Le cas français : approfondir les connaissances empiriques pour mieux cibler la formation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
L’article aborde la stratégie de l’OCDE en matière de formation. L’OCDE plaide en faveur d’une accumulation continue de capital humain et ses recommandations tendent à renforcer les incitations des entreprises et des individus à investir dans le capital humain. Si les chiffres confortent l’analyse de l’OCDE concernant l’inégalité d’accès à la formation, c’est moins vrai concernant l’efficacité des politiques de formation elles-mêmes. L’article pose la question essentielle de l’évaluation des dispositifs de formation comme instrument de lutte contre le chômage de longue durée, pour laquelle les auteurs estiment qu’on ne dispose pas d’informations de qualité permettant d’apprécier l’effet des formations sur les parcours professionnels.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it