Argument

Genetic Entropy Argument

Intro

John Sanford spent his career inside mainstream genetics. He held a professorship at Cornell, helped invent the gene gun (the biolistic-particle-delivery system now used across agricultural biotech), and held more than thirty patents. Then, in middle age, after a reconsideration of his evolutionary assumptions, he wrote Genetic Entropy and the Mystery of the Genome (2005) and proposed an argument that has occupied the YEC apologetic toolkit ever since.

The argument is short. Step one: humans pick up dozens to hundreds of new mutations every generation. Step two: almost all of those mutations are slightly harmful; helpful ones are rare. Step three: natural selection cannot catch mutations whose harmful effect is below a certain size, because they look neutral on a single generation's reproductive success. Step four: over many generations the slightly-harmful mutations slip through selection and accumulate, like a battery losing a small fraction of its charge every cycle. The genome runs down.

If Sanford is right, complex genomes cannot be millions of years old without already having collapsed into non-viability. The human genome would have melted down long before now. Sanford's conclusion is that the genome is young, on the order of thousands to tens of thousands of years, which means the deep-time chronology of human evolution is incompatible with the population-genetics data.

The mainstream reply is that purifying selection is more efficient than Sanford models. Mainstream geneticists argue that selection acts on combinations of mutations, that recombination breaks up linked deleterious mutations, and that beneficial mutations supply enough offset given large populations and deep time. Sanford's simulation tool, Mendel's Accountant, has been criticized for parameter choices that allegedly skew toward decline.

The debate is unsettled. Sanford has serious mainstream credentials and is engaging real population-genetics literature; mainstream geneticists are not dismissing him as fringe so much as disputing his model parameters. The page works through the argument as a structured syllogism with second-order arguments per premise, anticipated objections, rebuttals, a live-cite kit, and tactical notes. The page is a debate-prep companion to the concept-side hub at Genetic Entropy, which carries the descriptive history; this page carries the structured live-deployment form.

In full

A population-genetics deductive argument advanced by John C. Sanford in Genetic Entropy and the Mystery of the Genome (2005). Premises: (P1) empirically-measured deleterious mutation rates in humans are ~100 to 300 per individual per generation (Eyre-Walker and Keightley, Nature 397, 1999), with the vast majority being individually slightly deleterious and below the threshold of single-generation selection; (P2) natural selection cannot effectively remove near-neutral deleterious mutations because their per-individual fitness effect is below what selection on reproductive success can discriminate, and Muller's ratchet predicts steady degradation in finite populations; (P3) at measured rates and selection efficiencies, the human genome would have degraded to non-viability within hundreds of thousands of years, which is far short of the supposed million-plus-year human-lineage chronology. Conclusion: either the chronology is wrong (favoring a young earth) or the population-genetics framework is fundamentally misunderstood. The mainstream rescue is that purifying selection on combinations of mutations, recombination, and synergistic epistasis are more efficient than Sanford's model allows. This page is structured as debate prep, each premise carries a second-order positive case, anticipated objections, rebuttals, a live-cite kit, and tactical notes.

Argument structure

Form

Deductive with empirical premises. The conclusion follows necessarily from the conjunction of premises if the empirical numbers and the population-genetics theorem are correct. The soundness contest is on the empirical premises, especially the selection-efficiency assumption in P2 and the genome-decay extrapolation in P3. Mainstream population geneticists do not dispute the form; they dispute the parameter values feeding it. The argument is therefore deductively valid but empirically contested.

P1, Measured deleterious-mutation rates produce ~100 to 300 mildly harmful mutations per individual per generation

Affirmative case (second-order arguments)

1. Eyre-Walker and Keightley 1999, Nature 397. Adam Eyre-Walker and Peter Keightley, "High genomic deleterious mutation rates in hominids", Nature 397 (1999), 344. Using comparative-genomics methods on human and chimp coding sequences, the team estimated the deleterious mutation rate per human generation at ~1.6 deleterious mutations per zygote in coding regions alone, with the broader genome rate substantially higher. The implication of their own paper: "high deleterious mutation rates are difficult to reconcile with the apparent low impact on human fitness", which is precisely the entropy problem.
2. Lynch 2010, Proceedings of the National Academy of Sciences. Michael Lynch, "Rate, molecular spectrum, and consequences of human mutation", PNAS 107 (2010), 961. Lynch's analysis updates the mutation-rate estimate using direct whole-genome sequencing of parent-offspring trios; estimates ~75 to 175 new mutations per individual per generation, with a substantial deleterious fraction. Lynch himself writes, "the long-term consequences of these results suggest a substantial reduction in mean fitness", which is again the entropy thesis stated in mainstream voice.
3. Most are slightly deleterious, not strongly harmful. Strongly harmful mutations are filtered out within a few generations by purifying selection; they are visible in clinical genetics as recessive disease alleles or as embryonic lethals. The bulk of new mutations are in the slightly-deleterious or near-neutral range that Kimura's neutral theory identified; these are the ones that pose the entropy problem because they slip past single-generation selection.
4. The numbers are conservative for Sanford's case. Sanford uses 100 to 300 per generation; mainstream estimates land at 75 to 175 (Lynch) up to several hundred (Eyre-Walker, Keightley); the disagreement is in the deleterious fraction, not in the mutation count. Sanford's argument is robust across the range mainstream geneticists actually report.

Anticipated objections

1. "Most of the genome is non-coding; mutations there have no fitness effect."
2. "The 'deleterious' label is not as straightforward as you suggest; many supposedly deleterious mutations may have small positive effects in some environments."
3. "You are conflating the mutation rate with the deleterious-mutation rate; the latter is much smaller."

Rebuttals

1. The "junk DNA" framing has been substantially revised. The ENCODE project (2012, Nature) reported that as much as 80 percent of the human genome shows biochemical activity. Mainstream geneticists dispute the strong "80 percent functional" claim, but the bare assumption that non-coding DNA is functionally inert has been weakened. Even granting some non-coding regions are neutral, the coding genome alone (~1.5 to 2 percent of total DNA) absorbs enough mutations per generation to produce the entropy problem. Failure mode: invoking a non-coding-is-noise assumption that the ENCODE data and later work have weakened.
2. Eyre-Walker and Keightley themselves classify the bulk as deleterious. The mainstream literature does not characterize most mutations as conditionally neutral; it identifies a clear deleterious fraction. Sanford is not inflating the deleterious count beyond what mainstream geneticists report. Failure mode: shifting to a contestable conditional-neutrality framing when the mainstream literature itself does not adopt it.
3. Sanford uses standard mainstream estimates, not inflated ones. Lynch's 75 to 175 per generation (PNAS 2010) bookends Sanford's range. Whether the deleterious fraction is 80 percent or 30 percent, the per-generation deleterious load is in the dozens, which is the load-bearing number. Failure mode: rejecting the count without engaging the mainstream literature that supplies it.

Live-cite kit

• Scripture: Genesis 3:17-19 (the curse on the ground; creation under futility); Romans 8:20-22 (creation subjected to futility, bondage to corruption); Genesis 5 (antediluvian lifespans declining post-Flood, consistent with entropy)
• Scholarly: Adam Eyre-Walker and Peter Keightley, Nature 397 (1999); Michael Lynch, Proceedings of the National Academy of Sciences 107 (2010); Alexey Kondrashov, American Journal of Medical Genetics (1995); John Sanford, Genetic Entropy and the Mystery of the Genome (FMS, 2005, 4th ed. 2014)
• Aphorism: "Every generation, the human genome picks up dozens of new mistakes. Selection catches the big ones. The small ones add up."

Tactical notes

• Lead with Lynch's PNAS paper if the opponent is mainstream-credentialed. It is mainstream, recent, and uses the same numbers Sanford uses.
• Do not get pulled into ENCODE-vs-junk-DNA arguments at length. The coding genome alone supplies enough mutations to make the case; the non-coding question is a sidetrack.
• Force-commit move: "What do you think the per-generation deleterious mutation count is? Use any mainstream number you like." Then build from whatever number the opponent gives.

P2, Selection cannot remove near-neutral deleterious mutations; Muller's ratchet predicts progressive degradation

Affirmative case (second-order arguments)

1. Kimura's near-neutral theory. Motoo Kimura, The Neutral Theory of Molecular Evolution (1983). Kimura's central insight was that mutations with very small fitness effects behave nearly as neutral mutations in finite populations; their fate is dominated by genetic drift rather than by selection. The threshold below which selection cannot effectively distinguish deleterious from neutral is roughly 1 / 2Ne for a population of effective size Ne. For humans (Ne ~10,000), the threshold is small; the vast majority of new deleterious mutations fall below it.
2. Muller's ratchet. H. J. Muller, "Our load of mutations", American Journal of Human Genetics 2 (1950), 111. Muller's classical result: in finite asexual populations, deleterious mutations accumulate irreversibly because once a class of mutation-free individuals is lost to drift, it cannot be regenerated. Sexual recombination ameliorates but does not eliminate the effect; the ratchet still applies to the lowest-fitness class in any finite population.
3. Kondrashov's "mutation load" problem. Alexey Kondrashov, "Contamination of the genome by very slightly deleterious mutations: why have we not died 100 times over?", Journal of Theoretical Biology 175 (1995), 583. Kondrashov, a mainstream population geneticist, frames the problem in exactly this language. His proposed rescue is synergistic epistasis, the assumption that deleterious mutations have multiplicatively bad effects when combined, so that selection can act on bundles. Whether synergistic epistasis actually exists at the required scale is contested.
4. Empirical evidence from clinical genetics. Genetic counselors and clinical geneticists routinely deal with the accumulated load of deleterious alleles in human populations. Founder-effect populations show elevated frequencies of rare diseases; consanguinity raises homozygous-recessive disease incidence. The load is real and visible; the entropy question is whether it accumulates at a rate that destabilizes the genome over deep time.
5. Mendel's Accountant simulations. John Sanford, John Baumgardner, Wesley Brewer et al. developed Mendel's Accountant as a forward-time population-genetics simulation explicitly modeling deleterious-mutation accumulation under user-specified selection regimes. Published in Scalable Computing and IEEE conference proceedings. The simulations consistently show fitness decline under realistic parameter choices, with mainstream-disputed parameter sensitivity discussed under objections.

Anticipated objections

1. "Purifying selection is more efficient than Sanford allows; recombination breaks up linked deleterious mutations and lets selection act on combinations."
2. "Synergistic epistasis (Kondrashov's rescue) lets selection remove bundles of slightly-deleterious mutations even when each individually is below the selection threshold."
3. "Truncation selection, in which the lowest-fitness individuals do not reproduce, is a more realistic model than soft selection and dissolves the ratchet."
4. "Mendel's Accountant has parameter choices that skew toward decline; mainstream simulations with different parameters do not show entropy."

Rebuttals

1. Recombination ameliorates but does not eliminate the ratchet. The selection threshold is set by effective population size; recombination changes which mutations are linked, but the bulk near-neutral fraction remains below the threshold either way. Mainstream models that show stability assume specific recombination rates and selection coefficients; the assumptions are contestable. Sanford's reply is that mainstream models often assume the conclusion they are trying to prove, that selection is efficient enough to maintain stability. Failure mode: the rescue presupposes the load-bearing premise it is invoked to defend.
2. Synergistic epistasis is a hypothesis, not a measurement. Kondrashov proposed synergistic epistasis as the only mathematical rescue for the mutation-load problem. Whether such epistasis exists at the required scale in real genomes is an empirical question with limited direct evidence. Sanford and Carter have argued that empirical evidence supports diminishing-returns epistasis (the opposite direction), which would worsen the entropy problem rather than rescue it. Failure mode: invoking a hypothesized mechanism whose empirical reality is in dispute.
3. Truncation selection is unrealistic for real populations. Truncation selection requires that all individuals below a cutoff reproductive-success threshold die without reproducing; real populations show much softer reproductive variance, especially in low-mortality modern human societies. Sanford's reply is that truncation selection is a mathematical convenience that does not represent how human selection actually operates. Failure mode: a stylized selection regime invoked as if it were biologically realistic.
4. Mendel's Accountant parameter sensitivity cuts both ways. Critics argue Sanford's parameters skew toward decline; defenders argue mainstream simulations use unrealistically efficient selection. The technical debate is genuine and unresolved. Sanford has responded to the parameter-choice critique in multiple venues; the responses have not been formally engaged in mainstream peer-reviewed venues, which counts against the argument's mainstream uptake but does not refute its substance. Failure mode: dismissing a contested simulation result without engaging the substantive parameter-choice debate.

Live-cite kit

• Scholarly: Motoo Kimura, The Neutral Theory of Molecular Evolution (Cambridge, 1983); H. J. Muller, American Journal of Human Genetics 2 (1950); Alexey Kondrashov, Journal of Theoretical Biology 175 (1995); John Sanford, Genetic Entropy and the Mystery of the Genome (FMS, 2005, 4th ed. 2014); John Baumgardner, Wesley Brewer, John Sanford, Mendel's Accountant technical papers (IEEE, Scalable Computing)
• Aphorism: "Selection has a minimum size of mistake it can catch. Most mistakes are below that size. The math runs in one direction."

Tactical notes

• Lead with Kondrashov. Mainstream population geneticist who frames the problem in exactly the same language Sanford does. This breaks the "Sanford is fringe" frame at the door.
• Be ready for synergistic epistasis. It is the strongest mainstream rescue and the only mathematically-coherent way to get selection above the per-mutation threshold. Reply that it is a hypothesis without strong empirical support and that diminishing-returns epistasis (the opposite) has more support.
• Do not get pulled deep into Mendel's Accountant parameter debates in live debate. The argument's force does not require defending specific simulation parameter choices; it requires the structural population-genetics result that near-neutral mutations accumulate.
• Force-commit move: "What is the fitness-effect threshold below which selection cannot remove a mutation in a population of effective size 10,000? And what fraction of new mutations falls below that threshold?" Forces the opponent to commit to specific population-genetics numbers.

P3, The accumulated load drives genome non-viability within hundreds of thousands of years

Affirmative case (second-order arguments)

1. The arithmetic. At ~100 to 300 deleterious mutations per generation, with selection removing only the most strongly deleterious fraction (perhaps a few per generation), the net accumulation is dozens per generation. Over 10,000 generations (~250,000 years at 25 years per generation), the accumulated load is hundreds of thousands of slightly-deleterious mutations per individual. The aggregate fitness cost, even at very small per-mutation effect, becomes substantial.
2. Mendel's Accountant projections. Sanford and collaborators report that under mainstream-consistent parameter choices, the simulated fitness trajectory declines steadily over 1,000 to 10,000 generations, with the population approaching non-viability within tens of thousands of generations. The result is not a one-off; it recurs across parameter-sensitivity analyses within the model.
3. The Crow estimate. James Crow, "The high spontaneous mutation rate: Is it a health risk?", PNAS 94 (1997), 8380. Crow, a mainstream population geneticist, calculated that the human genome's mutation load is rising at ~1 to 2 percent per generation under modern conditions of relaxed selection (medical care, low infant mortality). Sanford's argument extends Crow's framing: if the load is rising under modern conditions, the genome cannot have been stable across millions of years.
4. The Sanford-Carter convergence with mitochondrial Eve dating. Mitochondrial Eve Argument independently arrives at a ~6,000 to 10,000 year coalescence using measured pedigree mutation rates. The convergence of two independent lines of population-genetics evidence, mtDNA coalescence and nuclear-genome entropy, points to the same young chronology.

Anticipated objections

1. "Lenski's long-term E. coli evolution experiment, over 75,000 generations, does not show the predicted decay; bacteria are robust to high mutation rates."
2. "Population-genetics simulations with mainstream parameters show stability over millions of generations."
3. "Modern relaxed-selection conditions are not how human evolution operated; pre-modern populations had strong selection, with infant mortality at 50 percent."
4. "The argument extrapolates from current rates without accounting for adaptive evolution over deep time."

Rebuttals

1. Lenski's E. coli shows substantial degradative change. Michael Behe's analysis in Darwin Devolves (HarperOne, 2019) argues that Lenski's E. coli show overwhelming degradative change (loss of function, broken regulatory elements) and very limited constructive change (the famous citrate-utilization mutation involves rearrangement of existing capacity rather than novel functional information). The bacteria do not melt down in the E. coli case because (a) bacterial generation times let purifying selection act on functional metabolism continuously and (b) bacteria have less coding-genome and less regulatory complexity than vertebrates. The Lenski experiment does not refute the entropy argument for vertebrate genomes. Failure mode: a bacterial-genome result extrapolated to a vertebrate-genome question with different selection dynamics.
2. Mainstream simulations assume the conclusion. Stability-favoring simulations typically assume highly efficient purifying selection or strong synergistic epistasis. These assumptions are not independently demonstrated; they are required to get the desired result. Sanford's case is that the assumptions are not warranted by the empirical mutation-rate and selection-effect data. Failure mode: a simulation result that depends on unverified assumptions being passed as empirical refutation.
3. Pre-modern selection was real but limited in what it could remove. Even at 50 percent infant mortality, selection acts on the entire individual, including the strongly deleterious mutations that produce embryonic or childhood lethality. The vast majority of slightly-deleterious mutations remained below the selection threshold then as now. The relaxed-selection era has accelerated the load increase, not initiated it. Failure mode: pretending high mortality is the same as efficient slight-deleterious selection, when high mortality acts predominantly on strong-effect alleles.
4. Adaptive evolution cannot rescue the genome from entropy. Beneficial mutations occur, but at rates orders of magnitude lower than deleterious mutations, and the proportion of fixed beneficial mutations is even smaller. Beneficial mutations contribute to local adaptation; they do not reverse the accumulation of slightly-deleterious mutations across the genome. Failure mode: invoking adaptive evolution as if it were the inverse of the entropy process, when the two operate at different scales and on different fitness components.

Live-cite kit

• Scripture: Genesis 5, Genesis 11 (declining post-Flood lifespans, consistent with progressive load); Romans 8:20-22 (creation under futility); Genesis 3:17-19 (the curse on the ground)
• Scholarly: James Crow, Proceedings of the National Academy of Sciences 94 (1997); John Sanford, Genetic Entropy and the Mystery of the Genome (FMS, 2005, 4th ed. 2014); John Sanford and Christopher Rupe, Contested Bones (FMS, 2017); Michael Behe, Darwin Devolves (HarperOne, 2019); Mendel's Accountant technical papers
• Aphorism: "If the genome were millions of years old, it would have already melted down. The fact that we are still here is the evidence that it is young."

Tactical notes

• Lead with Crow's PNAS paper for the load-rising-now claim. It is mainstream and recent and frames the entropy problem in exactly the language Sanford uses.
• Have Lenski / Behe at hand for the E. coli objection. Behe's Darwin Devolves argument is the standard reply.
• Be honest about the contested status. Mainstream geneticists do not accept Sanford's conclusions; the debate is live. Steel-manning the mainstream rescue strengthens the case rather than weakening it.
• Force-commit move: "If selection were efficient enough to maintain the genome over a million years at observed mutation rates, what is the selection coefficient threshold? And how does that match the empirically-measured distribution of mutation effects?" Forces a quantitative engagement rather than hand-waving.

Conclusion

Either the chronology of human evolution is wrong, favoring a young chronology compatible with biblical timeframes, or the standard population-genetics framework is fundamentally misunderstood. The mutation rates are empirically measured and not seriously disputed. The near-neutral selection threshold is a theorem of population genetics, not a YEC invention. The accumulated load over deep time produces non-viability under mainstream-consistent parameter choices. The standard rescues (synergistic epistasis, truncation selection, recombination efficiency) require empirically-unconfirmed assumptions and are themselves contested. The deductive form is valid; the empirical premises are contested but plausible; the conclusion forces a choice between revising the chronology and revising the population-genetics framework. The young-chronology option is at minimum a live competitor.

Master objections to the argument as a whole

1. "Sanford is not in the mainstream peer-reviewed literature." Reply: Sanford was a Cornell professor with mainstream genetics credentials; the entropy framing engages Kimura, Muller, Kondrashov, Crow, and Eyre-Walker, all of whom are mainstream. The argument runs through mainstream concepts even when the conclusion is rejected by the mainstream. The interpretive question, whether the load actually destabilizes the genome over deep time, is live within the mainstream literature (Crow 1997).
2. "Other lines of evidence (radiometric, fossil) settle the chronology regardless of population genetics." Reply: the chronology rests on the convergence of multiple lines, and the argument shows that one of those lines points in the opposite direction. Convergence requires all lines to agree; when one line disagrees, the convergence claim is weakened. See also Carbon-14 in Deep-Time Specimens Argument and Soft Tissue in Dinosaur Fossils Argument for parallel chronology-pressure cases.
3. "Christians can accept the mainstream timeline." Reply: agreed. The codex treats Young Earth Creationism, Old Earth Creationism, the Framework Hypothesis, and Walton's Functional Cosmic Temple as four live in-house Christian readings of Genesis (see Genesis Interpretation Spread). The argument supports the YEC reading; rejecting it does not put a Christian outside the faith.
4. "The Lenski E. coli experiment is the empirical refutation." Reply: Behe's Darwin Devolves (2019) analyzes the Lenski data and argues it shows degradative change overwhelmingly; the bacteria do not melt down because of generation-time and selection-on-metabolism dynamics that do not apply to vertebrates. The experiment is not a clean refutation.

Tactical opening / closing

Opening line: "John Sanford was a Cornell geneticist who helped invent the gene gun. He spent his career inside mainstream science. Then he wrote a book arguing that the human genome is decaying, not improving, and that the decay rate is incompatible with the deep timescales evolution requires. Let me walk you through the four-step argument, then we can see where it lands."

Closing landing strip: "The Genetic Entropy Argument does not deductively prove a young earth. It shows that the empirically-measured mutation rates, combined with the population-genetics theorem that selection cannot catch near-neutral mutations, produce a genome trajectory that does not survive millions of years. Either selection is more powerful than the mainstream literature lets it be, or the chronology is shorter than the mainstream chronology says. That is the choice."

Connection to Scripture

• Genesis 3:17-19, the curse on the ground; creation subjected to futility; the genomic resonance with the Fall.
• Romans 8:20-22, "creation was subjected to futility... in bondage to corruption." The entropy of the genome reads as the empirical face of the post-Fall world.
• Genesis 5, antediluvian lifespans of 800 to 950 years; post-Flood lifespans in Genesis 11 decline rapidly to ~120 years; the decline matches an accelerated load on a recently-bottlenecked human population.
• Romans 5:12, "through one man sin entered into the world, and death through sin", the theological frame that makes a recently-decaying genome theologically resonant.
• 1 Corinthians 15:45, "the first man Adam became a living soul", the historical Adam framing.

Patristic / scholarly note

Classical / patristic:

• The patristic tradition lacks a developed population-genetics framework, but the doctrine of the Fall (Augustine, De Civitate Dei, c. 426) provides the theological frame within which genomic decay reads as the empirical face of the post-Fall curse.

Modern (mainstream):

• H. J. Muller, American Journal of Human Genetics 2 (1950), the original ratchet result.
• Motoo Kimura, The Neutral Theory of Molecular Evolution (Cambridge, 1983), the near-neutral framework.
• Alexey Kondrashov, Journal of Theoretical Biology 175 (1995); American Journal of Medical Genetics 1995, the "why have we not died 100 times over" framing.
• James Crow, Proceedings of the National Academy of Sciences 94 (1997), the mutation-load-as-health-risk framing.
• Adam Eyre-Walker and Peter Keightley, Nature 397 (1999), high deleterious-mutation-rate measurement.
• Michael Lynch, Proceedings of the National Academy of Sciences 107 (2010), updated direct-sequencing estimate.

YEC / ID modern:

• John C. Sanford, Genetic Entropy and the Mystery of the Genome (FMS, 2005, 4th ed. 2014), the canonical statement.
• John Sanford and Christopher Rupe, Contested Bones (FMS, 2017), human-fossils synthesis.
• Robert W. Carter (Creation Ministries International), mtDNA and Y-chromosomal synthesis.
• John Baumgardner, Wesley Brewer, Mendel's Accountant development team.
• Michael Behe, Darwin Devolves (HarperOne, 2019), the Lenski E. coli analysis and the broader devolution thesis.

Critics:

• Joe Felsenstein, mainstream population geneticist, ongoing critiques of Sanford's selection-efficiency assumptions on Panda's Thumb and in published commentary.
• Michael Lynch (mainstream, despite the entropy-friendly framing of his 2010 PNAS paper), proposes mainstream resolution through epistasis and recombination.
• Dennis Venema (Adam and the Genome, Brazos 2017), theistic-evolution critique of YEC population genetics generally.

See also

• Genetic Entropy, concept-side hub with descriptive history and mainstream critique
• Mitochondrial Eve Argument, sister Tier-1 YEC scientific case from mtDNA coalescence
• Population Genetics for Historical Adam Argument, sister case on Adam-Eve historicity
• Soft Tissue in Dinosaur Fossils Argument, sister Tier-1 YEC scientific case from paleontology
• Carbon-14 in Deep-Time Specimens Argument, sister Tier-1 YEC scientific case on radiocarbon
• Young Earth Creationism, the position the argument supports
• Old Earth Creationism, in-house Christian alternative
• Theistic Evolution, in-house Christian alternative
• Adam and Eve Historicity, doctrinal-anthropological hub
• Genesis Interpretation Spread, four live in-house Christian readings of Genesis
• Origins, category master
• Arguments, top-level master index