Terms of <i>Dis</i> appropriation: Disability, Diaspora and Dionne Brand's <i>What We All Long For</i>
Bibliographic record
Abstract
The article brings together the minority discourses of disability and diaspora. Their shared spaces, histories and narratives—although not always welcome—warrant greater examination. Various moments of diaspora discourse are visited (from Stuart Hall, Robin Cohen, and others) to illustrate how disappropriation of pejorative representations and terms of disability complicate and create theoretical reconsiderations for disabled/diasporic thought in contexts of race, gender, class, trauma, and performance. Although language itself often creates inadequacies through its own terms—especially in the context of expressing inexpressible atrocities—can words accommodate expression without relying on the worn out prosthetics of disability for cachet? The article also explores the treatment of madness and the limp in Canadian author Dionne Brand's transitional text What We All Long For (2005), where diaspora appears in marked terms, connected to the mind and body—informing and troubling characters and experiences....
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.043 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".