MétaCan
Menu
Back to cohort
Record W614363412 · doi:10.5860/choice.48-4551

Deaf and disability studies: interdisciplinary perspectives

2011· article· en· W614363412 on OpenAlexaboutno aff

Bibliographic record

VenueChoice Reviews Online · 2011
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyPsychologyLinguisticsEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0120.012
Science and technology studies0.0210.054
Scholarly communication0.0280.021
Open science0.0020.020
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.288
GPT teacher head0.490
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations72
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueChoice Reviews OnlineSame topicHearing Impairment and CommunicationFrench-language works237,207