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Record W3206016709 · doi:10.15353/cjds.v10i2.784

Reverberation! A New Wave in Disability Art

2021· article· en· W3206016709 on OpenAlexvenueno aff
Maggie Bridger, Sydney Erlikh, Chun-shan Yi

Bibliographic record

VenueCanadian Journal of Disability Studies · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsAbleismDisability studiesScholarshipSociologyThe artsMainstreamField (mathematics)Diversity (politics)AestheticsVisual artsGender studiesArtPolitical scienceLawAnthropology

Abstract

fetched live from OpenAlex


 
 
 Graduate student scholar/artists Sydney Erlikh, Maggie Bridger, and Sandie Yi reflect on their experiences of having attended VIBE: Challenging Ableism and Audism Through the Arts. The three were struck by the diversity and range of unique experiences reflected in the work of the presenting artists. Each author takes the lead on one of three themes they collectively identified: what constitutes disability art, how community shapes artistic and scholarly practice, and how boundaries of the field are evolving. The article explores the ways in which disabled artists are defining creative processes and aesthetic approaches outside of the mainstream art world and its ableist productivity demands. They also take note of how artists with non- apparent disabilities are actively moving the field in new directions. Finally, they examine the ethical dimensions of artistic “ownership” in the collaboration between artists with and without disabilities, particularly around those with intellectual disabilities and their allies. The authors ultimately offer a description of a new wave of disability art that is pushing the field to think through questions of process, collaboration, ethics, visibility, creative scholarship, and relationship to disability studies. This new work, they argue, is creating space for a more sustainable, community-based practice.
 
 

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.129
GPT teacher head0.314
Teacher spread0.185 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2021
Admission routes1
Has abstractyes

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