A test for geographers: the geography of educational achievement in Toronto and Hamilton, 1997
Bibliographic record
Abstract
The recent introduction of standardised achievement tests in several provinces has created an opportunity for Canadian geographers to contribute to public and theoretical debates. Geographers are well‐equipped to comprehend and analyse the effects that neighbourhoods have upon pupil achievement. Independent of family background and school funding, such effects may be stronger in education than in other fields, such as voting behaviour and health research, but they have been ignored in recent public debates. They should be considered if informed judgements are to be made about whether specific teachers, schools, and boards are doing an adequate job. Analysis of the Ontario Grade 3 test results for 1997 in public schools in the City of Toronto and in Hamilton‐Wentworth indicate that social class had a greater effect on pupil achievement than language background. Differences in the determinants of achievement between these two urban centres may be attributable to local variations in occupational structure and residential patterns. L'introduction récente en éducation des tests de compêtences standardisés, dans plusieurs provinces, offre aux géographes canadiens l'occasion de contribuer aux débats publics et théoriques. Les géographes sont bien placés pour comprendre et analyser les effets de quartier sur le rendement scolaire des élèves. Indépendamment du milieu socioculturel et du financement scolaire, ces effets ont peut être plus d'impact en éducation que dans les domaines tels que le comportement électoral et la recherche dans le milieu de la santé, cependant, ils demeurent à l'écart des débats publics. Ces éléments doivent être considérés si l'on prétend juger en connaissance de cause l'efficacité et le rendement des écoles, le corps enseignant et les conseils scolaires. L'analyse des résultats d'examens de l'Ontario en 1997, pour les élèves des écoles publiques de la troisième année des villes de Toronto et Hamilton‐Wentworth, démontre que la réussite scolaire est plus liée au niveau socio‐économique qu'à l'origine linguistique. La divergence des facteurs de réussites des deux centres urbains est peut‐être attribuable aux variations des structures d'occupation locales et résidentielles.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".