Stratégies d'emploi et de compétences au Canada
Bibliographic record
Abstract
Ce rapport se fonde sur l’analyse de données infranationales et sur la consultation de parties prenantes locales dans quatre régions d’étude et deux provinces. Il établit un cadre de comparaison permettant d’appréhender le rôle de l’échelon local en faveur d’emplois plus nombreux et de meilleure qualité. Il pourra aider les responsables des politiques fédérales, provinciales et locales au Canada à bâtir au niveau local des partenariats efficaces et pérennes, porteurs de synergies et de résultats plus solides du point de vue des mesures prises pour l’emploi, la formation et le développement économique. Des politiques coordonnées peuvent aider les travailleurs à trouver l’emploi qui leur convient tout en stimulant l’entrepreneuriat et la productivité, et aboutir ainsi à une meilleure qualité de vie et à plus de prospérité aussi bien au niveau local que, globalement, dans le pays.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.007 |
| 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".