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Record W4415096879 · doi:10.1111/jar.70123

Co‐Designing Peer Support for Women Labelled With Intellectual Disabilities Who Have Experienced Sexual Violence

2025· article· en· W4415096879 on OpenAlexafffund
Alexis Buettgen, Tammy Bernasky, Kelly MacDougall, Ann Fudge Schormans, Jennifer Gordon, Sandra Tavares, Verónica Schiariti, Robín Masón, Janice Du Mont, Maria Huijbregts

Bibliographic record

VenueJournal of Applied Research in Intellectual Disabilities · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsCoalition for Research in Women's HealthPublic Health OntarioUniversity of TorontoUniversity of VictoriaToronto Rehabilitation InstituteUniversity of WaterlooWomen's College HospitalMcMaster UniversityWomen's and Gender Studies et Recherches FéministesCape Breton UniversityWilfrid Laurier University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIntellectual disabilityPeer supportBridging (networking)Sexual violenceDomestic violencePeer reviewSexual abusePoison controlPeer group

Abstract

fetched live from OpenAlex

BACKGROUND: Women labelled with intellectual disabilities face high rates of social exclusion and sexual violence, with limited research and few services tailored to their needs. Peer support offers many benefits including recognition of diverse lived experiences and nonprofessional perspectives. This article highlights collaborative efforts of women labelled with intellectual disabilities, service providers and researchers in advancing peer support through an applied research project. METHODS: Using trauma-informed, arts-based and human-rights-focused co-design approaches, we fostered inclusive research and programme development in a 3-day virtual symposium. RESULTS: The study emphasises shared control of research agendas, shaped by a multistakeholder team prioritising lived experience knowledge. Women took more control over the research through co-creative practices to that meaningfully included them in the design of future research and programming. CONCLUSION: This inclusive model champions equality and equity, advocating for positive discourse around intellectual disabilities while bridging lived, academic and professional insights in the field.

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)0.009
metaresearch head score (Gemma)0.034
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.009
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.093
GPT teacher head0.428
Teacher spread0.336 · 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.

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

Citations1
Published2025
Admission routes2
Has abstractyes

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