Bibliographic record
Abstract
Plusieurs raisons peuvent expliquer les difficultés que rencontrent certains groupes désavantagés à entrer sur le marché du travail : Faible scolarité, intégration sociale chancelante, etc. Récemment, certains gouvernements ont adopté des programmes de subventions directes sur les salaires des individus qui retournent sur le marché du travail. Ceux-ci peuvent inciter au travail et permettre l'acquisition d'habiletés qui augmentent la valeur des travailleurs auprès des employeurs. C'est dans cette optique que le programme Action emploi a été instauré par le gouvernement du Québec. Il consistait en un supplément temporaire au revenu pour les assistés sociaux de longue durée qui parvenaient à trouver un emploi. Le Regression Discontinuity Design, qui réduit le biais de sélection, est utilisé pour en tester l'efficacité. Les résultats confirment l'efficacité du programme, qui augmente significativement le niveau d'emploi de la population visée. Les femmes et les ménages monoparentaux sont ceux qui réagissent le plus au programme.
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 | 0.013 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".