Bibliographic record
Abstract
Résumé Ce texte se veut une synthèse des connaissances actuelles sur la gestion stratégique des ressources humaines. Après une introduction sur le concept de stratégie des ressources humaines et sur les raisons d’être d’une telle stratégie, le texte reprend la distinction classique entre «processus de gestion stratégique des ressources humaines» et «contenu de la stratégie des ressources humaines» (approches process et content ). Dans le premier cas, l’évolution historique de la gestion stratégique des ressources humaines, le double processus d’alignement (réactif) et d’investissement (proactif) qui est à la base de la formulation, les phases d’implantation et d’évaluation de même que le rôle des acteurs sont abordés. Dans le deuxième cas, différentes typologies de stratégies des ressources humaines sont présentées, et celle de Bamberger et Meshoulam est explicitée, sous l’angle notamment des modèles favorisant l’investissement dans le capital humain (stratégies d’internalisation) et des modèles favorisant la flexibilité (stratégies d’externalisation).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 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".