Teacher Collaborative Inquiry in Ontario Elementary Schools: An Analysis of Provincial and School Board Policies and Support Documents.
Bibliographic record
Abstract
Collaborative i nquiry (CI) has emerged as a dominant structure for educators’ professional learning in the 21st century. The purpose of this paper is to analyze publicly available documents and policies related to CI in Ontario in order to better understand the documentary scope and spread of this professional learning model in the province. We begin by defining the parameters of CI as a dominant professional learning model before detailing our methodology for selecting and analyzing CI policies and documents at both ministry and school board levels. In our subsequent analysis, we enumerate emergent themes and findings and offer three sample case studies that illustrate how school boards in the province are documenting their experiences with CI. Finally, we conclude with a discussion of potential tensions within current CI policies as a basis for future research and policy development.
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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 | 0.017 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.015 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".