“I Paid No Attention To It”: An Oral History of Curricular Change in the 1930s
Bibliographic record
Abstract
AbstractIn 1937 the Ontario Department of Education introduced unprecedented changes to the curriculumand pedagogy of the elementary schools of the province through the publication anddistribution of the document Programme of Studies for Grades 1 to VI of the Public andSeparate Schools. By exploring the oral history of twenty-one teachers who taught in the elementaryschools of Ontario during the 1930s, this article will explain how teachers understoodand experienced the pedagogical and curricular changes introduced in 1937. Juxtaposingthe oral history of teachers with the evidence of documentary sources will provide a means ofcreating a more nuanced account of the unprecedented reforms that were attempted in 1930sOntario.RésuméEn 1937, avec la parution du Programme d’études pour les écoles publiques et séparées de l’Ontario,le Département de l’éducation apporta des changements sans précédent au programmed’études de la 1ère à la 6e année et à la pédagogie en vigueur dans les écoles élémentaires de laprovince. C’est à partir de témoignages recueillis auprès de 21 personnes ayant enseigné à ceniveau durant les années 1930 que nous analysons la réaction des enseignants face à ces changementsintroduits cette année-là. La comparaison de ces entretiens avec les sources documentairespermettra de nuancer davantage les résultats de ces réformes sans précédent entreprisesen Ontario à cette époque.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.018 | 0.024 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".