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Record W4382520184 · doi:10.33137/cpep.v1i1.40262

Moving the Needle on Ableism: From Higher Education Access to Inclusion

2023· article· en· W4382520184 on OpenAlexaffabout
Erin Anderson

Bibliographic record

VenueCritical Perspectives in Education & Policy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInclusion (mineral)AbleismCharterIdentity (music)LegislationFace (sociological concept)Public relationsDisadvantagedSociologyInstitutionDisability studiesIntersectionalityPolitical scienceGender studiesLawSocial science

Abstract

fetched live from OpenAlex

Legislation in recent decades, such as the Canadian Charter of Rights and Freedom (1982) and the Ontario Human Rights Code (1962), have increased access to postsecondary education for diverse student populations; however, many students still face identity-based marginalization. While safety and inclusion are presented as foundational for learning, the experiences of disabled students suggest a hostile environment where access does not equate to a sense of belonging and safety may not even be guaranteed. As students’ sense of belonging impacts their willingness to get involved at their institution, inclusion is critical to the success outcomes of students with disabilities. I argue that meaningful inclusion requires universal access and intentional opportunities for participation by people who are historically excluded on the basis of disability and other intersectional identities, which must be preceded by increased awareness of the issues facing these students and collaboration among institutional actors to address them.

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)0.014
metaresearch head score (Gemma)0.015
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0170.120
Scholarly communication0.0230.028
Open science0.0020.033
Research integrity0.0100.016
Insufficient payload (model declined to judge)0.0070.001

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 head0.084
GPT teacher head0.488
Teacher spread0.404 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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