The Organizational and Electoral Determinants of the Provincial Funding of Private Education in Canada: A Quantile Regression Analysis
Bibliographic record
Abstract
Abstract. Several Canadian provinces partially fund private education through statistical formulas. This article draws on various studies in the area of political economy in order to link provincial educational grants to factors not explicitly comprised in the formulas. More specifically, organizational and electoral variables are expected to have an impact on the amount of provincial grants received by private school authorities. Quantile regression analysis shows that Catholic and Protestant private schools are somewhat favoured by the existing system of grants. Likewise, membership in the main provincial interest group and electoral competition are beneficial to private school authorities. Résumé. Plusieurs provinces canadiennes financent partiellement l'éducation privée. Le montant de ce financement est déterminé au moyen d'une formule statistique. Cet article se base sur divers travaux d'économie politique afin de relier les subventions publiques allouées à l'éducation privée à des facteurs non inclus dans les formules. Plus précisément, nous nous attendons à observer un impact significatif de variables organisationnelles et électorales. L'analyse de régression quantile montre que les écoles privées catholiques et protestantes de même que les écoles privées membres de l'association provinciale de représentation des intérêts sont avantagées du point de vue de la subvention et que la compétitivité électorale est positivement et significativement liée au montant de subventions reçues par les autorités scolaires privées.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".