Quelques contributions de Peirce à l’épistémologie des sciences sociales
Bibliographic record
Abstract
Le but de l’article est surtout de montrer que si nous réfléchissons aux liens entre deux notions de base de la philosophie de Peirce, soit le traité de la sémiosis et le traité des catégories (soit la priméité, la secondéité et la tiercéité), nous pouvons y découvrir les bases d’une épistémologie des sciences interprétatives, et notamment les sciences sociales qui se réclament d’une telle perspective. Si tout l’interactionnisme repose sur une notion interactive du signe, c’est que déjà chez Peirce l’interprétation des signes est sociale. De plus, s’il est bien exact que les sciences sociales ont souvent voulu thématiser l’action humaine, et ce notamment au 20e siècle, il est clair qu’une troisième idée de Peirce, soit la notion de science normative de l’action appelée « practics », a quelque chose d’inaugural au plan conceptuel, tant pour la sociologie que pour une éthique qui ne voudrait pas s’identifier à la morale mais thématiser sa réflexion pratique.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.007 | 0.046 |
| Scholarly communication | 0.015 | 0.021 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".