Bibliographic record
Abstract
Toutes les ressources humaines en plus de 300 entrees : les concepts, les sigles, les reglementations indispensables a connaitre. Les politiques et les pratiques de ressources humaines ont profondement evolue au cours des dernieres annees, ce qui a conduit a la creation de nouveaux termes et a l'apparition de nouveaux intervenants et de nouveaux sigles. Cette nouvelle edition enrichie identifie et definit la terminologie actuelle, les nouveaux concepts et presente les termes les plus frequemment utilises dans le champ des ressources humaines, notamment en matieres de droit social, politique de l'emploi, institutions et organismes, organisation du travail, management et strategie, etc. Elle integre egalement quelques termes etrangers (anglais, quebecois, italien ou espagnol), utiles a connaitre. Ce dictionnaire s'adresse aux dirigeants et aux professionnels de la fonction, aux cadres operationnels, aux etudiants en GRH, aux representants du personnel ainsi qu'a l'ensemble des salaries.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.088 | 0.055 |
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".