How a Generation Was Misled About Natural Selection (Natural Selection: How it Works, How it Applies to Culture)
Bibliographic record
Abstract
Building on von Neumann's pioneering insights about self-replicating automata, John Holland identified three requirements for natural selection: (1) sequestration of inherited information, (2) a clear-cut distinction between genotype and phenotype, and as a consequence of 1 and 2, (3) no transmission of acquired traits. This paper explains why Dawkins’ characterization of natural selection in terms of replicators with longevity, fedundity and fidelity was simpler, and caught the public imagination, but it threw the baby out with the bathwater. It led to cultural evolution being misleading described as a Darwinian process despite that it lacks the requisite deep structure for such a process, and lacks signature characteristic of evolution by natural selection: no transmission of acquired traits. This paper suggests that culture evolves through a more haphazard process akin to the process by which the earliest protocells evolved, a process that does not involve a self-assembly code yet is sufficient for cumulative, adaptive, open-ended change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".