Creating Alternative and Demedicalized Spaces: Testimonial Narrative on Disability, Culture, and Racialization
Bibliographic record
Abstract
The literature on disability, gender and “race” has benefited from the political economy perspective. With its emphasis on unmasking the workings of power, this perspective has brought into relief the systemic, institutionalized and spatial oppression of disabled persons, compounded in the case of gender and “race.” This narrative of deconstruction, however, remains incomplete in the absence of voice and subjectivity of persons with disabilities. Using narrative moments, recounted by an immigrant woman with two “disabled” children, this paper makes a case for an integrated framework for a study of racialized persons with disabilities. Here, the margins2 are not out there in other spaces; they form part of the centre whose existence is brought into question by alternative and demedicalized spaces. The data are drawn from a larger study of health and well being of South Asian East African women in metropolitan Vancouver, Canada.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.022 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| 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".