Le ministère du Travail, la Régie Renault et le contrôle des salaires (1944-1947)
Bibliographic record
Abstract
Le ministre du Travail, dans les années qui suivent la Libération, se retrouve en charge d’une tâche étonnante : déterminer, pour toutes les entreprises de tous les secteurs, les salaires minima mais aussi maxima. À partir de l’exemple de la Régie Renault, et notamment des archives de son PDG, l’article fait ressortir les grands enjeux et contradictions qu’a posés cette législation, dans un contexte d’intense pénurie de main-d’œuvre et de baisse du pouvoir d’achat. Le PDG de la Régie Renault s’est ainsi trouvé confronté à un dilemme entre l’intérêt collectif d’une part – respecter la loi et ainsi aider le gouvernement dans sa tâche de reconstruction – et l’intérêt individuel d’autre part – augmenter lui aussi les salaires pour faire face à ses confrères qui n’hésitent pas à contourner la législation en vigueur afin de débaucher son personnel qualifié.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".