A pan-Canadian research program for more inclusive schools in Canada: The diversity and equity research background
Bibliographic record
Abstract
This discussion paper presents four research questions as possible priorities for all partners in Canada. These questions reflect the interests and priorities already identified by respondents from provincial/territorial ministries and departments. The paper reviews the research that has already been done under each of the four theme areas, providing sub-headings that suggest the range of key issues. Discussion highlights omissions, new directions, and strengths and weaknesses in the assembled research in Canada. Question one asks if a pan-Canadian research program could help describe different, effective approaches to Aboriginal-controlled schooling that other Aboriginal communities could learn from. Major sub-headings include: issues of Aboriginal control; policies for language and cultural revival; and Aboriginal teacher education. Further related issues are raised under questions two and three. Question two asks if a pan-Canadian research program could help ministries and departments ease the integration difficulties presently experienced by culturally different children in school systems. Major sub-headings here include: fair assessment of student ability and achievement; English-as-a-second-language/French-as-a-second-language (ESL/FSL) versus bilingual education provisions; problems of bias in textbooks and in classroom discourse; bias against non-standard language varieties; and racial bias. Question three asks if a pan-Canadian research program could help reduce disparities in access to academic literacy among different social, cultural, and regional groups. It reviews the limited survey data available, and the few contextual studies in Canada on literacy and illiteracy.
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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 | 0.022 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.033 | 0.006 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".