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Record W4391161838 · doi:10.1162/leon_a_02502

Resisting Normality with Cultural Accessibility and Slow Technology

2024· article· en· W4391161838 on OpenAlexaff
Megan Johnson, Eliza Chandler, Carla Rice

Bibliographic record

VenueLeonardo · 2024
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsEli Lilly (Canada)University of Guelph
Fundersnot available
KeywordsNormalitySociologyPsychologyComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

Abstract Although the COVID-19 virus continues to circulate, there is an increasing insistence that the world “return to normal.” In this paper the authors resist this pull to normalcy and the way it devalues the knowledges, vitality, and livelihoods of disabled people. They examine the crip technoscience practices used during the 2022 digital gathering Practicing the Social: Entanglements of Art and Social Justice, situating them as examples of cultural accessibility that engage with slow technology to provoke crip(ped) ways of being in time. They argue that sustained engagement with cultural accessibility offers a different path through the pandemic, one that centers access and resists the way necropolitics devalues disabled life.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.044
Scholarly communication0.0110.007
Open science0.0010.020
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.294
Teacher spread0.279 · 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 designTheoretical or conceptual
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

Citations7
Published2024
Admission routes1
Has abstractyes

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