Les réseaux personnels et la diffusion des informations sur les emplois
Bibliographic record
Abstract
L'auteur propose une approche déductive pour montrer comment la structure et le contenu des réseaux personnels de relations sociales affectent l'accès à l'information sur les offres d'emplois dans une organisation. L'analyse porte sur les conditions qui affectent l'utilisation des différents champs de relations sociales (relations de sociabilité, relations occupationnelles et relations indirectes) à l'intérieur des réseaux personnels, sur les rapports entre les informateurs et les répondants et sur la longueur des chaînes d'informations. Deux résultats en particulier pourront retenir l'attention : la position de classe ne suffit pas à expliquer l'accès à certains types de relations et les liens forts jouent un rôle important dans la diffusion d'informations sur les emplois alors que les liens faibles ne semblent caractériser qu'un certain type d'occupations, les cadres et les administrateurs.
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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 | 0.011 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".