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Record W4407135103 · doi:10.1386/jaac_00069_1

‘Stories of Access’: Tangled Art + Disability and cultural accessibility in action

2024· article· en· W4407135103 on OpenAlexaffabout
Eliza Chandler, Megan Johnson

Bibliographic record

VenueJournal of Arts & Communities · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsDalhousie UniversityToronto Metropolitan University
Fundersnot available
KeywordsAction (physics)Gender studiesSociologyAestheticsPsychologyArt

Abstract

fetched live from OpenAlex

In this article we engage a transdisciplinary perspective to analyse cultural accessibility practices, which are access practices developed by disabled people for the cultural field. Cultural accessibility seeks to disrupt normative culture by creating flexible practices that centre disabled people and disability community. Drawing on research with Tangled Art + Disability, a disability art gallery in Toronto, Canada, we explore the iterative and collaborative processes through which the organization has developed cultural accessibility practices. We narrate the provenance of these practices through ‘Stories of Access’ that illustrate how the context of the gallery – including artists, staff, audiences, resources, technologies, materials, spaces, policies and access commitments – influenced their development. Throughout, we demonstrate how thinking about practices of cultural accessibility as themselves transdisciplinary allows us to track more nuanced origin stories as embedded in institutional history, crip wisdom and practices and organizational specificity and resist the ways that access is taken up as a non-relational 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 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)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0180.076
Scholarly communication0.0140.012
Open science0.0020.021
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.194
GPT teacher head0.463
Teacher spread0.269 · 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 designQualitative
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

Citations0
Published2024
Admission routes2
Has abstractyes

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