Winning and Re-Winning: Recommendations for Inclusive Education Reform for Students Labelled as Disabled in Alberta’s Schools
Bibliographic record
Abstract
Alberta Education has been engaged in reviews and reforms of special education, and attempting to describe and move toward more inclusive ways of supporting students with disabilities since 2008. These efforts have, at times, resulted in the production of more progressive inclusive education policies and, at times, seemed somewhat halting. The obstacle to realizing policies that are more consistently inclusive, the authors believe, has been a continuing tendency toward deficit understandings of disability. In this paper, the authors critique recent inclusive education reform and current policy documents in light of ongoing barriers to inclusion, both in practices in schools and in continuing deficit-based tendencies in some current policy statements and resource manuals. The authors conclude by making a series of recommendations, including a consideration of the activist discipline of Disability Studies in Education, to guide continuing reform efforts along more genuinely inclusive lines.
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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 | 0.035 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.024 | 0.014 |
| Scholarly communication | 0.034 | 0.012 |
| Open science | 0.013 | 0.018 |
| Research integrity | 0.034 | 0.020 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".