Taking the "Dis" out of "Disability": How a School's Community of Teachers Works to Empower Students with Disabilities in an Ableist Education System
Bibliographic record
Abstract
In this paper I investigate the perceptions and lived experiences of four teachers and one administrator working at a secondary school in Canada in which all of the students have been institutionally designated with a " disability." Data was collected for this qualitative study through five semi-structured, face-to-face interviews. As I deconstructed and analyzed the lived experiences of the participants I paid particular attention to their perceptions of what makes this school distinctive; how they as educators develop a sense of community and collegiality in their individual classrooms and the broader school; the issues or challenges they encounter supporting the learning and life chances of students; and the curricular and pedagogical choices they make to ensure their students are challenged and successful. Findings of this study reveal that this school and its community of teachers are a source of insight into the mindset and resulting approach to teaching that educators need to adopt in order to empower students with disabilities with the skills and attitudes necessary to succeed in our ableist society, a society that privileges what has been deemed to be 'normal.' The participants' efforts to empower their students illustrate the challenges educators face in eliminating ableism due to disabling language and an educational system constructed through an ideology of deficit. However, the participants also provide a peak, a flavour, an essence of what is possible when we educate to unconver the potential in our students.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.043 | 0.051 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".