The Epistemology of Evolutionary Psychology Offers a Rapprochement to Cultural Psychology
Bibliographic record
Abstract
Many detractors of evolutionary psychology (EP) presume that adaptive arguments are nothing more than whimsical and unfalsifiable just-so stories. The reality though is that the epistemology of EP is precisely the opposite of this antiquated canard in that it fixes the evidentiary threshold much higher than is typically achieved by most scientists. EP amasses evidence across cultures, time periods, disciplines, paradigms, methodologies, and units of analyses in validating a given scientific explanation. These nomological networks of cumulative evidence stimulate greater interdisciplinarity, lesser methodological myopia, and increased consilience (unity of knowledge). A component in building such nomological networks is to examine phenomena that are cross-culturally invariant (human universals) versus those that vary cross-culturally as adaptive responses (the domain of behavioral ecologists and gene-culture coevolution modelers). The epistemological efficacy of this unique approach is highlighted using two cases studies, the sex-specificity of toy preferences and men's preference for the hourglass figure.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".