conceive them, are finite dimensions. You cannot meaningfully describe two particulars as separated by an infinite distance or an infinite duration within an ordinary spacetime framework the way you could within a purely abstract, infinite mathematical space. Spacetime also differs from the Metaphysical level in another important respect: it is not itself intrinsically changeable, even though things within spacetime change constantly. Within any given physical Framework, the specific arrangement of spacetime is altered by the events occurring within it, but the underlying nature of spacetime itself — as the finite, four-dimensional stage on which those events occur — remains constant across all such changes.

    Having now discussed the two most fundamental Sources in the model — mind at the Metaphysical level, spacetime at the Physical level — we can test an interesting structural prediction. If mind really is more certain than even its own Particulars, as the Cartesian and Augustinian argument from Chapter 3 concludes, then we should expect a similar pattern of relative certainty to recur at every level: in each case, the Source of a level should turn out to be more fundamental — and, in an important sense, more certain — than the level’s other categories. And indeed, this rhyming pattern does appear to hold: spacetime, being less bound to any one specific physical configuration and more universal than any of the particular material objects it contains, turns out to be more certain and more fundamental than those objects. If the model is correct, we should expect this same rhyming structure to recur across every level’s set of three categories.

    Let us test the rhyme again, this time at the level of Particulars. A variable, the Metaphysical Particular, represents a consistent placeholder value running throughout a given logical or mathematical proposition; it carries a distinctive kind of universality, in that any specific, “accidental” content can be substituted into it without changing the overall logical structure of the framework it belongs to (think again of x in an equation — you can substitute any specific number for x, and the equation’s underlying form remains exactly the same). In an analogous way, matter, the Physical Particular, remains consistent as the basic substrate running throughout any physical system — which is exactly why material reductionism (the view that complex physical phenomena can, at least in principle, be fully explained in terms of their smaller material constituents) is a coherent project to pursue in the first place. Matter can certainly be described using a vast range of competing theoretical frameworks over time — Newtonian corpuscles, quantum fields, string-theoretic vibrating strings, and so on — but my goal in this chapter is not to adjudicate between these physical theories about what matter’s ultimate nature turns out to be; that question belongs to physics proper, not to this philosophical Framework for organizing physics. Indeed, some physicists themselves have advanced broadly idealist views, on which the entire physical world is ultimately some kind of emergent mental phenomenon rather than genuinely mind-independent stuff.

    That idealist possibility, interestingly, would fit quite comfortably within the Source-Particular Model’s overall structure, though the model by no means requires it. Instead, for the purposes of this chapter, we can simply take “matter” to mean whatever general, indivisible physical unit or units end up occupying physical spacetime, whatever their ultimate nature turns out to be. Yes, matter counts here as an ontological category in its own right — but note carefully that this is a claim only about the category itself, not a specific claim about what matter, in its final physical description, actually consists of. Working out that further, more specific question is squarely the job of physicists, not philosophers, and the philosopher can happily wait for the physicist’s verdict. What the philosopher can say with confidence in advance, however, is that matter’s ultimate nature can, in principle, be discovered by physical science — because otherwise we would be left with genuinely “floating,” unmoored laws of physics and chemistry that have no underlying substance to which they actually apply. And because, on this model, our metaphysical commitments come logically prior to our physical investigations, we can also say with confidence that our physical sciences, properly pursued, should not lead us into outright logical absurdities…

    [END OF PREVIEW]

  • An Empathetic Epistemology

    An Empathetic Epistemology

    Wesley Coleman

    Paul Garner’s The New Creationism (2009) is, in its own right, a competent book. Coming to it from within a young-earth creationist framework, I don’t think it’s dishonest or lazy. Garner sets out a defined and modest goal: to demonstrate that plausible scientific models exist which map on to the conclusions entailed by a creationist reading of Genesis. He is not attempting philosophy; there’s no questioning the assumptions of modern science. He is not interrogating his own interpretive assumptions about Scripture; he doesn’t do an explicit run-down justifying his exegetical framework. He takes a run-of-the-mill YEC hermeneutical framework as is and asks, simply, whether science and it can be made to wed. On those terms, he largely succeeds at least for the models available to him in the late nineties and early two-thousands.

    And yet the book is, for my purposes, radically unhelpful. This is not entirely Garner’s fault. On one hand, the evidence and models are out-of-date and the rhetorical style is too summary-driven to build genuine conviction in the reader. On the other hand, he is immersed in a cultural environment which takes many things for granted. But the deeper problem is one the book never acknowledges and, in certain ways, actively compounds. Garner operates within an essentially naturalistic and objectivist model of inquiry. He tacitly embraces the notion that knowledge is an enterprise of neutral evidence-gathering and model-fitting. This makes him hardly different from any other creationists doing science. It’s extraordinarily rare to see anyone asking whether their framework is coherent (or whether they’re uncritically taking on their opponents framework). 

    And within the model he operates, Garner provides data but sidesteps important issues. For example he dismisses radiometric dating on grounds of evidence which could easily be construed as anomalous (at best). He presents plausible stories but gives the reader no tools for weighing them. And finally, his seeming implicit suspicion of those who would question his conclusions, a kind of shy posture of his presentation, makes it very difficult for any genuine skeptic, non-YEC christians included, to engage without feeling pre-judged.

    This points to the real problem, which is not the book’s particular arguments but the epistemological framework it silently assumes and shares with many of its critics.

    Providing good data or a good alternative story is insufficient if the underlying theory of knowledge is broken. Garner’s models, even the best of them, cannot move a reader whose priors are organized differently and he does nothing to address those priors. This is the Bayesian heart of the matter. If I am a committed naturalist, the prior probability I assign to any divine act in history is, by stipulation, effectively zero. No amount of geological evidence for a global flood will alter my conclusions, because the flood’s supernatural cause is ruled out before the first piece of evidence is evaluated. Conversely, if I accept the flood on theological grounds, the rock record opens up in ways that compress geological time dramatically, and evolutionary timescales collapse accordingly. These are not just disagreements about data. Granted there is data involved, but we are using essentially different models to parse it. If it was just data, we could all go do some field work and resolve it relatively simply.

    The trouble is that neither party is typically honest (to themselves) about this. The naturalist often presents their epistemology as though it were simply “ the science.” That is, a neutral view-from-nowhere method that anyone reasonable would adopt. But naturalism is itself a prior, not a conclusion. It is a decision, made before the evidence is examined, about what kinds of causes are admissible. And all our beliefs are this way—they are decisions we commit to prior to evidence or reason. The creationist who dismisses radiometric dating on theological grounds is doing something structurally similar, but at least is usually more explicit about it. They follow “what the Bible says” and filter evidence that way. These are both problematic, of course.

    But what’s more pernicious is the skeptical posture that is invisible to itself. You see, if one assumes that one’s own epistemic tools are simply “rational inquiry” while the opponent’s (the rest of the world) are “faith” or “bias.” The skeptic’s lens changes what they see, but the lens itself goes unexamined. This is the foundational error, and it is not unique to any one side of this debate. In fact, we all do this. I am guilty of this too, no question.

    This epistemological failure has a name when it becomes habitual: suspicion. And suspicion, when it hardens into a hermeneutic, destroys not just arguments but people.

    The suspicious mind does not engage with what its opponent actually says. It looks for what the opponent must really mean. It asks: what’s the hidden motive, the tribal allegiance, the bad faith lurking beneath the surface of the stated position? When someone challenges a cherished belief, the suspicious interpreter does not ask: what is the most charitable reading of this challenge? Instead, they identify the person as either part of their group or not, and use that as a basis for ascribing their reasons and motivations. And having psychoanalyzed the questioner, they feel free to dismiss the question without answering it. This is often called well-poisoning and it comes from the suspicious mind.

    This is a type of hermeneutic of suspicion in its most socially destructive form. It does not show up only in academia, where it has a respectable pedigree. It shows up at the dinner table. It shows up in the conversation between a parent and a child who has started to doubt.

    The pattern is familiar to anyone who has spent time in strongly evangelical or young-earth creationist communities, though it is by no means limited to them (as I have heard of the direct reverse of this example too). A child raises a question. Perhaps about evolution, or about a passage of Scripture that doesn’t sit right, or about the age of the universe. And the question is not answered. It is adjudicated. The parent decides, often unconsciously, that the question is not a genuine inquiry but a symptom of bad influences, of pride, of the first steps away from faith. The question is treated as a threat rather than an invitation. And the child, sensing that their intellectual honesty is being read as betrayal, learns either to stop asking or to stop sharing. Or worse than that, sometimes the child is ostracized, losing that relationship permanently.

    This is a catastrophic failure, and it cannot be fixed by better arguments. The problem is not that the parent lacks a good answer to the question about radiometric dating or archaeological records. The problem is that they have pre-judged the questioner’s intent and, in doing so, have abdicated the most basic responsibility of love: to understand the other person on their own terms before responding.

    And yet, and this needs to be said plainly, the skeptical child is not innocent either. Questions can be genuine, or they can be rhetorical. It is entirely possible to ask a question you already believe you know the answer to, not because you seek understanding but because you want to establish your own position without exposing it to scrutiny. It is possible to use doubt as a crutch, i.e., a way of staying comfortable in uncertainty without doing the hard work of actually following the argument wherever it leads. It is possible to use questions as a tool to demonstrate intellectual superiority, because of the same genus of suspicion the parents may have held. Therefore, neither party in these conversations is automatically the victim. Yet, clearly a parent’s role is quite different, based on their natural responsibilities.

    Moving to another political question in the US, the Governor Spencer Cox situation is a useful illustration of how quickly this breaks down in public life. In the aftermath of Charlie Kirk’s assassination, Cox made a statement that he had prayed the killer would not be a Utah resident. Several media outlets and commentators interpreted this as an expression of xenophobia. They took it as a wish to scapegoat a foreigner. One framing put it that Cox had “hoped to blame the killing on an immigrant.”

    It is perfectly plausible—in fact, considerably more plausible—that Cox simply meant what he said: he had hoped the shooter wasn’t from his own state. No xenophobia or racism needed. But when a person has been categorized as part of an ill-intending elite, suddenly charitable exegesis cannot even be considered. The suspicious reader does not offer the generous interpretation to then reject it. They usually never consider it at all. The conclusion comes first, and the reading is constructed to confirm it. 

    This is the same error the excommunicating parent makes, and the same error the dismissive skeptic makes. It is a one-and-the-same error of deciding, in advance, that the person you disagree with is not rational enough, or honest enough, or good-faith enough, to be taken at their word.

    There is no logic or facts-based fix for this. You cannot reason someone out of a posture they did not reason themselves into. But there is a solution, and it begins with a simple commitment: empathy.

    This means resisting the first interpretation that comes to mind when someone challenges your worldview, and asking whether there is a more generous reading. It means treating the person across from you as someone who arrived at their position through some combination of experience, reasoning, and honest conviction—how would you be able to tell otherwise, anyway? It means being willing to say “I don’t know” without treating that admission as a defeat and being willing to accept that some will treat it as victory. It means recognizing that your own epistemic tools are not neutral, that your priors are not simply reason, and that the discomfort of examining them is the price of intellectual honesty.

    For Christians and creationists in particular, though again, this applies broadly, there is something theologically incoherent about treating people who ask hard questions as enemies. If you believe that truth is not threatened by honest inquiry, then honest inquiry should not threaten you. If you believe that love is the first obligation, then the person asking the question is the first obligation—not the question.

    Ken Ham has no difficulty identifying who is wrong and explaining why. That is easy. What is harder, and what matters infinitely more, is how you treat the person who is wrong (or who you believe is wrong). How you treat people in the moment of their doubt is not a secondary concern, it is the real work. The only work that can actually open a conversation rather than close one.

    So how do we have an open conversation? How do we have an empathetic mind? We need to be able to step back and ask: “Why are you asking that question? What’s behind it?” Asking that first protects you from falling into the trap of holding suspicion. The alternative is a world of building walls. We need to step back from the approach to conversation-as-war. It’s not. So many of us act like it is, and the damage matters here. It makes the cost of even asking questions too high a barrier for entry.

    Openness is, as it happens, the only epistemic strategy that can actually get you to the truth. Not the indifferent agnostic openness, but active, deliberate, uncomfortable practice of checking your own worst interpretations against the most generous alternative. When you catch yourself saying that someone is lying, stop. When you find yourself assuming that what a person plainly says must really mean something more sinister, stop. These are not signs of rigor or a critical mind. They are signs that you have prioritized the security of your own position and a suspicious mind over the person standing in front of you. Therefore, we should trade our suspicious mind with an empathetic mind which strives for humility, generosity, and grace in interpretation.

    Citations:

    Balta, Hugo. “Governor Cox’s Prayer Wasn’t Just Misguided—It Was Dangerous.” The Fulcrum, 14 Sept. 2025.

    Garner, Paul. The New Creationism. EP BOOKS, 2009.

  • Is Young Earth Creationism Irrational and Harmful?

    Is Young Earth Creationism Irrational and Harmful?

    Recently the popular creation skeptic Randal Rauser, who goes by the Youtube moniker of “The Tentative Apologist,” posted a video titled, “Why Young Earth Creationism is Irrational and Harmful.” In it, he laid out his case for why evangelicals should not embrace young earth creation as well as a general methodology for laymen wherein they conform to the expert opinion—specifically the expert majority opinion. While I do believe he is good-hearted and well meaning, the video exemplified the innate depravity of the modern “scientismist” view. He covered the bases so well and so thoroughly that I thought it apt to do an in-depth exegesis and logical analysis of the claims he made. My hope is that this case study can be instructive on how to critically think, this is not meant to be a dunk on Rauser.

    Argument #1: Social Contingency

    He begins his criticism of the young earth creationist movement by citing the book “The Creationists” by Ronald Numbers. Dr. Numbers is a historian of science who was the son of a fundamentalist Seventh-day Adventist preacher and later left becoming a self-proclaimed agnostic. Numbers’ thesis is that the modern movement of creationism began as an Adventist movement. Rauser notes:

    “The modern creationist movement actually comes from Seventh Day Adventism and particularly young earth creationist George McCready Price… As a result, young earth creationism became the mainstream view held by the emerging fundamentalist movement of the 1920-30s which was a reaction to the growth and perceived compromise of mainstream denominations and university-based divinity schools.”

    The real beginnings of modern creationism started not by an Adventist in the 20s but by Baptists in the 60s. Although Rauser acknowledges this, he points out that “The Genesis Flood” by Morris and Whitcomb was heavily influenced by Price’s work several decades earlier. While it is true that Price played a large role in the model put forth in the 60s, it is important to note that Price, Morris, and Whitcomb were not writing in a vacuum. 

    Who was Price influenced by? And if we are to say (rightly) not by Adventists, then you cannot simply argue that modern young earth creationism is an adventist movement.

    Price was citing Anglicans, Presbyterians, Congregationalists, Baptists, and Reformed geologists. To name a few non-adventist geologists: Thomas Burnet (Telluris Theoria Sacra, 1681), John Woodward (An Essay Toward a Natural History of the Earth, 1695), William Whiston, Granville Penn, George Fairholme, Sharon Turner, George Young, George Bugg, John Murray, David Lord, and Tayler Lewis.

    Seventh-Day Adventism wasn’t alone in holding to young earth creationism at that time, either. Many traditional Christian denominations—including Anglicans, Lutherans, and Eastern Orthodox all held semi-official doctrines or official dogmas on the young age of the earth. Figures like the Anglican Bishop James Ussher, Lutheran doctrines and dogmas such as the Westminster Standards (1643–1649) and the 1967 resolution of the LCMS affirmed the six day creation and young earth, and the Orthodox Anno Mundi calendar (held as the official calendar in most Eastern traditions) dates creation to approximately 5508 BC. Some modern Orthodox theologians argue that a literal reading of Genesis 1–2 remains the historic teaching of the church up until the 19th century.

    While it is true, Price definitely filtered the former creationist flood models and understandings through his adventist interpretive framework, yet Morris and Whitcomb filtered Price through their Baptist/Evangelical framework.

    This is all very important to bring up because Ronald Numbers’ view of the history of creationism is a very prevalent one in current culture and it is told by people who either fallaciously aim to discredit the movement as a prophetic fad or seek to over emphasize credit to Price, likewise to dismiss the important work of early creationist field geologists. Both of which count as genetic fallacies, of which we will cover shortly.

    So, then, why does Rauser, himself, open with this remark (of all remarks)?

    His answer:

    “It doesn’t make young earth creationism right or wrong—it doesn’t tell you anything per se about the science, but it does show you the social contingent historical origins of the young earth creationist movement. And for people who are taught, then, that young earth creationism just is the standard historical orthodox christian perspective to understand and see through the lenses of a historian just how contingent and limited the origins of this modern movement are, really helps to contextualize it and raise the level of prima facie skepticism that one should have about this movement.”

    Rauser is being fair when he points out this cannot be evidence of the truth of young earth creationism. And, for a second, I just want you to pause on that.

    He has realized that if he were to do so, it would be a genetic fallacy. That is, it would be a dismissal of the arguments and evidence of creationism, not on the basis of evidence, but on the basis of source or origin.

    Unfortunately for Rauser, the point he ends up making is likewise… a genetic fallacy. To argue that a movement, especially and particularly of the movement of scientific inquiry, can be discredited because the scientists who penned it were unorthodox is to deny the entire enterprise of science altogether.

    He argues fallaciously to what end?

    In order to “raise the level of prima facie skepticism.” Prima facie is latin for “at first sight.” What Rauser is communicating to us is that we should make a prior commitment to the falsity of the creationist movement. 

    Based on what grounds? 

    On the fallacious grounds of a socially contingent historical analysis, that is moreover historiographically asymmetric and based on the presuppositions of a former seventh day agnostic critical scholar. This is essentially a non-attempt to engage with any evidence (apart from pseudo history). In the philosophy of science, all movements are socially contingent.

    To his credit he mentions Bishop James Ussher, however methinks he doth protest too much.

    “And just to be cautious here, I do clarify that this is modern. There have been young earth creationists throughout history. The most famous example is Arch Bishop James Ussher, a British theologian and Bishop who attempted to date the origins of the universe to 4004 BC, writing in the seventeenth century. But his views aren’t the same as the modern young earth creationist movement that really traces to this influx of seventh day adventist prophetic theology into modern fundamentalism.”

    Well, I’ve got exciting news, Rauser! Modern creationists don’t hold to Price’s view either. In fact, modern flood geology is based on models of catastrophic plate tectonics (CPT) which were exposited by Dr. John Baumgardner in the 90s. The model has been refined since then, but it is the model of neither Price nor Morris and Whitcomb.

    This is what’s often called, in philosophy, a symmetry-breaker. You see, Rauser wanted so badly to articulate that early creationists, that are not Adventists, don’t count because they have different models. But if that rule were applied evenly, the start of the modern creationist movement would be pushed to the late 90s! If Rauser defines a movement by its specific mechanics (e.g., Price’s specific model), then he cannot logically link Morris and Whitcomb to Price while simultaneously distancing Ussher from Morris.

    Argument #2: Appeal To Experts

    Rauser begins his next line of argument with a question:

    “The first thing I want to ask whenever people come up with a minority view is: ‘what do the experts say on a particular issue?’ This is true across the board. We should be very careful about engaging in special pleading where we apply a different standard in one area than another just because that suits our bias.”

    The first thing I would like to ask Rauser is: what is an expert?

    To evaluate who the experts are and which experts to defer to, you already need independent critical judgment. Yet, to say that we should rely on experts is an explicitly uncritical statement.

    Rauser warns against special pleading, yet his own methodology treats historical science as if it were identical to operational science. We defer to “experts” like surgeons or pilots because their expertise is constantly validated by immediate, repeatable results. If a surgeon is “irrational,” the patient dies; if a pilot is “irrational,” the plane crashes.

    In contrast, “experts” in historical geology or evolutionary biology are constructing narratives about the unobservable past. There is no immediate “feedback loop” from reality to verify their conclusions. By demanding the same level of uncritical deference for historical narrative as we give to operational technology, Rauser is the one engaging in a form of special pleading.

    This is not to say Geologists don’t make predictions about, say, where to find oil, what rock strata will look like in unexplored regions, which fossils should exist in which layers… and those predictions get tested. But these are distinct from the narrative they tell about the data. The framework is what is in question in the origins debate, not the facts on the ground.

    To make Rauser’s argument clear, we can formulate it in a syllogism:

    Premise 1: Most minority views are wrong.

    Premise 2: Creationism is a minority view.

    Conclusion: Therefore, it is rational to assume Creationism is wrong.

    While, you might suppose premise one to be statistically probable generally, the problem is that it’s an extremely weak inference that does almost no epistemic work, especially when the minority view comes with substantive arguments that need engaging on their merits.

    It only takes a few history books to see that in every case, the maverick was right and the credentialed majority was wrong. Wegener had his continental drift theory rejected for decades by the geological establishment despite compelling evidence, Galileo was faced against ecclesiastical and academic authority simultaneously, Fleming was largely ignored for over a decade after discovering penicillin, and J Harlen Bretz proposed a massive catastrophic flood event which was ridiculed by the geological establishment for roughly 40 years. Other examples which we more readily accepted, but still independent thinkers are Copernicus, Bacon, Newton, Einstein, Pasteur, McClintock, Marshall and Warren with H. pylori.

    That’s not to mention the founders of the mainstream paradigm: Hutton, Lyell, Darwin, Wallace, and Mendel. Hutton and Lyell had to fight tooth and nail against flood geology in intense philosophical debate. Darwin and Wallace spent decades contesting the theory of natural selection. Mendel was entirely ignored for 35 years and only rediscovered posthumously. Yet, these are their icons. This is literally historical amnesia. How can Rauser seriously be saying that we should just default to the consensus? How could any science be done that way?

    This is not to say that creationism is right or that the minority is right. I only claim the epistemically humble position: the experts aren’t always right. However, can we embrace his less abrasive claims?

    “Experts are not infallible, but all things being equal, you want to go with the experts… You don’t want to go, all things being equal, with the very significant minority.”

    This is a particular and different claim. Notice that in the equation he’s drawn, there are no non-experts. But he argues, the majority of experts will be a better place to hang one’s hat—all things being equal.

    All things being equal.

    I want to highlight a couple angles on this qualifying phrase that Rauser uses. First, what does it mean for all else to be equal? How is that metric reached?

    In order to evaluate equality, we need some metric to evaluate the models in question. This means evaluating their explanatory power, internal consistency, relation to the data, and presuppositions. Yet, by the time you’ve done this, you are no longer relying on the experts, you are doing the work of an expert. 

    Rauser is asking the layman to exercise a form of meta-expertise. He is suggesting that while a layman isn’t qualified to judge the geology, they are qualified to judge the geologists.

    This is a precarious position. If a layman is not equipped to understand the nuances of Catastrophic Plate Tectonics (CPT) vs. Uniformitarianism, how are they equipped to judge the social and institutional pressures that produce a “majority”?

    What’s more, in the origins debate, “all else” is never equal because the starting presuppositions are diametrically opposed. You can’t even get any kind of equality when the foundations of either edifice cannot be compared to begin with.

    Argument #3: You Have To Teach!

    He closes that section off with a criterion for engagement:

    “Here’s a basic way to test your expertise: how prepared are you right now to give a one hour introductory lecture to any of these fields… geochemistry, or geochronology, or molecular biology?… The ability to give a one hour lecture is at least a minimal threshold to even have a further conversation.”

    Rauser’s “one-hour lecture” rule is an elitist filter that ignores how human knowledge actually functions. You do not need a degree in geochemistry to identify a logical contradiction in a geochemist’s paper, nor do you need to be a molecular biologist to understand the statistical impossibility of certain evolutionary transitions.

    Take the example of a court of law. In a court of law, we do not require jurors to be able to give a one-hour lecture on DNA sequencing or ballistics. We expect them to use their independent critical judgment to weigh the testimony of competing experts.

    Furthermore, most experts are hyper-specialized. A molecular biologist might not be able to give a one-hour lecture on geochronology, yet Rauser would likely still accept their “expert” opinion on the age of the earth simply because they belong to the same “consensus club.”

    Argument #4: You Have To Explain!

    “If you are a young earth creationist and you’re dismissing 98-99% of experts, you then have to give an explanation for how 98-99% experts could be wrong about some significant issue like the age of the universe, the age of earth, and the origin of species upon the planet. And this is where we’re going to tend to come into accounts which are boarding in the dangerous area of conspiracy theories.”

    Rauser says you “have to give an explanation” for how the experts could be wrong. The explanation is actually quite simple and historically grounded: Science is not a democracy. Truth is not determined by the number of PhDs who agree, but by the correspondence of a model to the physical data.

    When the majority holds to a flawed paradigm, they will consistently interpret all new data to fit that paradigm (a process called “epicyclic adjustment”). It takes a maverick to step outside the circle and show that the data actually fits a different, more robust model—like Catastrophic Plate Tectonics.

    By labeling this “conspiratorial,” Rauser is effectively saying that the only rational choice is to never challenge a majority. This is the very definition of historical amnesia.

    “Maybe you’re influenced by Thomas Kuhn’s historical understanding of the progress of science and you say ‘all these evolutionists are just locked into a naturalistic paradigm and they can’t see all the evidence for young earth creationism.’ But what that effectively does is it’s going to breed skepticism about expertise generally which is probably going to spill into other areas… in favor of various conspiracy theories.”

    Please, reader, take a big gulp of the irony here. There is enough to go around.

    The skeptic is worried about skepticism. The very people who will argue that Christianity or theism are ridiculous. The very people who can hold much incredulity to the largest consensus belief in the world are now going to explain why skepticism is a bad methodology.

    By warning against skepticism, Rauser is effectively discouraging the very “critical thinking” he claims to promote. To be “critically minded” is, by definition, to be skeptical of claims—especially those that demand uncritical deference.

    If an expert cannot explain the data to a thinking layman without resorting to “trust me, I’m an expert,” then their expertise has become a form of sophistry.

    Argument #5: The Harmful Belief

    “All of this means that allowing young earth creationism to proliferate unchallenged among the evangelical and fundamentalist protestant Christian subculture does enormous damage to the integrity and the witness of Christianity in North America.”

    This last point is supremely interesting. Does he think, first of all, that creationism has gone unchallenged in Western society? Even among evangelical and fundamentalist movements, there is a clear pressure to conform to the infallible doctrine of scientism.

    Does he think the Christians will gain ground in culture, if we give up ground? Will we convert more to the truth, if we tell lies?

    Let’s call out this appeal to the harm of young earth creationism for what it is—eurocentric scientific elitism. This argument only carries weight in the West, and it should really carry weight nowhere, because it is simply not an argument.

    Final Thoughts:

    Rauser’s case study is a masterclass in Scientism—the belief that the methods and conclusions of the natural sciences are the only source of genuine knowledge. His methodology requires the layman to be a passive consumer of institutional output rather than an active, critical thinker.

    By deconstructing his arguments, we’ve shown that:

    1. His history is socially contingent and misses the broader tradition and trends.
    1. His “Expert Appeal” is circular and ignores the history of scientific revolutions.
    1. His “Lecture Test” is elitist gatekeeping which ignores how we evaluate data.
    1. His “Harm” argument prioritizes social comfort over consistency and truth.

    To summarize, we should evaluate each model based on the evidence, parsimony, predictive success, presuppositions, coherence, consilience, etc—take your pick. We should not be evaluating the models on external factors such as perceived harm, individual comprehension, appeals to consensus, appeals to experts, and appeals to novelty or social contingency. These in the latter list do not help us in the project of “how to think.” And the project of “who to trust” has always been a very dangerous game.

  • Elucidating the Initial Heterozygous Gene Families

    Elucidating the Initial Heterozygous Gene Families

    PREVIEW ARTICLE

    Excerpts from ABSTRACT, INTRO, & PART IV

    Abstract

    The Created Heterozygosity and Natural Processes (CHNP) model, proposed by Nathaniel Jeanson (Jeanson, 2016), suggests that a significant amount of genetic diversity in originally created organisms was frontloaded rather than accumulating slowly through random mutations. Implicit in Jeanson’s model is the postulate that all diversity in humankind has emerged from two biallelic individuals. Little work has been done to explicate original allelic morphologies in created kinds, therefore this study will address this gap in the CHNP model by identifying functional genes (the frontloaded heterozygosity) and their deleterious variants. This study also aims to give quantified rates of mutations necessary for novel allelic frequencies. Doing so allowed for testing the two primary predictions of the CHNP model: (1) Mutations accumulate at a semi-constant rate, and are sufficient to explain novel diversity beyond the initial biallelic kinds and (2) initial created kinds were highly functional and optimized, containing no non-functional or suboptimal gene variants, therefore only function will be shared across lineages. We analyzed a variety of gene families (including CLLU1, MHC, LCT, ABO, Rh, KIR, NANOG, AMY1, DARC, GULO, and FOXP2) and found that initial functional alleles are highly conserved across species, while loss-of-function alleles are species-specific. Balancing selection reveals conflicting and contradictory hypotheses for the origin of alleles leading to the evolutionary explanations becoming ad hoc. The observed mutation rates for diversification of original biallelic pairs falls in the estimated 6000-year timeframe. These findings dovetail with prior CHNP research for known modern rates of molecular clock data (Jeanson, 2019). The results of this data are best explained by the CHNP model, as these genes produce young, discontinuous phylogenetic trees which begin with two variants and later branch into homozygosity. The data strongly supports genetic drift, founder effects, and weak selective pressure for all gene families.

    Introduction

    The key tenets of CHNP are frontloaded genetic diversity followed by rapid diversification into more homozygous populations via recombination, genetic drift, and regulatory mechanisms all amplified by major and minor founder effects. In CHNP, mutations are seen as creating new allelic variation by degrading the optimized biallelic state in various ways. CHNP, therefore, follows the principles of genetic entropy (GE) and chemical laws (Sanford, 2008). The selected gene families support this view as well as known chemical and structural mutation hot spots. The assumption of design is taken for granted in this paper, however much research has been done to support this inference and the problem of the insufficiency of naturalistic processes (Axe, 2004; Meyer, 2004; Meyer, 2021; Nelson & Buggs, 2016; Thorvaldsen & Hössjer, 2020). CHNP provides a coherent alternative framework to explain the abundance of genotypic and phenotypic diversity we observe in the biological world by emphasizing a pre-existing, divinely-created potential for variation, which is then expressed and refined through natural processes over a much shorter timeframe than mainstream evolutionary models propose.

    Being a relatively new evolutionary framework (a little over a decade old), CHNP has yet to elucidate particular historical details such as the evolution of the diversity of alleles. This has led to some popular-level critiques from well-meaning skeptics of the model making serious errors in their assessments (Duff, 2023; Hancock, 2023). Questions have been raised along the lines of: (1) How does CHNP account for the wide diversity and sheer number of alleles in modern human populations, when Adam and Eve could only account for a maximum of four alleles? (2) How does a human population maintain this initial variation of a biallelic couple over generations and then increase in variation? This paper successfully accounts for both challenges: There is overwhelming evidence that all the diversity at different loci for human alleles can be explained by two original humans with the same bi-allelic autosomes. The disparity (divergence in morphospace) and diversity (increase in morphologies) is then created by both homologous recombination and mutational load/GE, respectively.

    Works Cited

    Axe, Douglas D. “Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds.” Journal of Molecular Biology, vol. 341, no. 5, Aug. 2004, pp. 1295–1315, https://doi.org/10.1016/j.jmb.2004.06.058.

    Duff, Joel. “Does Created/Designed Heterozygosity Make Sense? Reacting to Drs. Hancock and Jeanson.” YouTube, 23 Aug. 2023. https://www.youtube.com/watch?v=M_ZQ0jpkeE0.

    Hancock, Zach B. “Designed Diversity Is Nonsense.” YouTube, 21 Aug. 2023. https://www.youtube.com/watch?v=jDo3FRMFCW0.

    Jeanson, Nathaniel. “Origin of Human Mitochondrial DNA Differences.” Answers Research Journal, vol. 9, p 123–130, Apr. 27, 2016. https://answersresearchjournal.org/origin-human-mitochondrial-dna-differences/.

    Jeanson, Nathaniel. “Testing Predictions for a Human Y Chromosome Molecular Clock.” Answers Research Journal, vol. 12, p 405–423, 4 Dec. 2019. https://answersresearchjournal.org/human-y-chromosome-molecular-clock/.

    Meyer, Stephen C. “The Origin of Biological Information and the Higher Taxonomic Categories.” Proceedings of the Biological Society of Washington, vol. 117, no. 2, 4 Aug. 2004, pp. 213–239. https://www.discovery.org/a/2177/.

    Meyer, Stephen C. “The Return of the God Hypothesis: Compelling Scientific Evidence for the Existence of God.” HarperOne, 30 Mar. 2021.

    Nelson, Paul A., and Richard J. A. Buggs. “Next Generation Apomorphy: The Ubiquity of Taxonomically Restricted Genes.” Next Generation Systematics, by Paul A. Nelson and Richard J. A. Buggs, Cambridge University Press, 5 June 2016, pp. 237–263. 10.1017/CBO9781139236355.013.

    Sanford, John C. “Genetic Entropy & the Mystery of the Genome.” FMS Publications, 2008.

    Thorvaldsen, Steinar, & Ola Hössjer. “Using Statistical Methods to Model the Fine-Tuning of Molecular Machines and Systems.” Journal of Theoretical Biology, vol. 501, no. 110352, Sept. 2020, https://doi.org/10.1016/j.jtbi.2020.110352.

    Part IV: ABO

    The ABO blood group, the first human blood group system discovered, remains a cornerstone of evolutionary biology and anthropology. The standard evolutionary model seeks to explain the persistence of the A, B, and O alleles in human and other primate populations through a concept known as “trans-species polymorphism.” This hypothesis posits that certain alleles are maintained by balancing selection for millions of years, predating speciation events. Consequently, the functional A and B alleles are argued to be approximately 20 million years old, having originated in a common ancestor and been preserved through the evolutionary divergence of modern primate branches (Ségurel et al., 2012). This ancient origin is believed to be the reason why humans, chimpanzees, gorillas, and other primates and mammals share the same genetic basis for the A and B antigens. Some mammals, such as cows, dogs, and cats, which are said to have diverged from the primate line over 80-90 million years ago, still maintain functional A and B alleles which are said to have been convergently evolved.

    1. The Paradox of the ‘O’ Allele

    While the A and B alleles are functional—coding for glycosyltransferase enzymes that attach specific sugars to red blood cells—the O allele is non-functional, or “null.” The O phenotype arises from mutations, typically single nucleotide polymorphisms (SNPs) or insertions/deletions (InDels), that introduce a frameshift, resulting in a non-working enzyme. From a molecular perspective, the mutational pathways to a null allele are numerous and common; it is far easier to break a functional gene than to create one.

    This molecular reality is coupled with a powerful selective pressure: the O allele confers significant resistance to severe forms of malaria. Given that malaria is a potent selective force in many regions of the world, and that primates have purportedly been evolving in such environments for millions of years, a paradox emerges. If the functional A and B alleles were maintained for 20 million years, then the highly advantageous and mutationally accessible O allele should have appeared constantly throughout this timeframe. Natural selection should have preserved it just as diligently, if not more so, than A and B. The logical prediction of the evolutionary model is, therefore, that the O allele should also be ancient and shared by descent among primate species.

    2. Genetic Evidence Falsifies this Evolutionary Prediction

    Contrary to the prediction derived from the deep-time model, genetic data reveals the precise opposite. While the functional A and B alleles show evidence of shared ancestry, the non-functional O alleles are demonstrably recent and species-specific. A key study by Ségurel et al. (2012) states this finding unequivocally:

    “Thus, primates not only share their ABO blood group, but also the same genetic basis for the A/B polymorphism. O alleles, in contrast, result from loss-of-function alleles such as frame-shift mutations and appear to be species specific.”

    Another paper researching non-primate ABO polymorphisms, from Kermarrec et al. (2017), wrote:

    “The sequences of cDNAs corresponding to the chimpanzee and rhesus monkey O alleles were characterized from exon 1 to 7 and from exon 4 to 7, respectively. A comparison of our results with ABO gene sequences already published by others demonstrates that human and non-human primate O alleles are species-specific and result from independent silencing mutations. These observations reinforce the hypothesis that the maintenance of the ABO gene polymorphism in primates reflects convergent evolution more than transpecies inheritance of ancestor alleles.”

    This means the specific mutations that create the O allele in humans are different from the mutations that create the O allele in chimpanzees, which are different from those in bonobos, orangutans, gorillas, etc. This is definitive proof that the O allele is not shared from a common ancestor. Instead, its appearance is convergent, having arisen independently in each lineage. The central question remains: if the O allele is so advantageous and easy to make, why did it not appear and become fixed or conserved anciently?

    Evolutionary genetics has proposed several auxiliary hypotheses to resolve this paradox, none of which withstand scrutiny:

    The Pathogen Trade-Off Hypothesis: 

    One proposal is that the O allele was constantly eliminated by negative selection because it confers vulnerability to other pathogens, such as gut bacteria like Vibrio cholerae. However, this is empirically falsified by the existence of entire populations, such as Native Americans, who are nearly 100% Type O and thrived for millennia prior to European contact. This demonstrates that any disadvantage cannot be a universal evolutionary law sufficient to prevent the fixation or preservation of the O allele over tens of millions of years.

    The Malaria-Smallpox “Tug-of-War” Hypothesis: 

    A more complex hypothesis has been invoked to explain the balanced allele frequencies in Europeans, where malaria was endemic but did not seem to exert the same selective pressure. This model suggests a selective “tug-of-war,” with malaria selecting against A and B, while smallpox targeting the foundational H-antigen (most exposed in Type O individuals), thereby selecting for A and B. However, the link between smallpox and blood type is based on conflicting and weak evidence. The foundational studies from the 1960s were heavily criticized by peers as likely reflecting methodological artifacts, while other comprehensive studies found no statistically significant link at all (Downie et al., 1965). Furthermore, genetic analysis of ancient European populations shows the O allele was present prior to widespread agriculture and malaria pressure, and its distribution shows no clear correlation with ancient malaria patterns (Gelabert et al., 2017). Given the challenges and apparent ad hoc nature of these explanations, it is valuable to consider an alternative framework that may account for the data more directly.

    3. Phylogenetic Structure and Mutation Counts in ABO

    The ABO system’s 345 recognized alleles (ISBT v11, January 2026) form a tree-like phylogeny rooted in an ancestral A-like sequence, with major branches forking via defining core events and subtypes adding derivatives. This structure collapses observed diversity into ~150–200 unique nucleotide changes (mostly SNPs and indels), far fewer than independent origins would require. Functional A and B alleles are conserved across species, while loss-of-function O variants are species-specific, supporting CHNP’s frontloaded heterozygosity.

    Table 1: Cumulative Missense Mutations by ABO Phenotype

    The table below summarizes missense mutations (amino acid-altering changes) across 207 alleles from a detailed dataset, grouped by phenotype. These represent cumulative instances relative to reference A¹ (ABO*A1.01).

    Phenotype Group# of AllelesTotal Missense MutationsAvg Mutations per Allele
    A Subtypes
    A1 (Reference)210.5
    A218321.8
    A37101.4
    A (Weak/Other)*55831.5
    B Subtypes
    B (Core)3144.7
    B (Weak/Other)**462305.0
    O Subtypes
    O (Null)621302.1
    Hybrids
    cis-AB / B(A)12423.5
    TOTAL2075442.6

    Note: *Includes Aweak, Ael, Afinn, Am, Ax. **Includes B3, Bel, Bweak, Bx. The low average divergence (2.6 mutations) across hundreds of alleles supports the CHNP view of recent diversification from highly functional progenitors, rather than deep-time accumulation.

    Table 2: Cumulative Missense Mutations by ABO Phenotype

    Analysis of 207 detailed alleles showing the distribution of amino acid-altering changes relative to the reference A1 allele.

    Branch / CladeAllele Count (Est.)Core Mutation Events (Defining the Branch)Derivative Diversity (Unique Events)Representative SubtypesEvolutionary Mechanism
    A (Ancestral)~600 (Reference State)~40A¹, A², A³Original State: Variations arise via single SNPs (e.g., p.Pro156Leu).
    B (Divergent)~1007 (nt substitutions)~30B, B³, BʷFrontloaded Variant: Core differences (c.526C>G, etc.) likely created; tips show degradation.
    O (Null)~1501 (c.261delG Frameshift)~20O¹, O², O³Loss of Function: Dominant inactivation event followed by drift/selection (Malaria).
    Hybrids~35Chimeric Fusions~10cis-AB, B(A)Recombination: Fusion of A/B cores; not de novo creation of new information.
    OVERALL345~10 Core Events~100–150Parsimony: <200 unique events explain all 345 alleles.

    The “Bushy” structure of the tree—short branches radiating from specific cores—aligns with the “Pulse-Fragmentation” model below. The high allele count is an illusion caused by counting slight variants of the same few functional themes.

    Table 3: ABO Phylogenetic Tree

    Above is a phylogenetic tree for the ABO blood group gene based on the CHNP model. Showing several mainline alleles as well as two case bases (cis-AB and A3) which arose from, among other events, intragenic recombination. A-end and B-end represent further variants of weak A or B and O alleles.

    This model shows alleles cluster into 6–8 major clades with low divergence (avg. 1.5 nt/allele beyond cores), consistent with young, discontinuous trees.

    4. Implications for the CHNP Model

    Mutation Budget

    To evaluate whether the observed diversity in the ABO gene is consistent with the CHNP model (a ~6,000–10,000 year timeframe), we must calculate the expected number of mutation events using established human mutation rates. The ABO gene spans approximately 24,000 base pairs (24kb). The standard human mutation rate is estimated at 1.1 X 10-8 per base pair per generation (Roach et al., 2010; Campbell et al., 2012).

    Traditionally, we analyze this “budget” like so. The number of mutations separating a modern individual from the original ancestor, Lineage Accumulation. In a single direct lineage from a founder (e.g., Adam) to a modern human, the expected number of de novo mutations in the ABO gene is calculated as: 

    Mutations = Rate (1.1 x 10-8) x Gene Size (24,000) x Generations (low 200 to high 333)

    (1.1 x 10-8) x 24,000 x 333 (or 200) ≈ 0.087912 mutations (or 0.528)

    A modern individual is expected to differ from the ancestral sequence by less than 0.1 mutations on average.

    This indicates that the 127–200 unique variants observed today cannot be the result of accumulation along a single line. They must represent a collection of rare variants preserved from a much larger total inventory of events across the population.

    While a single lineage accumulates little change, the population as a whole generates massive diversity due to exponential growth. Modeling a population expansion from a bottleneck of 6 individuals to 8 billion over 333 generations, we can estimate the total number of mutation events that have occurred in the ABO gene history. The total human mutations (genome-wide) are ~4.40 x 1011 (440 Billion) events. 

    The ABO gene represents ~0.0008% of the genome. For ABO specific events, we calculate 4.40 x 1011 x (24,000 / 3.2 x 109) = 3.3 million events. Therefore, the CHNP model faces a “retention” challenge rather than a “production” challenge. The young human population has generated over 3.3 million mutation events in the ABO gene history, far exceeding the ~200 unique alleles observed today. The vast majority of these 3.3 million events were lost to genetic drift or purifying selection (ABO incompatibility). The presence of ~200 unique alleles is mathematically possible within 6,000 years, provided that these specific variants survived drift.

    The observation that most alleles are “subtypes” of A or B (differing by only 1 SNP) is consistent with them being recent survivors from this large pool of 3.3 million historical events. The ABO locus’s genetic diversity—345 alleles arising from ~127–200 unique mutations—must be understood in the context of population-wide mutation loads. While a single lineage accumulates negligible change (<1 mutation), the global human population has generated an estimated 3.3 million mutation events in the ABO locus over the last 10 millennia. The observed ~200 unique variants represent a tiny fraction (<0.01%) of this historical inventory that successfully reached detectable frequencies. This supports a model where the core A and B alleles were frontloaded, while the “bushy” diversity of subtypes (including the various O alleles) arose recently from the vast reservoir of population-wide mutations.

    Paternal Age Effect

    Standard evolutionary calculations assume a constant mutation rate based on a 20-to-30-year generation time. However, the CHNP model posits distinct biological parameters for the early human population, specifically the extreme longevity of the Patriarchs (e.g., Noah, Shem, Arphaxad). Modern genetic research confirms a strong Paternal Age Effect, where the number of de novo mutations passed to offspring increases exponentially with the father’s age due to continuous cell division in the male germline (Kong et al., 2012).

    For example, a 30-year-old father transmits ~45 new mutations. Whereas, if the mutation rate doubles every ~16.5 years of paternal age (as observed in modern humans), a father conceiving at age 100, 200, or 500 would transmit hundreds or potentially thousands of de novo mutations in a single generation.

    Table 4: Patriarch Exponential Mutation Curve
    Father’s Age at ConceptionStandard Model (Total Mutations Transmitted In X Years)Patriarchal Model (Projected Mutations)*Impact Factor
    30 years (Modern Avg)~45~451x (Baseline)
    63 years~90 (gen 2)~1802x
    100 years~135 (gen 3)~850~6x
    200 years~270 (gen 6)~56,000**~207x
    500 years (e.g., Noah)~720 (gen 16)SaturationExplosive

    *Projections based on a doubling of the mutation rate every 16.5 years of paternal age (Kong et al., 2012). **Theoretical projection highlighting the exponential potential of long-lived germlines.

    This biological reality suggests that the “Input” of mutations in the first millennium of human history was not linear but explosive. The initial mutation inventory was likely frontloaded by these long-lived progenitors, rapidly diversifying the created template far faster than current low-fidelity rates would predict.

    Demographic Accelerants: Inbreeding and Fixation

    Following the population bottlenecks (Creation and the Flood), high rates of consanguinity (inbreeding) were unavoidable. While modern population genetics views inbreeding primarily as a mechanism for exposing recessive traits, in the CHNP context, it serves as a powerful evolutionary accelerant in two ways:

    1. Rapid Fixation via Drift: In small, inbreeding populations, the coefficient of genetic drift is high. New mutations—whether generated by patriarchs or random errors—can move from 0% to 100% frequency (fixation) in just a few generations. This overcomes the “swamping” effect seen in large populations, allowing unique ABO variants (like specific O alleles) to become characteristic of entire distinct lineages instantly.
    2. Accumulation of Genetic Load: Inbreeding depresses the effectiveness of purifying selection (“Inbreeding Depression”). Slightly deleterious mutations (such as the degradation of the A antigen into O) are less effectively weeded out in small populations (Lynch et al., 1995). This relaxes the selective constraints, allowing loss-of-function alleles to accumulate and persist at rates that would be impossible in a large, randomly mating population.

    The Pulse-Fragmentation Model

    When these factors are integrated, the CHNP model predicts a specific pattern:

    1. Pulse: A surge of mutational diversity generated by high-age Patriarchs.
    2. Fragmentation: Rapid isolation of this diversity into distinct gene pools via inbreeding and migration.
    3. Degeneration: The inevitable slide from heterozygous function (A/B) to homozygous dysfunction (O) due to entropic forces.

    Additional Considerations

    • Phylogenetic Tree Structure: ABO’s bushy clades (e.g., weak B from B core + 1–2 missense) exemplify recurrent inheritance, reducing independent events.
    • Parsimonious Evolutionary Model: <200 uniques suffice for all diversity, aligning with CHNP’s recent, bottlenecked history.

    Conclusion

    The ABO locus’s genetic diversity—345 alleles arising from ~127–200 unique mutations—is within the expected mutation budget under the CHNP model (~330 events over 10 kyr). The phylogenetic tree structure, with subtypes branching from a handful of core ancestral mutations (e.g., A-to-B divergence), supports a parsimonious evolutionary framework where recurrent propagation explains observed variation. Pre-loaded A and B alleles could plausibly have diversified via neutral drift in a young human population, consistent with CHNP claims. The observed genetic diversity at the ABO locus, with 127 to 200 unique mutations, is within the expected range of mutations under the CHNP model. This indicates that the pre-loaded A and B strings could have been accumulating mutations for around 10 kyr, consistent with the CHNP claim for ABO.

    Works Cited

    Besenbacher, Søren, et al. “Novel Variation and de Novo Mutation Rates in Population-Wide de Novo Assembled Danish Trios.” Nature, vol. 6, no. 1, 19 Jan. 2015, https://doi.org/10.1038/ncomms6969.

    Dean, Laura. “Hemolytic Disease of the Newborn.” Nih.gov, National Center for Biotechnology Information (US), 2005, www.ncbi.nlm.nih.gov/books/NBK2266/.

    *Dean, Laura. “The ABO Blood Group.” National Library of Medicine, National Center for Biotechnology Information (US), 2005, www.ncbi.nlm.nih.gov/books/NBK2267/.

    Downie, A W, et al. “Smallpox Frequency and Severity in Relation to A, B and O Blood Groups.” Bulletin of the World Health Organization, vol. 33, no. 5, 1965, p. 623, pmc.ncbi.nlm.nih.gov/articles/PMC2475872/.

    Gelabert, Pere, et al. “Malaria Was a Weak Selective Force in Ancient Europeans.” Scientific Reports, vol. 7, no. 1, 3 May 2017, https://doi.org/10.1038/s41598-017-01534-5.

    International Society of Blood Transfusion (ISBT). (2026). ABO Allele Nomenclature. Retrieved from https://blooddatabase.isbtweb.org/system/ABO.

    Kermarrec, Nathalie, et al. “Comparison of Allele O Sequences of the Human and Non-Human Primate ABO System.” Immunogenetics, vol. 49, no. 6, 5 May 1999, pp. 517–526, https://doi.org/10.1007/s002510050529.

    Kong, Augustine, et al. “Rate of de novo mutations and the importance of father’s age to disease risk.” Nature, vol. 488, no. 7412, 2012, pp. 471-475.

    Kwiatkowski, Dominic P. “How Malaria Has Affected the Human Genome and What Human Genetics Can Teach Us about Malaria.” The American Journal of Human Genetics, vol. 77, no. 2, Aug. 2005, pp. 171–192, https://doi.org/10.1086/432519.

    Lynch, M., et al. “Mutation accumulation and the extinction of small populations.” The American Naturalist, vol. 146, no. 4, 1995, pp. 489-518.

    Marian, Jakub. “Blood Type Distribution,” Jakubmarian.com, 2018.

    Mullaney, J. M., et al. “Small Insertions and Deletions (INDELs) in Human Genomes.” Human Molecular Genetics, vol. 19, no. R2, 21 Sept. 2010, pp. R131–R136, https://doi.org/10.1093/hmg/ddq400.

    Nachman, Michael W, and Susan L Crowell. “Estimate of the Mutation Rate per Nucleotide in Humans.” Genetics, vol. 156, no. 1, 1 Sept. 2000, pp. 297–304, https://doi.org/10.1093/genetics/156.1.297.

    O’Neil, Dennis. “Modern Human Variation: Distribution of Blood Types.” Kinsta.page, 2012, anthropology-tutorials-nggs7.kinsta.page/vary/vary_3.htm.

    Ségurel, Laure, et al. “The ABO Blood Group Is a Trans-Species Polymorphism in Primates.” Proceedings of the National Academy of Sciences, vol. 109, no. 45, 6 Nov. 2012, pp. 18493–18498, www.pnas.org/content/109/45/18493, https://doi.org/10.1073/pnas.1210603109.

    Wang, Jianbin, et al. “Genome-Wide Single-Cell Analysis of Recombination Activity and de Novo Mutation Rates in Human Sperm.” Cell, vol. 150, no. 2, 13 June 2012, pp. 402–412, https://doi.org/10.1016/j.cell.2012.06.030.Yamamoto, F., et al. “Molecular Genetic Basis of the Histo-Blood Group ABO System.” Nature, vol. 345, no. 6272, 17 May 1990, pp. 229–233, http://www.ncbi.nlm.nih.gov/pubmed/2333095, https://doi.org/10.1038/345229a0.

  • The Idealist Argument from Contingency

    The Idealist Argument from Contingency

    Introduction: Observing Ex Nihilo Creation

    As I have been promoting the Kalam cosmological argument, I’ve been thinking deeply about its particular criticisms. To be clear, most criticisms of Craig’s Kalam fail, however some are fascinating and get you thinking about the particulars such as what existence means and whether ex nihilo (out of nothing) is an ontologically distinct kind of creation which we don’t observe.

    On one hand, most proponents of the Kalam are perfectly willing to grant that we don’t observe ex nihilo creation and redirect the skeptic to the metaphysical entailments of creation (usually from the principle of sufficient reason), suggesting that the universe, and all things which have ontology in and of themselves, do need efficient causes. Yet, I really don’t think we need to cede ground here. As I’ve meditated on this, I’ve come to the conclusion that we do in fact observe ex nihilo creations—from our minds.

    What do I mean by this? Well, take any concept of a “thing”, let’s say a wooden chair (it’s the favorite of philosophers), and ask ourselves how it is that this thing exists in the “real” world. When we examine a chair carefully, we discover something remarkable: the chair as a unified object—as a chair—does not exist in the physical substrate at all. What exists physically are atoms arranged in a particular configuration. The “chairness” of this arrangement, the ontological unity that makes these atoms one thing rather than billions of separate things, is something imposed by mind. In this sense, we observe minds creating genuine ontological categories ex nihilo—not creating the matter itself, but creating the very thingness that makes a collection of particles into a unified object.

    This realization leads to a profound philosophical argument that I believe has been insufficiently explored in contemporary philosophy of religion.

    The Nature of Composite Objects

    We land on a few interesting features when we examine any purported “thing” in the material world. For one, a thing is instantiated in the world separate from its physical parts. This chair, for instance, may be made of wood, but many metals, plastics, and fabrics can be substituted and the identity of a thing within a category (or genus) is not changed. There is something higher than just mere components which brings the composition into a unified whole.

    But what is this “something higher”? The materialist wants to say it’s just the arrangement of particles. But this raises immediate problems. Consider: when exactly does a collection of wood atoms become a chair? When the carpenter has assembled 50% of the pieces? 75%? 90%? What if one leg is broken—is it still a chair, or merely chair-shaped atoms? What if the leg is cracked but still functional? The materialist has no principled answer to these questions because “chairness” is not a property that can be reduced to particle arrangements.

    The problem becomes even clearer when we consider boundaries. A chair has clear boundaries to us—we know where the chair ends and the floor begins. But at the atomic level, there are no such boundaries. Atoms are constantly exchanging electrons, being shed and replaced. Air molecules intermingle with the chair’s molecules at the surface. There is no physical demarcation that says “here the chair ends.” The boundaries we perceive (form) are imposed by our minds based on function and purpose.

    This leads to several different possible conclusions about where a “thing” must be sustained. We are asking where something really exists, ontologically speaking. To be precise, there are three exhaustive options: (1) the thing is sustained in a domain of itself (like Platonic Forms), (2) the thing is sustained in the material domain (by physics and chemistry alone), (3) the thing is sustained in the mental domain (by a mind). I offer the reader to consider alternate hypotheses and notice that these choices really do cover the gamut.

    The Trilemma of Ontology

    Let us examine each option in turn to see which can bear the weight of explanation.

    Option 1: Material Sustenance (Reductionist Materialism)

    For the materialist position, we run into the logical contradiction of unified-composite objects. The materialist must assume that composite objects, like a rock, have no inherent boundaries. Physical things are mere indifferentiable clusters of atoms. From here, the materialist has two options. They can either accept a form of object nihilism, where no composite objects actually exist, or they can turn to a nominalistic approach.

    In regards to nominalism, we must ask: what is the reason we would call a rock “rock” if separate from its ontology or it actually being a rock? If things, like a rock, exist in name only, then they do not really exist within distinct categories or kinds. This renders their definitions completely meaningless, because a good definition requires classification within the context of genus-species relationships. If things really exist as distinct objects, it is only because we have determined some aspect of their ontology over and above what reductionism or materialism can explain. So in reality, there is no sustainable nominalist approach for the materialist: one is either an object nihilist, or one must accept that real things are established some other way.

    It seems to me that something like a rock is a perfect example of what would be impossible to be established as ontologically distinct without a mind. Is a pebble a rock? Is a handful of sand many small pebbles? Why do we call a variant quantity of small rocks a singular category? Why do we delineate between singular grains of sand and groups of pebbles? Is it not an arbitrary size distinction relative to our observational abilities and purposes?

    For another example, consider why people groups such as Inuit tribes, who live in snowy environments, have many particular names for snow, whereas those tribes who live near the equator do not. It is because words are conventions within social groups to establish meaningful concepts. To someone who may see snow one day of the year, different textures and variations of snow are not meaningfully distinct. All composite objects that exist—including the very words that I am writing—are things minds have established as meaningful and bounded.

    Therefore, a rock is meaningfully different from a pebble and a group of pebbles from sand only insofar as our use or intent dictates. Our experience of snow presupposes our naming conventions of snow. If you learn a language with seven words for snow, but you have always lived in a desert, you will not suddenly understand snow differently—you need to experience snow differently first.

    But the materialist might object: “Even if our labels are arbitrary, the physical arrangements are real. When I sit in a chair, something physical holds me up.” This is true, but it misses the point. Yes, atoms arranged in a certain configuration will bear weight. But those atoms bearing weight is not the same as a chair existing. The chair, as a unified object with identity over time, with the capacity to be the same chair even if we replace parts, with clear boundaries—this is not present in the physical substrate. It is a mental construct imposed on that substrate.

    Consider the philosophical puzzle of the Ship of Theseus. If we replace every plank of a ship, one by one, is it the same ship? The puzzle has no answer in purely physical terms because the ship’s identity is not a physical property. Identity over time, unity, and boundaries are all features imposed by minds, not discovered in matter.

    If you accept Object Nihilism for composite objects and argue for a fundamental realist view where only quarks and leptons (or quantum fields) exist, then you face equally severe problems. What is your evidence that you exist ontologically? An entity which doesn’t exist as a unified object cannot consistently argue that some things do exist as unified objects. Moreover, what is your basis for assuming you know the “stuff” which is fundamental to reality? Even the quantum field is not necessarily the bottom line. Who can say what energy ultimately is? What’s to say that what’s fundamental isn’t also mind-contingent? That it isn’t mathematical in nature—which would itself require mental grounding?

    This view has made a distinction where everything composite is nominal except for something that has never been directly observed as a truly fundamental “thing.” How does one justify this distinction in the first place? It seems to me a contradiction in reasoning to deny mind-dependent categories for composite objects while affirming mind-independent categories for fundamental particles. Both require the same kind of ontological boundary-drawing that only minds can provide.

    Option 2: Self-Sustaining Forms (Platonism)

    From here, a skeptic might say, “Okay, the chair or rock isn’t purely material. But maybe it’s just a Platonic Form. It sustains itself in an abstract realm. Why do we need a Mind?”

    This is a more sophisticated response, but it ultimately fails for several reasons.

    First, abstract objects have no causal power. A Platonic Form of “chairness” cannot reach down into the physical world and organize atoms into a chair configuration. It cannot explain why this particular collection of atoms instantiates the form rather than some other collection. The relationship between abstract forms and concrete particulars remains deeply mysterious in Platonic metaphysics—so mysterious that even Plato himself struggled with it in dialogues like the Parmenides.

    Second, and more fundamentally, it is unintelligible to think of abstract objects like propositions, mathematical truths, or forms existing without a mind to think them. As Alvin Plantinga has argued, propositions are the contents of thoughts. They are the sort of thing that exists in minds. To say they exist “on their own” in some abstract realm is to commit a category error—it’s like saying colors exist independently of anything colored, or that motion exists independently of anything moving.

    Consider what a Platonic Form would have to be: a truth, a concept, a logical structure. But these are precisely the kinds of things that exist as thoughts. A thought cannot exist without a thinker any more than a dance can exist without a dancer. The Platonist wants to affirm that 2+2=4 exists eternally and necessarily, and I agree. But this truth exists as an eternal thought in an eternal mind, not as a free-floating abstraction.

    Third, many Platonic forms presuppose relationships, which themselves presuppose minds. Take the concept of justice. Justice involves right relations between persons. But “right relations” is an inherently normative concept that makes no sense without minds capable of recognizing and valuing those relations. Or consider mathematical sets. A set is defined by a rule of membership—a mental act of grouping things together according to a criterion. Sets don’t group themselves.

    Therefore, if the “Blueprint” of the universe is real—if there truly are eternal structures, categories, and forms that ground the intelligibility of reality—these cannot be free-floating abstract objects. They must be Divine Thoughts, eternally sustained in a Divine Mind.

    Option 3: Mental Sustenance (Idealism)

    This leaves us with the third option: composite objects exist insofar as they are sustained by minds. This may sound counterintuitive at first, but it’s the only option that avoids the contradictions of the previous two.

    When a carpenter builds a chair, he doesn’t merely arrange atoms—he imposes a conceptual unity on those atoms. He creates boundaries where there were none. He establishes identity conditions (this is one chair, not four separate legs plus a seat plus a back). He determines a function and purpose that gives meaning to the configuration. All of these acts are mental, not physical.

    But here’s the crucial question: once the carpenter stops thinking about the chair, does it cease to exist? In one sense, yes—the carpenter’s mind is no longer actively sustaining it. But in another sense, no—the chair continues to be recognized as a chair by other minds. As long as someone conceptualizes those atoms as a unified object called “chair,” it exists as such.

    This actually goes back to Bishop George Berkeley’s famous argument: “If a tree falls in the woods and no one is there to hear it, does it make a sound?” In a sense, if we stipulate that there is no wildlife and trees lack the ability to register sound frequencies, the fall really does not make a sound. This is because sound is a perception, a mental phenomenon. There are pressure waves in the air, certainly, but “sound” as we experience it requires a mind to interpret those waves.

    However, Berkeley went further than this, and so must we. Berkeley argued that material objects continue to exist when no human observes them because God’s mind perpetually perceives them. I want to make a similar but distinct claim: composite objects, categories, and the conceptual structure that makes reality intelligible all require perpetual mental sustenance. Not just observation, but active ontological grounding.

    An analogy may help: consider an author writing a novel. The characters in the novel have a kind of existence—they’re not nothing. But their existence is entirely dependent on the author’s creative act and the mind of any reader engaging with them. If every copy of the book were destroyed and everyone forgot the story, the characters would cease to exist in any meaningful sense. They have no “existential inertia” apart from minds sustaining them.

    I propose that composite objects in our world are similar. The atoms may have mind-independent existence (though even this is debatable), but the chairness—the unified object with boundaries, identity, and purpose—exists only in minds. And since these objects continue to exist even when finite human minds aren’t thinking about them, they must be sustained by an infinite, omnipresent Mind.

    The Formal Argument

    All this contemplation leads me to the first formulation of a new kind of contingency argument which I call the Argument from Ontological Sustenance (or Idealist Argument from Contingency):

    Premise 1: All composite objects require a mind to sustain their ontology.

    Premise 2: The universe is a composite object.

    Conclusion: Therefore, the universe requires a mind to sustain its ontology.

    This is a logically valid argument, meaning if the premises are true, the conclusion must be as well.

    The first premise has been defended at length above. The key insight is that composite objects—things made of parts organized into a unity—have no ontological status in the physical substrate alone. Their unity, boundaries, and identity exist only as mental constructs.

    The second premise should be relatively uncontroversial. The universe is composed of parts (galaxies, stars, planets, particles) organized into a whole. It has boundaries (even if those boundaries are the limits of spacetime itself). It has an identity that persists through time. All of these features require the same kind of mental grounding that chairs and rocks require.

    Therefore, the universe itself must be sustained in its existence as a unified, bounded entity by a mind. And since the universe contains all finite minds, this sustaining mind must be transcendent—beyond the universe, not part of it.

    Why Not Pantheism?

    An obvious objection arises: couldn’t the universe itself be the Mind that sustains all these categories? This would be a pantheistic solution—identifying God with the universe itself rather than positing a transcendent deity.

    This fails for several reasons:

    Step 1: A mind is a container for concepts. It is the sort of thing that has thoughts, holds ideas, and maintains logical relationships between propositions.

    Step 2: Necessary truths (logic, mathematics, metaphysics) exist outside our finite minds. We discover them; we don’t invent them. This implies a Greater Mind contains them.

    Step 3: Could this Greater Mind be the Universe itself?

    Refutation: No. A “Universe Mind” would be composed of parts (galaxies, energy fields, quantum states) and subject to entropy (time, change, decay). But anything composed of parts is contingent—dependent on those parts and their organization. Anything subject to entropy requires external sustenance or an explanation for why it continues to exist through change.

    Moreover, the universe is precisely the kind of composite object that needs mental grounding. To say the universe grounds its own categories is circular—it’s like saying a novel writes itself, or a dance choreographs itself.

    Conclusion: The Ultimate Sustainer cannot be the Universe. It must be Transcendent (distinct from creation) and Non-Contingent (self-existent, not dependent on anything external to itself).

    The Divine Attributes

    Once we establish that a Transcendent, Non-Contingent Mind sustains all reality, we can derive further attributes through the classical logic of Act and Potency (pure actuality).

    Premise: A Non-Contingent Mind has no external cause, and therefore no external limitations or deficiencies. It is “Pure Act”—fully realized, with no unrealized potential.

    Omnipotence

    To possess “some” power but not “all” power is to have a limitation—an unrealized potential to do more. But a Non-Contingent Being has no unrealized potentials by definition. Nothing external limits what it can do. Therefore, it possesses all power—omnipotence.

    Omniscience

    Ignorance is a lack, a privation of knowledge. A Fully Realized Mind has no lacks or privations. Moreover, if this Mind sustains all reality through its thoughts, it must know everything it sustains—otherwise, how could it sustain it? Therefore, it knows all things—omniscience.

    Omnibenevolence

    Evil, in the classical metaphysical tradition, is a privation—a lack of goodness or being. It is not a positive reality but an absence, like cold is the absence of heat or darkness the absence of light. Since this Mind is Fully Realized Being with no privations, it contains no evil. It is Pure Goodness—omnibenevolence.

    Eternity and Immutability

    Change implies potentiality—the ability to become something one is not yet. But a Non-Contingent Being has no potentiality. Therefore, it does not change. It exists eternally in a timeless present, not subject to temporal succession.

    Personhood

    This Mind thinks, knows, and creates categories. These are the activities of a person, not an impersonal force. Moreover, the categories it sustains include moral values, relational properties, and purposes—all of which presuppose personhood. Therefore, this Being is personal.

    The Christian Specificity

    We have now established the existence of a Transcendent, Omnipotent, Omniscient, Omnibenevolent, Eternal, Personal Mind that sustains all reality. This is recognizably the God of classical theism. But can we go further and identify this God with the specific God of Christianity?

    The Argument from Relational Necessity

    Premise 1: A God who is Personal, Truthful, and Loving is inherently Relational. Love seeks connection; truth seeks to be known; personhood seeks communion.

    Premise 2: To be fully known and to establish a perfect relationship with finite creatures, this Infinite God must bridge the ontological gap. He cannot remain purely transcendent and abstract.

    Consider: if God is perfectly loving, His love must be expressed, not merely potential. If God is truth, He must reveal Himself, not remain hidden. If God is personal, He must enter into relationship with persons He has created. But finite creatures cannot reach up to an infinite God—the ontological distance is too vast. Therefore, God must reach down to us.

    The Filter

    With this criterion, we can evaluate the world’s major religious traditions:

    Deism/Pantheism: These fail immediately because they offer no relationship. Deism presents a God who creates and withdraws. Pantheism identifies God with the universe, making genuine relationship impossible.

    Unitarian Monotheism (Islam/Judaism): These traditions affirm God’s transcendence and offer prophetic revelation—books and laws sent from on high. But God remains fundamentally separate. He sends messages but does not cross the boundary to unite with creation. The relationship is external, mediated through texts and commandments, never achieving full intimacy or union.

    Christianity: This succeeds as the only worldview where the Sustainer becomes the Sustained. In the doctrine of the Incarnation, God doesn’t merely send a message about Himself—He enters history as a human being. The Infinite becomes finite. The Creator becomes a creature. The Mind that sustains all reality subjects Himself to the very categories He created.

    This is not merely unique—it’s philosophically necessary. If God is to bridge the ontological gap between infinite and finite, between Creator and creature, He must do so by becoming both. The Incarnation is the only way for perfect relationship to be achieved.

    Verification Through Human Experience

    The Christian worldview also uniquely and truthfully describes the human condition. We experience ourselves as simultaneously possessing great dignity (made in God’s image, capable of reason and love) and great depravity (prone to selfishness, cruelty, and irrationality). We long for meaning, purpose, and redemption, yet find ourselves unable to achieve these on our own.

    Christianity explains this through the doctrine of the Fall and offers a solution through Redemption—not by our own efforts, but by God’s gracious action in Christ. This narrative aligns with both our philosophical conclusions about God’s nature and our existential experience of ourselves.

    Conclusion

    The Mind that sustains the rock, the chair, and every composite object in reality is the same Mind that entered the world as Jesus of Nazareth. From the seemingly simple question “What makes a chair a chair?” we have traced a path to the central truth of Christianity: God is not distant or abstract, but intimately involved in every aspect of reality, from the smallest pebble to the vast cosmos, from the categories that make thought possible to the incarnate life that makes redemption possible.

    This is the Argument from Ontological Sustenance. Like all philosophical arguments, it invites scrutiny, challenges, and further refinement. But I believe it opens a fruitful path for natural theology—one that begins not with cosmological speculation about the universe’s beginning, but with careful attention to the ontological structure of everyday objects and the categories that make them intelligible.

    Every time we recognize a chair as a chair, a rock as a rock, or the universe as a cosmos, we are implicitly acknowledging the work of the Divine Mind that makes such recognition possible.

  • Introduction To Created Heterozygosity

    Introduction To Created Heterozygosity

    Introduction

    Evolution by natural selection is a foundational theory in biology, observable in bacteria developing resistance, finch beak size changes, and populations adapting to environments. These microevolution examples are experimentally verified and widely accepted.

    A deeper question persists: Are the mechanisms of random mutation and natural selection sufficient to explain not only the modification of existing biological structures, but also their original creation? Specifically, can the processes observed in generating variation within species account for the origin of entirely novel protein folds, enzymatic functions, and the fundamental molecular machinery of life?

    This essay addresses this question by systematically evaluating the proposed mechanisms for evolutionary innovation, identifying their constraints, and highlighting what appears to be a fundamental limit: the origin of complex protein architecture.

    Part I: The Mechanisms of Modification

    Gene Duplication: Copy, Paste, Edit

    The most commonly cited mechanism for evolutionary innovation is gene duplication. The logic is straightforward: when a gene is accidentally copied during DNA replication, the organism now has two versions. One copy maintains the original function (keeping the organism alive), while the redundant copy is “free” to mutate without immediate lethal consequences.

    In theory, this freed copy can acquire new functions through random mutation—a process called neofunctionalization. Over time, what was once a single-function gene becomes a gene family with diverse, related functions.

    This mechanism is real and well-documented. For instance, in “trio” studies (father, mother, child), we regularly see de novo copy number variations (CNVs). Based on this, we can trace gene families back through evolutionary history and see convincing evidence of duplication events. However, gene duplication has important limitations:

    Dosage sensitivity: Cells operate as finely tuned chemical systems. Doubling the amount of a protein often disrupts this balance, creating harmful or even lethal effects. The cell isn’t simply tolerant of extra copies—duplication frequently imposes an immediate cost.

    Subfunctionalization: Rather than one copy evolving a bold new function, duplicate genes more commonly undergo subfunctionalization—they degrade slightly and split the original function between them. What was once done by one gene is now accomplished by two, each doing part of the job. This adds genomic complexity but doesn’t create novel capabilities.

    The prerequisite problem: Most fundamentally, gene duplication requires a functional gene to already exist. It’s a “copy-paste-edit” mechanism. It can explain variations on a theme—how you get a family of related enzymes—but it cannot explain the origin of the first member of that family.

    Evo-Devo: Rewiring the Switches

    Evolutionary developmental biology (evo-devo) revealed something crucial: many major morphological changes don’t come from inventing new genes, but from rewiring when and where existing genes are expressed. Mutations in regulatory elements—the “switches” that control genes—can produce dramatic changes in body plans.

    A classic example: the difference between a snake and a lizard isn’t that snakes invented fundamentally new genes. Rather, mutations in regulatory regions altered the expression patterns of Hox genes (master developmental regulators), eliminating limb development while extending the body axis.

    This mechanism helps explain how evolution can produce dramatic morphological diversity without constantly inventing new molecular parts. But it has clear boundaries:

    The circuitry prerequisite: Regulatory evolution presupposes the existence of a sophisticated, modular regulatory network—the Hox genes themselves, enhancer elements, transcription factor binding sites. This network is enormously complex. Evo-devo explains how to rearrange the blueprint, but not where the drafting tools came from.

    Modification, not creation: You can turn genes on in new places, at new times, in new combinations. You can lose structures (snakes losing legs). But you cannot regulatory-mutate your way to a structure whose genetic basis doesn’t already exist. You’re rearranging existing parts, not forging new ones.

    Exaptation: Shifting Purposes

    Exaptation describes how traits evolved for one function can be co-opted for another. Feathers, possibly first used for insulation or display, were later recruited for flight. Swim bladders in fish became lungs in land vertebrates.

    This is an important concept for understanding evolutionary pathways—it explains how structures can be preserved and refined even when their ultimate function hasn’t yet emerged. But exaptation is a description of changing selective pressures, not a mechanism of generation. It tells us how a trait might survive intermediate stages, but not how the physical structure arose in the first place.

    Part II: The Hard Problem—De Novo Origins

    The mechanisms above all share a common feature: they are remixing engines. They shuffle, duplicate, rewire, and repurpose existing genetic material. This works brilliantly for generating diversity and adaptation. But it raises an unavoidable question: Where did the original material come from?

    This is where the inquiry becomes more challenging.

    De Novo Gene Birth: From Junk to Function?

    To tackle this question, we examine the hypothesis that new genes can arise from previously non-coding “junk” DNA—an idea central to de novo gene birth.

    One hypothesis is that non-coding DNA—sometimes called “junk DNA”—occasionally gets transcribed randomly. If a random mutation creates an open reading frame (a start codon, some codons, a stop codon), you might produce a random peptide. Perhaps, very rarely, this random peptide does something useful, and natural selection preserves and refines it.

    This mechanism has some support. We do see “orphan genes” in various lineages—genes with no clear homologs in related species, suggesting recent origin. When we examine these orphan genes, many are indeed simple: short, intrinsically disordered proteins with low expression levels.

    But here’s where we hit the toxicity filter—a fundamental physical constraint.

    The Toxicity Filter

    Protein synthesis is energetically expensive, consuming up to 75% of a growing cell’s energy budget. When a cell produces a protein, it’s making an investment. If that protein immediately misfolds and gets degraded by the proteasome, the cell has just run a futile cycle—burning energy to produce garbage.

    In a competitive environment (which is where natural selection operates), a cell wasting energy on useless proteins will be outcompeted by leaner, more efficient cells. This creates strong selection pressure against expressing random, non-functional sequences.

    It gets worse. Cells have a limited capacity for handling misfolded proteins. Chaperone proteins help fold new proteins correctly, and the proteasome system degrades those that fail. But these are finite resources. If a cell produces too many difficult-to-fold or misfolded proteins, it triggers the Unfolded Protein Response (UPR).

    The UPR is an emergency protocol. Initially, the cell tries to fix the problem—producing more chaperones, slowing translation. But if the stress is too severe, the UPR switches from “repair” to “abort”: the cell undergoes apoptosis (programmed cell death) to protect the organism.

    This creates a severe constraint: natural selection doesn’t just fail to reward complex random sequences—it actively punishes them. The toxicity filter eliminates complex precursors before they have a chance to be refined.

    The Result

    The “reservoir” of potentially viable de novo genes is therefore biased heavily toward simple, disordered, low-expression peptides. These can slip through because they don’t trigger the toxicity filters. They don’t misfold (because they don’t fold), and at low expression, they don’t drain significant resources.

    This explains the orphan genes we observe: simple, disordered, regulatory, or binding proteins. But it fails to explain the origin of complex, enzymatic machinery—proteins that require specific three-dimensional structures to catalyze reactions.

    Part III: The Valley of Death

    To understand why complex enzymatic proteins are so difficult to generate de novo, we need to examine what makes them different from simple disordered proteins.

    Two Types of Proteins

    Intrinsically Disordered Proteins (IDPs) are floppy, flexible chains. They’re rich in polar and charged amino acids (hydrophilic—“water-loving”). These amino acids are happy interacting with water, so the protein doesn’t collapse into a compact structure. IDPs are excellent for binding to other molecules (they can wrap around things) and for regulatory functions (they’re flexible switches). They’re also relatively safe—they don’t aggregate easily.

    Folded Proteins, by contrast, have a hydrophobic core. Water-hating amino acids cluster in the center of the protein, away from the surrounding water. This hydrophobic collapse creates a stable, specific three-dimensional structure. Folded proteins can do things IDPs cannot: precise catalysis requires holding a substrate molecule in exactly the right geometry, which requires a rigid, well-defined active site pocket.

    The problem is that the “recipe” for these two types of proteins is fundamentally different. You can’t gradually transition from one to the other without passing through a dangerous intermediate state.

    The Sticky Globule Problem

    Imagine trying to evolve from a safe IDP to a functional folded enzyme:

    1. Start: A disordered protein—polar amino acids, floppy, safe.
    2. Intermediate: As you mutate polar residues to hydrophobic ones, you don’t immediately get a nice folded structure. Instead, you get a partially hydrophobic chain—the worst of both worlds. These “sticky globules” are aggregation-prone. They clump together like glue, forming toxic aggregates.
    3. End: A properly folded protein with a hydrophobic core and stable structure

    The middle step—the sticky globule phase—is precisely what the toxicity filter eliminates most aggressively. These partially hydrophobic intermediates are the most dangerous type of protein for a cell.

    This creates what we might call the Valley of Death: a region of sequence space that is selected against so strongly that random mutation cannot cross it. To get from a safe disordered protein to a functional enzyme, you’d need to traverse this valley—but natural selection is actively pushing you back.

    Catalysis Requires Geometry

    There’s a second constraint. Catalysis—the acceleration of chemical reactions—almost always requires a precise three-dimensional pocket (an active site) that can:

    • Position the substrate molecule correctly.
    • Stabilize the transition state.
    • Shield the reaction from water (in many cases)

    A floppy disordered protein is excellent for binding (it can wrap around things), but terrible for catalysis. It lacks the rigid geometry needed to precisely orient molecules and stabilize reaction intermediates.

    This means the “functional gradient” isn’t smooth. You can evolve binding functions with IDPs. You can evolve regulatory functions. But to evolve enzymatic function, you need to cross the valley—and the valley actively resists crossing.

    Part IV: The Escape Route—And Its Implications

    There is one clear escape route from the Valley of Death: don’t cross it at all.

    Divergence from Existing Folds

    If you already have a stable folded protein—one with a hydrophobic core and a defined structure—you can modify it safely:

    1. Duplicate it: Now you have a redundant copy.
    2. Keep the core: The hydrophobic core (the “dangerous” part) stays conserved. This maintains structural stability.
    3. Mutate the surface: The active site is usually on flexible loops outside the core. Mutate these loops to change substrate specificity, reaction type, or regulation.

    This mechanism is well-documented. It’s how modern enzyme families diversify. You get proteins that are functionally very different (digesting different substrates, catalyzing different reactions) but structurally similar—variations on the same fold.

    Critically, you never cross the Valley of Death because you never dismantle the scaffold. You’re modifying an existing, stable structure, not building one from scratch.

    The Primordial Set

    This escape route, however, comes with a profound implication: it presupposes the fold already exists.

    If modern enzymatic diversity arises primarily through divergence from existing folds rather than de novo generation of new folds, where did those original folds come from?

    The empirical data suggest a striking answer: they arose very early, and there hasn’t been much architectural innovation since.

    When we examine protein structures across all domains of life, we don’t see a continuous spectrum of novel shapes appearing over evolutionary time. Instead, we see roughly 1,000-10,000 basic structural scaffolds (fold families) that appear again and again. A bacterial enzyme and a human enzyme performing completely different functions often share the same underlying fold—the same basic architectural plan.

    Comparative genomics pushes this pattern even further back. The vast majority of these fold families appear to have been present in LUCA—the Last Universal Common Ancestor—over 3.5 billion years ago.

    The implication is stark: evolution seems to have experienced a “burst” of architectural invention right at the beginning, and has spent the subsequent 3+ billion years primarily as a remixer and optimizer, not an architect of fundamentally new structures.

    Part V: The Honest Reckoning

    We can now reassess the original question: Are the mechanisms of mutation and natural selection sufficient to explain not just the modification of life, but its origination?

    What the Mechanisms Can Do

    The neo-Darwinian synthesis is extraordinarily powerful for explaining:

    • Optimization: Taking an existing trait and refining it
    • Diversification: Creating variations on existing themes
    • Adaptation: Adjusting populations to new environments
    • Loss: Eliminating unnecessary structures
    • Regulatory rewiring: Changing when and where genes are expressed

    These mechanisms are observed, experimentally verified, and sufficient to explain the vast majority of biological diversity we see around us.

    What the Mechanisms Struggle With

    The same mechanisms face severe constraints when attempting to explain:

    • The origin of novel protein folds: The Valley of Death makes de novo generation of complex, folded, enzymatic proteins implausible under cellular conditions.
    • The origin of the primordial set: The fundamental protein architectures that all modern life relies on
    • The origin of the cellular machinery: DNA replication, transcription, translation, and error correction systems that evolution requires to function

    A New Theory

    The constraints we’ve examined—the toxicity filter, the Valley of Death, the thermodynamics of protein folding—are not “research gaps” that might be closed with more data. They are physical constraints rooted in chemistry and bioenergetics.

    Modern evolutionary mechanisms are demonstrably excellent at working with existing complexity. They can shuffle it, optimize it, repurpose it, and elaborate on it in extraordinary ways. The diversity of life testifies to its power.

    But when we trace the mechanisms back to their foundation—when we ask how the original protein folds arose, how the first enzymatic machinery came to be—we encounter a genuine boundary.

    The thermodynamics that make de novo fold generation implausible today presumably existed 3.5 billion years ago as well. Perhaps early Earth conditions were radically different in ways that bypassed these constraints—different chemistry, mineral catalysts, an RNA world with different rules. Perhaps there are mechanisms we haven’t yet discovered or understood.

    But based on what we currently understand about the mechanisms of evolution and the physics of protein folding, the honest answer to “how did those original folds arise?” is:

    They didn’t.

    We need a new explanation that can account for the data. We have excellent, mechanistic explanations for how life diversifies and adapts. We have a clear understanding of the constraints that limit those mechanisms. And we have an unsolved problem at the foundation.

    The question remains open: not as a gap in data, but as a gap in mechanism. So what mechanism can account for genetic diversity?

    Part VI: A More Parsimonious Model

    For over a century, the primary explanation for the vast diversity of life on Earth has been the slow accumulation of mutations over millions of years, filtered by natural selection. However, there is another account of the origins of life that is often left unacknowledged and dismissed as pseudoscience. The concept is simple. We see information in the form of DNA, which is, by nature, a linguistic code. Codes require minds in our repeated and uniform experience. If our experience truly tells us that evolutionary mechanisms cannot account for information systems, as we’ve discovered through this inquiry, then it stands to reason that a design solution cannot rightly be said to be “off the table.

    However, there are many forms of design, so which one fits the data?

    The answer lies in a powerful, testable model known as Created Heterozygosity and Natural Processes (CHNP). This model suggests that a designer created organisms not as genetically uniform clones, but with pre-existing genetic diversity “front-loaded” into their genomes.

    Here is why Created Heterozygosity makes scientific sense.

    A common objection to any form of young-age design model is that two people cannot produce the genetic variation seen in seven billion humans today. Critics argue that we would be clones. However, this objection assumes Adam and Eve were genetically homozygous (having two identical DNA copies).

    If Adam and Eve were created with heterozygosity—meaning their two sets of chromosomes contained different versions of genes (alleles)—they could possess a massive amount of potential variation.

    The Power of Recombination

    We observe in biology that parents pass on traits through recombination and gene conversion. These processes shuffle the DNA “deck” every generation. Even if Adam and Eve had only two sets of chromosomes each, the number of possible combinations they could produce is mind-boggling.

    If you define an allele by specific DNA positions rather than whole genes, two individuals can carry four unique sets of genomic information. Calculations show that this is sufficient to explain the vast majority of common genetic variants found in humans today without needing millions of years of mutation. In fact, most allelic diversity can be explained by only two “major” alleles.

    In short, the problem isn’t that two people can’t produce diversity; it’s that critics assume the starting pair had no diversity to begin with.

    Part VI: A Dilemma, a Ratchet, and Other Problems

    Before we go further in-depth in our explanation of CHNP, we must realise the scope of the problems with evolution. It is not just that the mechanisms are insufficient for creating novelty, that would be one thing. But we see there are insurmountable “gaps” everywhere you turn in the modern synthesis.

    The “Waiting Time” Problem

    The evolutionary model relies on random mutations to generate new genetic information. However, recent numerical simulations reveal a profound waiting time problem. Beneficial mutations are incredibly rare, and waiting for specific strings of nucleotides (genetic letters) to arise and be fixed in a population takes far too long.

    For example, establishing a specific string of just two new nucleotides in a hominin population would take an average of 84 million years. A string of five nucleotides would take 2 billion years. There simply isn’t enough time in the evolutionary timeline (e.g., 6 million years from a chimp-like ancestor to humans) to generate the necessary genetic information from scratch.

    Haldane’s Dilemma

    In 1957, the evolutionary geneticist J.B.S. Haldane calculated that natural selection is not free; it has a biological “cost”. For any specific genetic variant (mutation) to increase in a population, the individuals without that trait must effectively be removed from the gene pool—either by death or by failing to reproduce.

    This creates a dilemma for the evolutionary narrative:

    A population only has a limited surplus of offspring available to be “spent” on selection. If a species needs to select for too many traits at once, or eliminate too many mutations, the required death rate would exceed the reproductive rate, driving the species to extinction.

    Haldane calculated that for a species with a low reproductive rate like humans, the cost of fixing just one beneficial mutation would require roughly 300 generations. This speed is far too slow to explain the complexity of the human genome, even within the evolutionary timescale of millions of years.

    Rarity of Function

    From the perspective of Dr. Douglas Axe, a molecular biologist and Director of the Biologic Institute, there is a mathematically fatal challenge to the Darwinian narrative. His research focuses on the “rarity of function”—specifically, how difficult it is to find a functional protein sequence among all possible combinations of amino acids.

    Proteins are chains of amino acids that must fold into precise three-dimensional shapes to function. There are 20 different amino acids available for each position in the chain. If you have a modest protein that is 150 amino acids long, the number of possible arrangements is 20^150. This number is roughly 10^195. To put this in perspective, there are only about 10^80 atoms in the entire observable universe.

    The “search space” of possible combinations is unimaginably vast. Evolutionary theory assumes that “functional” sequences (those that fold and perform a task) are common enough that random mutations can stumble upon them. Dr. Axe tested this assumption experimentally using a 150-amino-acid domain of the beta-lactamase enzyme. In his seminal 2004 paper published in the Journal of Molecular Biology, Axe determined the ratio of functional sequences to non-functional ones.

    He calculated that the probability of a random sequence of 150 amino acids forming a stable, functional fold is approximately 1 in 10^77. This rarity is catastrophic for evolution. To find just one functional protein fold by chance would be like a blindfolded man trying to find a single marked atom in the entire Milky Way galaxy. Because functional proteins are so isolated in sequence space, natural selection cannot help “guide” the process.

    Natural selection only works after a function exists. It cannot select a protein that doesn’t work yet. Axe describes functional proteins as tiny, isolated islands in a vast sea of gibberish. This is precisely the Valley of Death we discussed earlier. You cannot “gradually” evolve from one island to another because the space between them is lethal (non-functional). Even if the entire Earth were covered in bacteria dividing rapidly for 4.5 billion years, the total number of mutational trials would be roughly 10^40. This is nowhere near the 10^77 trials needed to statistically guarantee finding a single new protein fold.

    Muller’s Ratchet

    While Haldane highlighted the cost and Axe showed the scale, Muller showed the trajectory. Muller’s Ratchet describes the mechanism of irreversible decline. The genome is not a pool of independent genes; it is organized into “linkage blocks”—large chunks of DNA that are inherited together.

    Because beneficial mutations (if they occur) are physically linked to deleterious mutations on the same chromosome segment, natural selection cannot separate them. As deleterious mutations accumulate within these linkage blocks, the overall genetic quality of the block declines. Like a ratchet that only turns one way, the damage locks in. The “best” class of genomes in the population eventually carries more mutations than the “best” class of the previous generation. Over time, every linkage block in the human genome accumulates deleterious mutations faster than selection can remove them. There is no mechanism to reverse this damage, leading to a continuous, downward slide in genetic information.

    Genetic Entropy

    According to Dr. Sanford, these factors together create a lethal dilemma for the standard evolutionary model. The combination of high mutation rates, vast fitness landscapes, the high cost of selection, and physical linkage ensures that the human genome is rusting out like an old car, losing information with every generation.

    If humanity had been accumulating mutations for millions of years, our genome would have already reached “error catastrophe,” and we would be extinct. Alexey Kondrashov described this phenomenon in his paper, “Why Have We Not Died 100 Times Over?” The fact that we are still here suggests we have only been mutating for thousands, not millions, of years.

    The vast majority of mutations are harmful or “nearly neutral” (slightly harmful but invisible to natural selection). These mutations accumulate every generation. Human mutation rates indicate we are accumulating about 100 new mutations per person per generation. If humanity were hundreds of thousands of years old, we would have gone extinct from this genetic load.

    Created Heterozygosity aligns with this reality. It posits a perfect, highly diverse starting point that is slowly losing information over time, rather than a simple starting point struggling to build information against the tide of entropy. The observed degeneration is also consistent with the Biblical account of a perfect Creation that was subjected to corruption and decay following the Fall.

    Rapid Speciation

    Proponents of CHNP do not believe in the “fixity of species.” Instead, they observe that species change and diversify over time—often rapidly. This is called “cis-evolution” (diversification within a kind) rather than “trans-evolution” (changing from one kind to another).

    Speciation often occurs when a sub-population becomes isolated and loses some of its initial genetic diversity, shifting from a heterozygous state to a more homozygous state. This reveals specific traits (phenotypes) that were previously hidden (recessive). These changes will inevitably make two populations reproductively isolated or incompatible over several generations. This particular form of speciation is sometimes called Mendelian speciation.

    Real-world examples of this can easily be found. We see this in the rapid diversification of cichlid fish in African lakes, which arose from “ancient common variations” rather than new mutations. We also see it in Darwin’s finches, where hybridization and isolation lead to rapid changes in beak size and shape. In fact, this phenomenon is so prevalent that it has its own name in the literature—contemporary evolution.

    Darwin himself noted that domestic breeds (like dogs or pigeons) show more diversity than wild species. If humans can produce hundreds of dog breeds in a few thousand years by isolating traits, natural processes acting on created diversity could easily produce the wild species we see (like zebras, horses, and donkeys) from a single created kind in a similar timeframe.

    Molecular Clocks

    Finally, when we look at Mitochondrial DNA (mtDNA)—which is passed down only from mothers—we find a “clock” that fits the biblical timeline perfectly.

    The number of mtDNA differences between modern humans fits a timescale of about 6,000 years, not hundreds of thousands. While mtDNA clocks suggest a recent mutation accumulation, nuclear DNA differences are too numerous to be explained by mutation alone in 6,000 years. This confirms that the nuclear diversity must be frontloaded (original variety), while the mtDNA diversity represents mutational history.

    Conclusion

    The Created Heterozygosity model explains the origin of species by recognizing that God engineered life with the capacity to adapt, diversify, and fill the earth. It accounts for the massive genetic variation we see today without ignoring the mathematical impossibility of evolving that information from scratch. Rather than being a reaction against science, this model embraces modern genetic data—from the limits of natural selection to the reality of genetic entropy—to provide a robust history of life.

    Part VII: Created Heterozygosity & Natural Processes

    The evidence for Created Heterozygosity, specifically within the Created Heterozygosity & Natural Processes (CHNP) model, makes several important predictions that distinguish it from the standard Darwinian explanations.

    Prediction 1: “Major” Allelic Architecture

    If the created heterozygosity is correct, each gene locus of the human line should feature no more than four predominant alleles encoding functional, distinct proteins. This is a prediction based on Adam and Eve having a total of four genome copies altogether. This prediction can be refined, however, to be even more particular.

    Based on an analysis of the ABO gene within the Created Heterozygosity and Natural Processes (CHNP) model, the evidence suggests there were only two major alleles in the original created pair (Adam and Eve), rather than the theoretical maximum of four, for the following reasons:

    1. Only A and B are Functionally Distinct “Major” Alleles

    While a single pair of humans could theoretically carry up to four distinct alleles (two per person), the molecular data for the ABO locus reveals only two distinct, functional genetic architectures: A and B. The A and B alleles code for functional glycosyltransferase enzymes. They differ from each other by only seven nucleotides, four of which result in amino acid changes that alter the enzyme’s specificity. In an analysis of 19 key human functional loci, ABO is identified as having “dual majors.” These are the foundational, optimized alleles that are highly conserved and predate human diversification. Because A and B represent the only two functional “primordial” archetypes, the CHNP model posits that the original ancestors possessed the optimal A/B heterozygous genotype.

    2. The ‘O’ Allele is a Broken ‘A.’

    The reason there are not three (or four) original alleles (e.g., A, B, and O) is that the O allele is not a distinct, original design. It is a degraded version of the A allele.

    The most common O allele (O01) is identical to the A allele except for a single guanine deletion at position 261. This deletion causes a frameshift mutation, resulting in a truncated, non-functional enzyme. Because the O allele is simply a broken A allele, it represents a loss of information (genetic entropy) rather than originally created diversity. The CHNP model predicts that initial kinds were highly functional and optimized, containing no non-functional or suboptimal gene variants. Therefore, the non-functional O allele would not have been present in the created pair but arose later through mutation.

    3. AB is Optimal For Both Parents

    A critical medical argument for the AB genotype in both parents (and therefore 2 Major created alleles) concerns the immune system and pregnancy. The CHNP model suggests that an optimized creation would minimize physiological incompatibility between the first mother and her offspring.

    In the ABO system, individuals naturally produce antibodies against the antigens they lack. A person with Type ‘A’ blood produces anti-B antibodies; a person with Type ‘B’ produces anti-A antibodies; and a person with Type O produces both.

    Individuals with Type AB blood produce neither anti-A nor anti-B antibodies because they possess both antigens on their own cells.

    If the original mother (Eve) were Type A, she would carry anti-B antibodies, which could potentially attack a Type B or AB fetus (Hemolytic Disease of the Newborn). However, if she were Type AB, her immune system would tolerate fetuses of any blood type (A, B, or AB) because she lacks the antibodies that would attack them.

    If there were more than two original antigens, these problems would be inevitable. The only solution is for both parents to share the same two antigens.

    4. Disclaimer about scope

    This, along with many other examples within the gene catalogue, suggests most, if not all, original gene loci were bi-allelic for homozygosity. This is not to say all were, as we do not have definitive proof of that, and there are several, e.g., immuno-response genes, loci which could theoretically have more than two Majors. However, it is highly likely that all genetic diversity can be explained by bi-genome, and not quad-genome, diversity. Greater modern diversity, if present, can consistently be partitioned into two functional clades, with subsidiary alleles emerging via SNPs, InDels, or recombinations over short timescales.

    Prediction 2: Cross-Species Conservation

    Having similar genes is essential in a created world in order for ecosystems to exist; it shouldn’t be surprising that we share DNA with other organisms. From that premise, it follows that some organisms will be more or less similar, and those can be categorized. Due to the laws of physics and chemistry, there are inherent design constraints on forms of biota. Due to this, it is expected that there will be functional genes that are shared throughout life where they are applicable. For instance, we share homeobox genes with much of terrestrial life, even down to snakes, mice, flies, and worms. These genes are similar because they have similar functions. This is precisely what we would predict from a design hypothesis.

    Both models (CHNP and EES) predict that there will be some shared functional operations throughout all life. Although this prediction does lean more in favor of a design hypothesis, it is roughly agnostic evidence. However, what is a differentiating prediction is that “major” alleles will persist across genera, reflecting shared functional design principles, whereas non-functional variants will be species-specific. This prediction is due to the two models ’ different understandings of the power of evolutionary processes to explain diversity.

    This prediction can be tested (along with the first) by examining allelic diversity (particularly in sequence alignment) across related and non-related populations. For instance, take the ABO blood type gene again. The genetic data confirm that functional “major” alleles are conserved across species boundaries, while non-functional variants are species-specific and recent.

    1. Major Alleles (A and B): Shared Functional Design

    Both models acknowledge that the functional A and B alleles are shared between humans and other primates (and even some distinct mammals). However, the interpretation differs, and the CHNP model posits this as evidence of major allelic architecture—original, front-loaded functional templates.

    The functional A and B alleles code for specific glycosyltransferase enzymes. Sequence analysis shows that humans, chimpanzees, and bonobos share the exact same genetic basis for these polymorphisms. This fits the prediction that “major” alleles represent the optimized, original design. Because these alleles are functional, they are conserved across genera (trans-species), reflecting a common design blueprint rather than convergent evolution or deep-time descent.

    Standard evolution attributes this to “trans-species polymorphism,” arguing that these alleles have been maintained by “balancing selection” for 20 million years, predating the divergence of humans and apes.

    2. Non-Functional Alleles (Type O): The Differentiating Test

    The crucial test arises when examining the non-functional ‘O’ allele. Because the ‘O’ allele confers a survival advantage against severe malaria, the standard evolutionary model must do one of the following: 1) explain why it is not the case that A and B, the ‘O’ alleles are not all three ancient and shared across lineages (trans-species inheritance), or provide an example of a shared ‘O’ allele across a kind-boundary. The reason why this prediction must follow is that the ‘O’ allele, being the null version, by evolutionary definition must have existed prior to either ‘A’ or ‘B’. What’s more, ‘A’ and ‘B’ alleles can easily break and the ‘O’ is not significant enough to be selected out of a given population.

    In humans, the most common ‘O’ allele (O01) results from a specific single nucleotide deletion (a guanine deletion at position 261), causing a frameshift that breaks the enzyme. However, sequence analysis of chimpanzees and other primates reveals that their ‘O’ alleles result from different, independent mutations.

    Human and non-human primate ‘O’ alleles are species-specific and result from independent silencing mutations. The mutation that makes a chimp Type ‘O’ is not the same mutation that makes a human Type ‘O’.

    This supports the CHNP prediction that non-functional variants arise after the functional variants from recent genetic entropy (decay) rather than ancient ancestry. The ‘O’ allele is not a third “created” allele; it is a broken ‘A’ allele that occurred independently in humans and chimps after they were distinct populations. It has become fixated in populations, such as those native to the Americas, due to the beneficial nature of the gene break.

    This brings us, also, back to the evolutionary problems we mentioned. Even if these four or more beneficial mutations could occur to create one ‘A’ or ‘B’ allele, which we discussed as being incredibly unlikely, either gene would break likely at a faster rate (due to Muller’s Ratchet) than could account for the fixity of A and B in primates and other mammals.

    3. Timeline and Entropy

    The mutational pathways for the human ‘O’ allele fit a timeline of <10,000 years, appearing after the initial “major” alleles were established. This aligns with the CHNP view that variants arise via minimal genetic changes (SNPs, Indels) within the last 6,000–10,000 years.

    The emergence of the ‘O’ allele is an example of cis-evolution (diversification within a kind via information loss). It involves breaking a functional gene to gain a temporary survival advantage (malaria resistance), which is distinct from the creation of new biological information.

    4. Broader Loci Analysis

    This pattern is not unique to ABO. An analysis of 19 key human functional loci (including genes for immunity, metabolism, and pigmentation) confirms the “Major Allele” prediction:

    Out of the 19 loci, 16 exhibit a single (or dual, like ABO) major functional allele that is highly conserved across species. Meaning that the functional versions of the genes are shared with other primates, mammals, vertebrates, or even eukaryotes. In contrast, non-functional or pathogenic variants (such as the CCR5-Δ32 deletion or CFTR mutations) are predominantly human-specific and arose recently (often <10,000 years ago). And when similar non-functional traits appear in different species (e.g., MC1R-loss, or ‘O’ blood group), they are due to convergent, independent mutations, not shared ancestry.

    To illustrate this point, below is a graph from the paper testing the CHNP model in 19 functional genes. Table 1 summarizes key metrics for each locus. Across the dataset, 84% (16/19) exhibit a single major functional allele conserved >90% across mammals/primates, with variants emerging <50,000 years ago (kya). ABO and HLA-DRB1 align with dual ancient clades; SLC6A4 shows neutral biallelic drift. Non-functional variants (e.g., nulls, deficiencies) are human-specific in 89% of cases, often via single SNPs/InDels.

    LocusMajor Allele(s)Functional Groups (Ancient?)Cross-Species ConservationVariant Derivation (Changes/Time)Model Fit (1/2/3)
    HLA-DRB1Multiple lineages (e.g., *03, *04)2+ ancient clades (pre-Homo-Pan)High in primates (trans-species)Recombinations/SNPs; post-speciation (~100 kya)Strong (clades); Partial (multi); Strong
    ABOA/B (O derived)2 ancient (A/B trans-species)High in primatesInactivation (1 nt del.); <20 kyaStrong; Strong; Strong
    LCTAncestral non-persistent (C/C)1 majorHigh across mammalsSNPs (e.g., -13910T); ~10 kyaStrong; Strong; Strong
    CFTRWild-type (non-ΔF508)1 majorHigh across vertebrates3 nt del. (ΔF508); ~50 kyaStrong; Strong; Strong
    G6PDWild-type (A+)1 majorHigh (>95% identity)SNPs at conserved sites; <10 kyaStrong; Strong; Strong
    APOEε4 (ancestral)1 major (ε3/2 derived)High across mammalsSNPs (Arg158Cys); <200 kyaStrong; Strong; Partial
    CYP2D6*1 (wild-type)1 majorModerate in primatesDeletions/duplications; recentStrong; Partial; Strong
    FUT2Functional secretor1 majorHigh in vertebratesTruncating SNPs; ancient nulls (~100 kya)Strong; Strong; Partial
    HBBWild-type (HbA)1 majorHigh across vertebratesSNPs (e.g., sickle Glu6Val); <10 kyaStrong; Strong; Strong
    CCR5Wild-type1 majorHigh in primates32-bp del.; ~700 yaStrong; Strong; Strong
    SLC24A5Ancestral Ala111 (dark skin)1 majorHigh across vertebratesThr111 SNP; ~20–30 kyaStrong; Strong; Strong
    MC1RWild-type (eumelanin)1 majorHigh across mammalsLoss-of-function SNPs; convergent in someStrong; Partial (conv.); Strong
    ALDH2Glu504 (active)1 majorHigh across eukaryotesLys504 SNP; ~2–5 kyaStrong; Strong; Strong
    HERC2/OCA2Ancestral (brown eyes)1 majorHigh across mammalsrs12913832 SNP; ~10 kyaStrong; Strong; Strong
    SERPINA1M allele (wild-type)1 majorHigh in mammals (family expansion)SNPs (e.g., PiZ Glu342Lys); recentStrong; Strong; Strong
    BRCA1Wild-type1 majorHigh in primatesFrameshifts/nonsense; <50 kyaStrong; Strong; Strong
    SLC6A4Long/short 5-HTTLPR2 neutrally evolvedHigh across animalsInDel (VNTR); ancient (~500 kya)Partial; Strong; Partial
    PCSK9Wild-type1 majorHigh in primates (lost in some mammals)SNPs (e.g., Arg469Trp); recentStrong; Strong (conv. loss); Strong
    EDARVal370 (ancestral)1 majorHigh across vertebratesAla370 SNP; ~30 kyaStrong; Strong; Strong

    Table 1: Evolutionary Profiles of Analyzed Loci. Model Fit: Tenet 1 (major architecture), 2 (conservation), 3 (derivation). “Partial” indicates minor deviations (e.g., multi-clades or potentially >10 kya).

    This is devastating for modern synthesis. If the pattern that arises is one of shared functions and not shared mistakes, the theory is dead on arrival.

    Prediction 3: Derivation Dynamics

    Another important prediction to consider is due to the timeline for creating heterozygosity. If life were designed young (an entailment for CHNP), variant alleles must have arisen from “majors” through minimal modifications, feasible within roughly 6 to 10 thousand years.

    To look at the ABO blood group once more, we see the total feasibility of this prediction. The ABO blood group, again, offers a “cornerstone” example, demonstrating how complex diversity collapses into simple, recent mutational events.

    1. The ABO Case Study: Minimal Modification

    The CHNP model identifies the A and B alleles as the original, front-loaded “major” alleles created in the founding pair. The diversity we see today (such as the various O alleles and A subtypes) supports the prediction of minimal, recent modification:

    As we’ve discussed, the most common O allele (O01) is not a novel invention; it is a broken ‘A’ allele. It differs from the ‘A’ allele by a single guanine deletion at position 261. This minute change causes a frameshift that renders the enzyme non-functional. Other ABO variants show similar minimal changes. The A2 allele (a weak version of A) results from a single nucleotide deletion and a point mutation. The B3 allele results from point mutations that reduce enzymatic activity.

    These are not complex architectural changes requiring millions of years. They are “typos” in the code. Molecular analysis confirms that the mutation causing the O phenotype is a common, high-probability event.

    2. The Mathematical Feasibility of the Timeline

    A mathematical breakdown can be used to demonstrate that these variants would inevitably arise within a young-earth timeframe using standard mutation rates.

    Using a standard mutation rate (1.5×10^−8 per base pair per generation) and an exponentially growing population (starting from founders), mutations accumulate rapidly and easily. Calculations suggest that in a population growing from a small founder group, the first expected mutations in the ABO exons would appear as early as Generation 4 (approx. 80 years). Over a period of 5,000 years, with a realistic population growth model, the 1,065 base pairs of the ABO exons would theoretically experience tens of thousands of mutation events. The gene would be thoroughly saturated, meaning virtually every possible single-nucleotide change would have occurred multiple times.

    Specific estimates for the emergence of the ‘O’ allele place it within 50 to 500 generations (1,000 to 10,000 years) under neutral drift, or even faster with selective pressure. This perfectly fits the CHNP timeline of 6,000-10,000 years.

    3. Further Validation: The 19 Loci Analysis

    This pattern of “Ancient Majors, Recent Variants” is not unique to ABO. The 19 key human functional loci study also confirms that this is a systemic feature of the human genome.

    Across genes involved in immunity, metabolism, and pigmentation, derived variants consistently appear to have arisen within the last 10,000 years (Holocene). ALDH2: The variant causing the “Asian flush” (Glu504Lys) is estimated to be ~2,000 to 5,000 years old. LCT (Lactase Persistence): The mutation allowing adults to digest milk arose ~10,000 years ago, coinciding with the advent of dairy farming. HBB (Sickle Cell): The hemoglobin variant conferring malaria resistance emerged <10,000 years ago. In 89% of the analyzed cases, these variants are caused by single SNPs or Indels derived from the conserved major allele.

    The prediction that variant alleles must be derived via minimal modifications feasible within a young timeframe is strongly supported by the genetic data. The ABO system demonstrates that the “O” allele is merely a single deletion that could arise in less than 100 generations.

    This confirms the CHNP view that while the “major” alleles (A and B) represent the original, complex design (Major Allelic Architecture), the variants (O, A2, etc.) are the result of recent, rapid genetic entropy (cis-evolution) that requires no deep-time evolutionary mechanisms to explain.

    An ABO Blood Group Paradox

    As we have run through these first three predictions of the Created Heterozygosity model, we have dealt particularly with the ABO gene and have run into a peculiar evolutionary puzzle. Let’s first speak of this paradox more abstractly in the form of an analogy:

    Imagine a family of collectors who passed down two distinct types of antique coins (Coins A and B) to their descendants over centuries because those coins were valuable. If a third type of coin (Coin O) was also extremely valuable (offering protection/advantage) and easier to mint, you would predict the Ancestors would have kept Coin O and passed it down to both lineages alongside A and B. You wouldn’t expect the descendants to inherit A and B from the ancestor, but have to invent Coin O continuously from scratch every generation.

    By virtue of this same logic, evolutionary models must predict that the ‘O’ allele should be ancient (20 million years) due to balancing selection. However, the genetic data shows ‘O’ alleles are recent and arose independently in different lineages. This supports the CHNP view: the original ancestors were created with functional A and B alleles (heterozygous), and the O allele is a recent mutational loss of function.

    Prediction 4: Rapid Speciation and Adaptive Radiation

    If created heterozygosity is true, and organisms were designed with built-in potential for adaptation given their environment, then we should expect to find mechanisms of extreme foresight that permit rapid change to external stressors. There are, in fact, many such mechanisms which are written about in the scientific literature: contemporary evolution, natural genetic engineering, epigenetics, higher agency, continuous environmental tracking, non-random evolution, evo-devo, etc.

    The phenomenon of adaptive radiation—where a single lineage rapidly diversifies into many species—is clearly differentiating evidence for front-loaded heterozygosity rather than mutational evolution. Why? Because random mutation has no foresight. Random mutations do not prepare an organism for any eventuality. If it is not useful now, get rid of it. That is the mantra of evolutionary theory. That is the premise of natural selection. However, this premise is drastically mistaken.

    1. Natural Genetic Engineering & Non-Random Evolution

    The foundation of this alternative view is that genetic change is not accidental. Molecular biologist James Shapiro argues that cells are not passive victims of random “copying errors.” Instead, they possess “active biological functions” to restructure their own genomes. Cells can cut, splice, and rearrange DNA, often using mobile genetic elements (transposons) and retroviruses to rewrite their genetic code in response to stress. Shapiro calls the genome a “read-write” database rather than a read-only ROM.

    Building on this, Dr. Lee Spetner proposed that organisms have a built-in capacity to adapt to environmental triggers. These changes are not rare or accidental but can occur in a large fraction of the population simultaneously. This work is supported by modern research from people like Dr. Michael Levin and Dr. Dennis Noble. Mutations are revealing themselves to be more and more a predictable response to environmental inputs.

    2. The Architecture: Continuous Environmental Tracking (CET)

    If organisms engineer their own genetics, how do they know when to do it? This is where CET provides the engineering framework.

    Proposed by Dr. Randy Guliuzza, CET treats organisms as engineered entities. Just like a self-driving car, organisms possess input sensors (to detect the environment), internal logic/programming (to process data), and output actuators (to execute biological changes). In Darwinism, the environment is the “selector” (a sieve). In CET, the organism is the active agent. The environment is merely the data the organism tracks. For example, blind cavefish lose their eyes not because of random mutations and slow selection, but because they sense the dark environment and downregulate eye development to conserve energy, a process that is rapid and reversible. More precisely, the regulatory system of these cave fish specimens can detect the low salinity of cave water, which triggers the effect of blindness over a short timeframe.

    3. The Software: Epigenetics

    Epigenetics acts as the “formatting” or the switches for the DNA computer program. Epigenetic mechanisms (like methylation) regulate gene expression without changing the underlying DNA sequence. This allows organisms to adapt quickly to environmental cues—such as plants changing flowering times or root structures. These changes can be heritable. For instance, the environment of a parent (e.g., diet, stress) can affect the development of the offspring via RNA absorbed by sperm or eggs, bypassing standard natural selection. This blurs the line between the organism and its environment, facilitating rapid adaptation.

    4. The Result: Contemporary Evolution

    When these internal mechanisms (NGE, CET, Epigenetics) function, the result is Contemporary Evolution—observable changes happening in years or decades, not millions of years. Conservationists and biologists are observing “rapid adaptation” in real-time. Examples include invasive species changing growth rates in under 10 years, or the rapid diversification of cichlid fish in Lake Victoria.

    For Young Earth Creationists (YEC), Contemporary Evolution validates the concept of Rapid Post-Flood Speciation. It shows that getting from the “kinds” on Noah’s Ark to modern species diversity in a few thousand years is biologically feasible.

    Conclusion

    So, where does the information for all this diversity come from? This is the specific model (CHNP) that explains the source of the variation being tracked and engineered.

    This model posits that original kinds were created as pan-heterozygous (carrying different alleles at almost every gene locus). As populations grew and migrated (Contemporary Evolution), they split into isolated groups. Through sexual reproduction (recombination), the original heterozygous traits were shuffled. Over time, specific traits became “fixed” (homozygous), leading to new species.

    This model argues that random mutation cannot bridge the gap between distinct biological forms (the Valley of Death) due to toxicity and complexity. Therefore, diversity must be the result of sorting pre-existing (front-loaded) functional alleles rather than creating new ones from scratch.

    Look at it this way:

    1. Mendelian Speciation/Created Heterozygosity is the Resource: It provides the massive library of latent genetic potential (front-loaded alleles).

    2. Continuous Environmental Tracking is the Control System: It uses sensors and logic to determine which parts of that library are needed for the current environment.

    3. Epigenetics and Natural Genetic Engineering are the Mechanisms: They are the tools the cells use to turn genes on/off (epigenetics) or restructure the genome (NGE) to express those latent traits.

    4. Contemporary Evolution is the Observation: It is the visible, rapid diversification (cis-evolution) we see in nature today as a result of these internal systems working on the front-loaded information.

    Together, these concepts argue that organisms are not passive lumps of clay shaped by external forces (Natural Selection), but sophisticated, engineered systems designed to adapt and diversify rapidly within their kinds.

    The mechanism driving this diversity is the recombination of pre-existing heterozygous genes. Just 20 heterozygous genes can theoretically produce over one million unique homozygous phenotypes. As populations isolate and speciate, they lose their initial heterozygosity and become “fixed” in specific traits. This process, known as cis-evolution, explains diversity within a kind (e.g., wolves to dog breeds) but differs fundamentally from trans-evolution (evolution between kinds), which finds no mechanism in genetics.

    The CHNP model argues that mutations are insufficient to create the original genetic information due to thermodynamic and biological constraints. De novo protein creation is hindered by a “Valley of Death”—a region of sequence space where intermediate, misfolded proteins are toxic to the cell. Natural selection eliminates these intermediates, preventing the gradual evolution of novel protein folds.

    Mechanisms often cited as creative, such as gene duplication or recombination, are actually “remixing engines.” Duplication provides redundancy, not novelty, and recombination shuffles existing alleles without creating new genetic material. Because mutations are modifications (typos) rather than creations, the original functional complexity must have been present at the beginning.

    Genetics reveals that organisms contain “latent” or hidden information that can be expressed later.

    Information can be masked by dominant alleles or epistatic interactions (where one gene suppresses another). This allows phenotypic traits to remain hidden for generations and reappear suddenly when genetic combinations shift, facilitating rapid adaptation without new mutations.

    Genetic elements like transposons can reversibly activate or deactivate genes (e.g., in grape color or peppered moths), acting as switches for pre-existing varieties rather than creators of new genes.

    Summary

    The genetic evidence for created heterozygosity rests on the observation that biological novelty is ancient and conserved, while variation is recent and degenerative. By starting with ancestors endowed with high levels of heterozygosity, the “forest” of life’s diversity can be explained by the rapid sorting and recombination of distinct, front-loaded genetic programs.

  • The Irreducibility of Life

    The Irreducibility of Life

    In his paper “Life Transcending Physics and Chemistry,” Michael Polanyi examines biological machines in a way that illuminates the explanatory failures of materialism. The prevailing materialist paradigm that life can be fully explained by the laws of inanimate nature fails to account for higher ordered realities which have operations and structures that involve non-material judgements and interpretations. He specifically addresses the views of scientists such as Francis Crick, who, along with James Watson, argued for a total reductionist and nominalist view based on their discovery of DNA. For Polanyi, there is a life-transcending nature that all biological organisms have which is akin to machines and their transcendent properties. His central argument is based on the concept of “boundary control,” which argues the notion that there are laws that govern physical reactions (as Crick would accept) yet there are particular laws of form and function which are unique and separate from those lower-level laws.

    There is a real clash between Polanyi’s position and the reductionist/nominalist position which is commonly held by molecular biologists. To start to broach this divergence he explains how the contemporaneous discovery of the genetic function of DNA was interpreted as the final blow to vitalist thought within sciences. He writes:

    “The discovery by Watson and Crick of the genetic function of DNA (deoxyribonucleic acid), combined with the evidence these scientists provided for the self-duplication of DNA, is widely held to prove that living beings can be interpreted, at least in principles, by the laws of physics and chemistry.”

     Polanyi explicitly rejects Crick’s interpretation; that position is of the mainstream and popular level academia. Crick states that his principle “has so far been accepted by few biologists and has been sharply rejected by Francis Crick, who is convinced that all life can be ultimately accounted for by the laws of inanimate nature.” This same sentiment can indeed be found in Crick’s book “Molecules and Man.” Crick writes the following:

    “Thus eventually one may hope to have the whole of biology “explained” in terms of the level below it, and so on right down to the atomic level.”

    To dismantle the materialist argument, Polanyi utilizes the analogy of a machine. A machine cannot be defined or understood solely through the physical and chemical properties of its materials. Take a watch and put it into a machine that can read a detailed atomic map of the device: can even the best chemist give any coherent reason as to whether the watch is functioning or not? Worse—can one even tell you what a watch is, if all that exists is matter in motion for no particular reason? Polanyi writes it best:

    “A complete physical-chemical topography of my watch—even though the topography included the changes caused by the movements in the watch—would not tell us what this object is. On the other hand, if we know watches, we would recognize an object as a watch by a description of it which says that it tells the time of the day… We know watches and can describe one only in terms like ‘telling the time,’ ‘hands,’ ‘face,’ ‘marked,’ which are all incapable of being expressed by the variables of physics, length, mass, and time.”

    Once you see this distinction, you are invariably led (as Polanyi was) to two unique substratum of explanation; what he calls the concept of dual control. Obviously, there are physical laws which dictate constraints and operations of all material and all material things can be explained by these very laws. However, those laws are only meaningfully called constraints when there is some notion of intention or design to be constrained. The shape of any machine, man-made or biological, is not determined by natural laws. Not only is it not determined by them, it cannot be determined by them in any way. Polanyi elaborates on this relationship:

    “The machine is a machine by having been built and being then controlled according to principles of engineering. The laws of physics and chemistry are indifferent to these principles; they would go on working in the fragments of the machine if it were smashed. But they serve the machine while it lasts; machines rely for their operations always on the laws of physics and chemistry.”

    As I hinted at before, Polanyi also applies this logic to biological systems, arguing that morphology is a boundary condition in the same way that a design of a machine is a boundary condition. Biology cannot be reduced to physics because the structure that defines a living being is not the result of physical-chemical equilibration. Physical laws do not intend to create nor do they care that anything functions. Instead, “biological principles are seen then to control the boundary conditions within which the forces of physics and chemistry carry on the business of life.”

    Where Polanyi and Crick truly have the disagreement, then, is in their interpretation of the explanatory power of nature and how DNA is implicated within these frameworks. While Crick views DNA as a chemical agent that proves reducibility, Polanyi argues that the very nature of DNA as an information carrier proves the opposite. For a molecule to function as a code, its sequence cannot be determined by chemical necessity. If chemical laws dictated the arrangement of the DNA molecule, it would be a rigid crystal incapable of conveying complex, variable information. Polanyi writes:

    “Thus in an ideal code, all alternative sequences being equally probable, its sequence is unaffected by chemical laws, and is an arithmetical or geometrical design, not explicable in chemical terms.”

    By treating DNA as a transmitter of information, Polanyi aligns it with other non-physical forms of communication, such as a book. The physical chemistry of the ink and paper does not explain the content of the text. Similarly, the chemical properties of DNA do not explain the genetic information it carries. Polanyi contends that Crick’s own theory inadvertently supports this non-materialist conclusion:

    “The theory of Crick and Watson, that four alternative substituents lining a DNA chain convey an amount of information approximating that of the total number of such possible configurations, amounts to saying that the particular alignment present in a DNA molecule is not determined by chemical forces.”

    Therefore, the pattern of the organism, derived from the information in DNA, represents a constraint that physics cannot explain. It is a boundary condition that harnesses matter. Polanyi concludes that the organization of life is a specific, highly improbable configuration that transcends the laws governing its atomic constituents:

    “When this structure reappears in an organism, it is a configuration of particles that typifies a living being and serves its functions; at the same time, this configuration is a member of a large group of equally probable (and mostly meaningless) configurations. Such a highly improbable arrangement of particles is not shaped by the forces of physics or chemistry. It constitutes a boundary condition, which as such transcends the laws of physics and chemistry.”

    In this way, Polanyi refutes the nominalist materialist perspective by demonstrating that the governing principles of life—its form, function, and information content—are logically distinct from, and irreducible to, the physical laws that govern inanimate matter. Physical laws are, then, merely a piece of the puzzle of the explanation. What’s more, they are insufficient to account for the existence of particular organizations of matter which physical laws and chemistry are not determinative of.

  • Human Eyes – Optimized Design

    Human Eyes – Optimized Design

    Is the human eye poorly designed? Or is it optimal?

    If you ask most proponents of modern evolutionary theory, you will often hear that the eye is a pinnacle of unfortunate evolutionary history and dysteleology.

    There are three major arguments that are used in defending this view:

    The human eye:

    1. is inverted (retina) and wired backwards
    2. has a blind spot due to nerve exit
    3. Is fragile due to retinal detachment

    #1 THE HUMAN EYE IS INVERTED

    The single most famous critique is, of course, the backward wiring of the retina. An optimal sensor should use its entire surface area for data collection, right? The vertebrate eye requires obstruction of the eye-path by axons and capillaries before it hits the photoreceptors.

    Take the cephalopod eye: it has an everted retina, the photo receptors face the light and the nerves are behind them meaning there is no need for a blind spot. The human reversed wiring represents a mere local (rather than global) maximum where the eye could only optimize so far due to its evolutionary history.

    Yet, this argument misses non-negotiable constraints. There is a metabolic necessity for the human eye which doesn’t exist in the squid or octopus.

    Photoreceptors (the rods and cones) have the highest metabolic rate of any cell in the body. They generate extreme heat and oxygen levels and undergo constant repair from constant reaction from photons. The energy demand is massive. This is an issue of thermoregulation, not just optics.

    The reason this is important is because the vertebrate eye is structured with an inverted retina precisely for the survival and longevity of these high-energy photoreceptors. These cells require massive, continuous nutrient and oxygen delivery, and rapid waste removal.

    The current inverted orientation is the only geometric configuration that allows the photoreceptors to be placed in direct contact with the Retinal Pigment Epithelium (RPE) and the choroid. The choroid, a vascular layer, serves as the cooling system and high-volume nutrient source, similar to a cooling unit directly attached to a high-performance processor.

    If the retina were wired forward, the neural cabling would form a barrier, blocking the connection between the photoreceptors and the choroid. This would inevitably lead to nutrient starvation and thermal damage. Not only that, but human photoreceptors constantly shed toxic outer segments due to damage, which must be removed via phagocytosis by the RPE. The eye needs the tips of the photoreceptors to be physically embedded in the RPE. 

    If the nerve fibers were placed in front they would form a barrier, preventing waste removal. This specific geometry is a geometric imperative for long-term molecular recycling and allows for eyes that last for 80+ years on the regular.

    Critics often insist however that even given the neural and capillary layers being necessary for metabolism, it is still a poor design because they block or scatter incoming light. 

    Yet, research has demonstrated that Müller glial cells span the thickness of the retina and act as essentially living fiber-optic cables. These cells possess a higher refractive index than the surrounding tissue, which gives them the capability to channel light directly to the cones with minimal scattering.

    So this criticism actually goes from being a poor design choice into an awesome low-pass filter which improves the signal-to-noise ratio and visual acuity of the human eye.

    But wait, there’s more! The neural layers contain yellow pigments (lutein and zeaxanthin) which absorb excess blue and ultraviolet light that is highly phototoxic! This layer is basically a forcefield against harmful rays (photo-oxidative damage) which extends the lifespan of these super delicate sensors.

    #2 THE HUMAN EYE HAS A BLIND SPOT

    However, the skeptics will still push back (which leads to point number 2): But surely a good design would not include a blind spot where the optic nerve runs through! And indeed this point is a fairly powerful one at a glance. But on further inspection, we see that this exit point, where literally millions of nerve fibers bundle together to pass the photoreceptors, is an example of optimized routing and not a critical flaw of any kind.

    This is true for many reasons. For one, by having the nerves bundle into this reinforced exit point, in this way, maximized the structural robustness of the remaining retina. Basically, if it were not this way, and the nerve fibers exited individually or even in small clusters across the retina, it would radically lower the integrity of the whole design. It would make the retina prone to tearing during rapid eye movements (saccades). In other words, we wouldn’t be getting much REM sleep! That, but also, we’d be missing out on most looking around of any kind.

    I’d say, even if that was the only advantage, the loss of a tiny fraction of our visual field is worth the trade-off.

    Second, and this is important, the blind spot is functionally irrelevant. What do I mean by that? I mean that humans were designed with two eyes for the purpose of seeing depth-of-field, i.e., understanding where things are in space. You can’t do that with one eye, so that’s not an option. With two eyes, the functional retina of the left eye covers the blind spot of the right eye, and vice versa. There is no problem in this design if both the vision is covered and depth-of-field are covered 100% accurately: which they are.

    Third, the optic disc is also used for integrated signal processing, containing melanopsin-driven cells that calibrate brightness perception for the entire eye, using the exit cable as a sensor probe. That means that the nerves also detect brightness and run the logistics in a localized region which is incredibly efficient.

    #3 THE HUMAN EYE IS VULNERABLE

    That is, the vulnerability specifically refers to retinal detachment. That is when the neural retina separates from the RPE. Why does this happen? It is a consequence of the retina being held loosely against the choroid, largely by hydrostatic pressure. Critics call this a failure point. Wouldn’t a good design be one where the RPE is solidly in place, especially if it needs to be connected to the retina? Well… no, not remotely.

    The RPE must actively transport massive amounts of fluid (approximately 10 liters per day) out of the subretinal space to the choroid to prevent edema (swelling) and maintain clear vision. A mechanically fused retina would impede this rapid fluid transport and waste exchange. Basically, the critics offer a solution which is really a non-solution. There is no possible way the eye could function at all by the means they suggest as the alternative “superior” version.

    So, what have we learned?

    The human eye is not a collection of accidents, but a masterpiece of constrained optimization. When the entire system (eye and brain) is evaluated, the result is astonishing performance. The eye achieves resolution at the diffraction limit (the theoretical physical limit imposed by the wave nature of light!) at the fovea, meaning it is hitting the maximum acuity possible for an aperture of its size.

    The arguments that the eye is “sub-optimal” often rely on comparing it to the structurally simpler cephalopod eye. Yet, cephalopod eyes lack trichromatic vision (they don’t see color like we do), have lower acuity (on the scale of hundreds of times worse clarity), and only function for a lifespan of 1–2 years (whereas the human eye must self-repair and maintain high performance for eight decades). The eye’s complexity—the Müller cells, the foveal pit, and the inverted architecture—are the necessary subsystems required to achieve this maximal performance within the constraints of vertebrate biology and physics.

    That’s not even getting to things like mitochondrial microlens in our cells which are essential for processing light. Recent research suggests that mitochondria in cone photoreceptors may actually function as micro-lenses to concentrate light, adding another layer of optical optimization. Optimization which would need to be there, perhaps a lot earlier than even the reversed lens structure.

    The fact that the eye is so optimal still remains, despite the critics best attempts at thwarting it. Therefore, the question remains, how could something so optimized evolve by random chance mutation, as well as so early and often in the history of biota?