School market and the democratization of education: one step forward, two steps back. The case of the Canadian Province of Quebec
Bibliographic record
Abstract
The purpose of this article is to show that since the 1980s, educational inequalities in Quebec have gradually been reconfigured through the school market. The results obtained from a sample (N = 24,085) of a cohort of students who entered their first year of secondary school in 2002–2003 and who were observed for up to ten years (2012–2013) show that the influence of social origin on educational inequalities operates in large part via mediation of the type of institution attended. The results indicate that enrollment in selective schools, whether public or private, is closely associated to the social characteristics of the students: socioeconomic and ethnocultural origin, gender and mother tongue. In addition, there is a strong association between attendance at these same institutions, access to higher education and graduation. We conclude that the persistence of the reproduction of social inequalities in education is the result of the interactive and combined effects of social power relations related to class and ethnicity, and the current organization of public policies in education. This reveals a paradox as school markets have been promoted by public policies in the name of strengthening democratization and improving the quality of education.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".