Suréducation et salaire au Canada
Bibliographic record
Abstract
Cette étude analyse la relation existante entre la suréducation et le salaire au Canada. Les travailleurs suréduqués sont définis comme ceux qui ont un niveau d’éducation supérieur à la moyenne requise pour leurs professions. Nous utilisons un riche ensemble des données provenant de l’Enquête sur la population active du Canada de décembre 2022 pour offrir une image actualisée de la situation. Nous fournissons des estimations systématisées des pénalités salariales dues à la suréducation en utilisant les estimations des moindres carrés ordinaires. Nos résultats montrent une corrélation négative et statistiquement significative entre la suréducation et le salaire. L’intensité de cette relation varie considérablement selon le niveau d’éducation des travailleurs, étant beaucoup plus intense chez ceux détenant un diplôme postsecondaire comparé aux universitaires. Il apparaît que le niveau d’éducation, l’âge, le statut matrimonial et l’immigration sont des déterminants de la suréducation au Canada. _____________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : suréducation, éducation, pénalités, moindres carrés ordinaires, Canada
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".