School Resources and the Academic Achievement of Canadian Students
Bibliographic record
Abstract
This study estimates the impact of schools’ physical resources and teachers’ academic press on students’ academic achievement in mathematics and reading when a number of important student variables are controlled. Academic press is defined as teachers' emphasis on academic excellence and upholding academic standards (McDill, Natriello, &; Pallas, 1986). It is often argued that both school and teacher resources affect the educational achievement of students. But, the research literature has been inconsistent, which may be due to methodological issues. For this reason, this study attempts to correct two of the most important issues by using Canadian national data and multi-level modeling. The results reveal that, in Canada, at least, the physical resources and academic press evaluated by school principals do not significantly affect students’ achievement in mathematics and reading. Cette étude évalue l’impact des ressources physiques des écoles et la rigueur académique des enseignants sur le rendement académique des élèves en mathématiques et en lecture lorsqu’on contrôle un certain nombre de variables importants chez les élèves. On définit la rigueur académique comme l’importance que les enseignants accordent à l’excellence académique et le maintien de normes académiques (McDill, Natriello, &; Pallas, 1986). On soutient souvent que tant les ressources de l’école que celles des enseignants jouent un rôle dans le rendement académique des élèves. Les publications de recherche, par contre, sont contradictoires, peut-être en raison de problèmes méthodologiques. Cette étude tente donc de rectifier deux des problèmes les plus importants en employant des données nationales canadiennes et le modelage multiniveau. Les résultats indiquent qu’au Canada du moins, les ressources physiques et la rigueur académique telles qu’évaluées par les directeurs d’école n’affectent pas de façon significative le rendement des élèves en mathématiques et en lecture.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".