Modularité massive ou construction sociale? : une analyse de l'approche psychoévolutionniste de Cosmides et Tooby.
Bibliographic record
Abstract
Ce mémoire se veut un examen épistémologique de la thèse psychoévolutionniste de Leda Cosmides et John Tooby, principalement en ce qui concerne la modularité massive. Nous avons tâché de voir si la modularité massive permet de rendre compte des processus mentaux complexes en nous penchant plus particulièrement sur le cas des émotions. Nous explorons d'abord la thèse de Cosmides et Tooby en la distinguant d'avec d'autres conceptions comme l'écologie béhaviorale et en expliquant le rôle particulier que jouent les émotions au sein de la théorie. Nous analysons ensuite la thèse de la modularité massive et les différents arguments théoriques ou empiriques qui l'appuient, et évaluons finalement des critiques de la modularité émises par certains philosophes, dont David Buller.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.045 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".