Deaf and disability studies: interdisciplinary perspectives
Bibliographic record
Abstract
This collection presents 14 essays by renowned scholars on people, Deafhood, histories, and identity, but from different points of view on the Deaf/Disability compass. Editors Susan Burch and Alison Kafer have divided these works around three themes. The first, Identities and Locations, explores identity in different contexts. Topics range from a history of activism shaped by the ableism of elites in the United States from 18801920, to a discussion of the roles that economics, location, race, and culture play in the experiences of a woman from northern Nigeria now living in Washington, D.C. Alliances and Activism showcases activism organized across differences. Studies include a feminist analysis of how deaf and hearing women working together share responsibility, and an examination of how intra-cultural variations in New York City and Quebec affect deaf-focus HIV/AIDS programs. The third theme, Boundaries and Overlaps, explicitly addresses the relationships between Studies and Disability Studies. Interviews with scholars from both disciplines help define these relationships. Another contributor calls for hearing/not-deaf people with disabilities to support their peers in gaining langue access to the United Nations. Deaf and Disability Studies: Interdisciplinary Perspectives reveals that different questions often lead to contrary conclusions among their authors, who still recognize that they all have a stake in this partnership.
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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 | 0.020 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.021 | 0.054 |
| Scholarly communication | 0.028 | 0.021 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".