MétaCan
Menu
Back to cohort
Record W3199768585 · doi:10.1177/10778004211046249

Mobilizing Interference as Methodology and Metaphor in Disability Arts Inquiry

2021· article· en· W3199768585 on OpenAlexaff
Carla Rice, K. Alysse Bailey, Katie Cook

Bibliographic record

VenueQualitative Inquiry · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsWilfrid Laurier UniversityUniversity of Guelph
Fundersnot available
KeywordsMetaphorRealmSociologyDisability studiesAbleismAestheticsAgency (philosophy)The artsGazeAutoethnographyEpistemologyPsychologyVisual artsGender studiesSocial sciencePsychoanalysisPolitical scienceLinguisticsArt

Abstract

fetched live from OpenAlex

This article interrogates the limits and possibilities of interference as methodology and metaphor in video-based research aiming to disrupt ableist understandings of disability that create barriers to health care. We explore the overlapping terrain of diffractive and interference methodologies, teasing apart the metaphorical-material uses and implications of interference for video-makers in our project. Using the digital/multimedia stories created and an interview as research artifacts, we illuminate how interference manifested in disabled makers’ lives, how interference operated through the research apparatus, and how the videos continue to hold agency through their durability in the virtual realm. Drawing on feminist post-philosophies of matter (Barad) and use (Ahmed), we argue that the videos disrupt the gaze that fetishizes disabled bodies, thereby interfering with cultural-clinical processes that abnormalize disability. The research apparatus interfered with makers’ subjectivities yet also brought people together to generate something new—a community that creates culture and contests its positioning as marginal.

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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.460
GPT teacher head0.558
Teacher spread0.098 · 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 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

Citations11
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueQualitative InquirySame topicDisability Rights and RepresentationFrench-language works237,207