Le rendement privé et social de l’éducation universitaire au Québec en 2015
Bibliographic record
Abstract
This study calculates for Québec the private and social rates of return to university education by various levels and fields of study using 2016 Canadian Census data. The main results are presented in Tables R1, R 2 and Figure R1. Table R1 indicates that: I. The social return is always lower than the private return because part of the total cost of a university education is borne by society. II. Rates of return decrease with growth in education level (MD excepted). III. Rates of return are higher for women than for men. Table R2 indicates that the rates of return vary greatly by field of study and are generally higher in scientific fields at the undergraduate level. Figure R1 shows that undergraduate university studies paid a lot in Quebec in 2000, 005, 2010 and 2015. The rates of return for 2015 differ from those in table 1 to allow intertemporal comparability. We also find that for 2015: university education is often better remunerated in the public than in the private sector; an increase in the share of workers with a university degree in STEM increases the earnings of non STEM workers in Canadian CMAs. Cette étude calcule pour le Québec les taux de rendement, privés et sociaux, d’une scolarité universitaire de divers niveaux et domaines avec les données du Recensement canadien de 2016. Les résultats principaux sont présentés aux tableaux R1, R2 et à la figure R1. Le tableau R1 indique que : Le rendement social est toujours plus faible que le rendement privé car une partie du coût total d’une formation universitaire est supportée par la société. Les taux de rendement diminuent avec la croissance du niveau de scolarité (MD excepté). Les taux de rendement sont plus élevés pour les femmes que pour les hommes. Le tableau R2 indique que les taux de rendement varient fortement selon le domaine d’études au niveau du baccalauréat et sont généralement plus élevés dans les domaines scientifiques. La figure R1 indique que les études universitaires du 1er cycle sont fort payantes au Québec en 2000, 2005, 2010 et 2015.Les taux de rendement pour 2015 diffèrent de ceux du tableau 1pour fin de comparabilité inter-temporelle. On constate également que pour 2015 : l'enseignement universitaire est souvent mieux rémunéré dans le secteur public que dans le secteur privé ; une augmentation de la proportion de travailleurs détenant un diplôme universitaire en STIM augmente les gains des travailleurs non STIM dans les RMR canadiennes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".