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Record W3135868982 · doi:10.26522/ssj.v15i2.2653

Disability and Deaf Futures (Dispatch)

2021· article· en· W3135868982 on OpenAlexaffvenue
Taeyoon Choi, Aaron Labbe, Annie Segarra, Elizabeth Sweeney, Syrus Marcus Ware

Bibliographic record

VenueStudies in Social Justice · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsYork UniversityMcMaster University
Fundersnot available
KeywordsFutures contractEconomicsBusinessAudiologyFinancial economicsMedicine

Abstract

fetched live from OpenAlex

This dispatch recounts a panel conversation on disability and D/deaf futurity that took place at the Cripping the Arts Symposium.The artists on this panel discuss how they assert disability and D/deaf futurity in the midst of the Anthropocene through their artistic activist practices.By discussing topics such as interdependence, the internet as increasing both community and the privatization of ideas, and how the arts can transform understandings of difference, these artists share their visions for the future.Elizabeth Sweeney: I'm going to start this panel with the words of Stephen Fakiyesi, 1 a Black visual artist based here in Toronto: I think there will always be a need for individuals, groups, and most certainly artists, to imagine the world, not as it is, but as it can be.I do not lament the present order of things, rather, one of the privileges of being an artist on the peripherals, as it were, is that you have the distance to more readily perceive the status quo, and possibly challenge it.I have a pretty active imagination and faith in something greater than myself to think that even now, all things are possible.1 See https://stephenfakiyesi.com

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.368
Threshold uncertainty score0.901

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.000
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.3680.178

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 head0.090
GPT teacher head0.457
Teacher spread0.367 · 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.

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 routes2
Has abstractyes

Explore more

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