Le régime canadien d’assurance-emploi sur la voie de la modernisation. Pour qui et comment ?
Bibliographic record
Abstract
Le gouvernement canadien, responsable de la Loi sur l'assurance-emploi 1 , a engag en 2022 une consultation destine la modernisation de celle-ci 2 . Ceci n'est pas un hasard. Les mesures successives d'allgement des conditions d'accs aux bnfices en temps de Covid (mars 2020 -septembre 2022) 3 ont rvl avec fracas les problmes d'un rgime qui exclut 4 plus qu'il n'inclut en temps de paix sanitaire. Quelles sont les lignes de force issues de cette consultation en vue d'une rforme qui demeure ce jour un vague projet port par un gouvernement libral minoritaire ? Les lignes qui suivent tentent d'esquisser grands traits une approche thmatique qui rvle, d'une part, les inadquations entre les exigences de la loi et les ralits du march du travail, et d'autre part, les tensions idologiques qui traversent les discussions. Ces discussions sont prcdes d'un trs bref rappel de l'architecture gnrale du rgime canadien d'assurance-emploi (LAE).
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 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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".