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Record W4416746747 · doi:10.3390/disabilities5040109

Experiences of Ableism and Racism Among Racially Minoritized Youth and Young Adults with Disabilities

2025· article· en· W4416746747 on OpenAlexafffund
Sally Lindsay, Peiwen Cao, Nicole Thomson, Jennifer Stinson, Sharon Smile

Bibliographic record

VenueDisabilities · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsUniversity of British ColumbiaHospital for Sick ChildrenGrand River HospitalHolland Bloorview Kids Rehabilitation HospitalToronto Rehabilitation InstituteUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Toronto
KeywordsRacismThematic analysisYoung adultCoping (psychology)Qualitative researchAbleismMental healthIdentity (music)Semi-structured interview

Abstract

fetched live from OpenAlex

Youth with disabilities face persistent disability-related discrimination (ableism) but research frequently overlooks the experiences of racially minoritized youth. The purpose of our study was to explore the experiences and perceived impact of discrimination among racially minoritized youth and young adults with disabilities. This qualitative study involved a sample of 15 youth and young adults with disabilities (mean age 22 years) identifying as racially minoritized. A descriptive inductive thematic analysis was applied to the interview data. Our findings highlighted the following themes: (1) types of discrimination (i.e., cultural and family-related ableism, racist ableism, and gendered/sexist ableism); (2) perceived impact of discrimination (i.e., social isolation, avoidance of unwelcoming and unsafe situations, impact on physical and mental health, decisions about identity disclosure, and a lack of access to resources and opportunities); and (3) positive coping strategies (i.e., inclusive and safe spaces, self-advocacy, and social and family supports).

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0020.001
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.294
Teacher spread0.277 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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