Les tensions entre engagements privés et engagements collectifs, des variations au cours du temps selon le genre et les groupes sociaux
Bibliographic record
Abstract
Tant les engagements de proximité que ceux qui se revendiquent de causes plus générales sont parcourus au cours du temps par des mouvements d’investissement et de retrait. Les premiers, dont la visibilité reste trop souvent incertaine nonobstant leur utilisation par les politiques publiques, sont principalement évoqués dans cet article. Une séquence temporelle particulière est retenue, celle des transitions de fin de carrière et de début de retraite, et elle est étudiée dans les mouvements d’engagement et de désengagement entre sphère privée et sphère publique. Quel que soit leur lieu d’expression, ces engagements sont à analyser comme formes et normes de la responsabilité à l’égard d’autrui, différemment configurées selon le genre et selon les milieux sociaux.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".