Bibliographic record
Abstract
Evolutionary psychiatry suggests that mental disorders can be explained in evolutionary terms (a) as failures of psychological mechanisms to produce the adaptive effects for which they were naturally selected, (b) as mismatches between naturally selected psychological mechanisms and contemporary environmental pressures, or (c) as naturally selected psychological mechanisms whose effects continue to be adaptive.In this paper, I present a philosophical critique of evolutionary psychiatry that draws on Subrena Smith's matching problem for evolutionary psychology.For evolutionary psychiatry hypotheses to be empirically supported, proponents of evolutionary psychiatry must demonstrate (1) that the contemporary psychological mechanisms involved in mental disorders resemble the psychological mechanisms of our evolutionary ancestors, (2) that the contemporary psychological mechanisms are phylogenetically descended from the ancestral psychological mechanisms, and (3) that the ancestral psychological mechanisms were naturally selected because their effects had adaptive benefits.However, for many mental disorders, evolutionary psychiatry lacks the methodological resources to demonstrate these conditions.Therefore, many evolutionary psychiatry hypotheses are empirically untestable and remain indefinitely underdetermined by data.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.033 |
| Scholarly communication | 0.003 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".