Les attentes différenciées des talents selon le sexe : une approche par la justice procédurale et la justice distributive
Bibliographic record
Abstract
La présente recherche vise à étudier l’impact différencié selon le sexe des justices procédurale et distributive, sur l’intention de rester des travailleurs considérés comme des talents, via l’effet médiateur de l’engagement organisationnel. Les données utilisées pour le traitement statistique proviennent d’une enquête menée auprès d’un échantillon de 220 talents œuvrant dans des organisations de la Région Centre Val de Loire (France). Les principaux résultats indiquent que seule la justice distributive contribue à faire augmenter l’intention de rester des talents féminins. De plus, l’engagement organisationnel agit comme variable médiatrice seulement chez les talents féminins. Chez les talents masculins, seule la justice procédurale fait augmenter l’engagement organisationnel mais n’a pas d’impact direct sur leur intention de rester. La recherche se conclut en élaborant certaines pistes pour mieux fidéliser les talents en renforçant leur intention de rester.
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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 | 0.015 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.004 |
| 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".