Special Education in Ontario, Canada: A case study of market-based reforms
Bibliographic record
Abstract
In 1995 the Government of Ontario commenced educational reforms that have broad implications for students with special educational needs. The reforms reflect governmental shifts in defining education in terms of economic accountability and market-driven demand and away from concerns for social justice. Five principles of educational reform under market-driven policies are drawn from the literature; diversification and decentralisation (distributing responsibility for implementation, decision making and funding and outsourcing tasks), contestability (competition for resources), prescription/surveillance (through standards-based reform) and accountability to parents. The special education reform initiatives in Ontario are analysed to see how and to what extent they reflect these principles. The results are then compared with the ways in which the principles have played out in other jurisdictions which have longer histories of implementing economics-based models, notably England and Wales, the USA and New Zealand. The purpose of the comparison is to see what difficulties have arisen from the experiences of others which might be anticipated in the case of the Ontario reforms.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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 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".