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Record W2557527097 · doi:10.1080/02660830.2016.1219479

Exhibiting activist disability history in Canada:<i>Out from under</i>as a case study of social movement learning

2016· article· en· W2557527097 on OpenAlexaffabout
Kathryn Church, Danielle Landry, Catherine Frazee, Esther Ignagni, Mitchell Cindy, Melanie Panitch, Jennifer Patterson, Phillips Sandra, Terry Poirier, Karen Yoshida, Jijian Voronka

Bibliographic record

VenueStudies in the Education of Adults · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMovement (music)Social movementSociologyAdult educationGender studiesPsychologyPolitical sciencePedagogyAestheticsPolitics

Abstract

fetched live from OpenAlex

This article introduces the exhibit called Out from Under: Disability, History and Things to Remember and positions it as a focal point for exploring questions of disability, museum exhibition and adult education. Created by the School of Disability Studies at Ryerson University in Toronto, Out from Under was the first public exhibit of disability history in Canada (2007–2014) and the first to be displayed at the prestigious Royal Ontario Museum. With adult education in mind, we unravel some of the strands of teaching and learning woven through this lengthy, creative project. Highlighting a complex blend of actors and forms of knowing, we consider the knowledge activated through exhibit creation as well as a subsequent formal study of visitor responses. We situate the whole project as a robust and rare example of social movement learning through practices that crossed the borders between disability/mad rights movements, an undergraduate programme of Disability Studies and a major Canadian museum.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.053
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.063
GPT teacher head0.377
Teacher spread0.314 · 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.

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

Citations7
Published2016
Admission routes2
Has abstractyes

Explore more

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