Long Term Educational Attainment of Private High School Students in Québec: Estimates of Treatment Effects from Longitudinal Data
Bibliographic record
Abstract
(in French) Peu d'études peuvent évaluer les effets de long terme de l'école privée secondaire sur les résultats éducatifs des élèves, tout en contrôlant pour les caractéristiques des élèves et des parents. Au Québec, la deuxième province canadienne la plus populeuse, plus de vingt pourcent des élèves du secondaire fréquentent les écoles privées subventionnées par l'État, mais avec frais de scolarité plafonnés. Les biais de sélection, de causalité et de recrutement causés par la possibilité pour l'école privée de sélectionner les élèves rendent toutefois inappropriée une comparaison simpliste de leurs résultats éducatifs par rapport à leurs pairs du secteur public. Cette étude utilise les quatre premiers cycles de deux cohortes longitudinales de l'Enquête sur les jeunes en transition (EJET) réalisée par Statistique Canada. Elle estime l'effet de traitement de l'école privée sur le taux de graduation du secondaire selon le temps attendu, la fréquentation d'un CEGEP à 19 ans, la fréquentation de l'université à 21 ans ou plus, la graduation universitaire à partir de 24 ans ou plus ainsi que l'inscription aux programmes menant à des professions régies par des ordres professionnels au Québec. L'analyse économétrique estime les effets de traitement selon l'appariement par balancement entropique prenant en considération plusieurs variables clés dont le statut socioéconomique des élèves. Les résultats sont ensuite validés par une simulation de variable confondante. Les effets significatifs et robustes estimés attribuables à l'école privée expliquent plus de 56 de l'écart observé entre les élèves par les données (administratives ou descriptives de l'EJET), et près de 81 pourcent selon le modèle, la cohorte et le sexe. Abstract (in English, working paper is in French. See GRCH WP16-02 for English.) Very few studies analyze the long term educational effects of private secondary school students while controlling for their socioeconomic status. In Quebec, the second most populous Canadian province, twenty percent of students at this level are enrolled in private schools subsidized by the government, who however set a relatively low ceiling for the fees in exchange for subsidies. Bias from selection, causality and admission coming from the fact that private schools may select their students, give way to inappropriate simplistic comparison of their educational results with their public sector peers. This study uses the first four longitudinal waves on the two cohorts of Statistics Canada's Youth in Transition Survey (YITS). The analysis estimates the average treatment on the treated the effect of private school on secondary school graduation rate within expected number of years (5), enrollment in postsecondary institutions at age 19, university enrollment at age 21 or more, university graduation at age 24 or more, and enrollment in professional degrees program. The econometric analysis of treatment effects is based on a particular entropy balancing algorithm with a large set of key balancing covariates. Results are validated by a simulation-based sensitivity analysis for matching estimators. We find large, positive and statistically significant effects of private schooling on almost all outcomes analyzed. The results are not sensitive to simulations of omitted variable bias.
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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 | 0.012 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".