MétaCan
Menu
Back to cohort
Record W3081940340

Ableism in the Academy: A Series About Disability Oppression and Resistance in Higher Education

2020· article· en· W3081940340 on OpenAlexvenueno aff
Steven Singer, Jessica Bacon

Bibliographic record

VenueCritical education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsnot available
Fundersnot available
KeywordsAbleismCognitive reframingOppressionPerspective (graphical)Disability studiesResistance (ecology)SociologyPedagogyPsychologyGender studiesSocial psychologyLawPolitical sciencePolitics
DOInot available

Abstract

fetched live from OpenAlex

This special series offers the readers of Critical Education groundbreaking work by scholars who explore a myriad of issues related to how ableism manifests and is resisted in higher education. Ableism is defined as the idea that able-bodiedness/mindedness is a preferred way of being in society. In this series introduction we, the editors, recount our own orientations to the themes that are brought forth in the special issue. Subsequently, we synthesize the innovative themes that have emerged in the eight manuscripts that are a part of this special issue, including: 1) Asking: from whose perspective should we learn about disability experiences in higher education?; 2) Describing the critically-oriented theoretical perspective employed across the manuscripts, all of which align to a disability studies perspective; 3) Questioning who is invited to participate and thrive in the academy; and 4) Exploring tactics used to create change and breakdown ableist structures that persist in the academy. Ultimately, we feel the implications of the work undertaken by the authors in this special issue are far-reaching and encourage the increased citizenry of disabled people, elevate the social positioning of disabled people in higher education settings, and ultimately reframe what it means to be labeled as disabled.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.668
Threshold uncertainty score0.311

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.078
GPT teacher head0.424
Teacher spread0.346 · 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 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

Citations12
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCritical educationSame topicDisability Rights and RepresentationFrench-language works237,207