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Record W4410548897 · doi:10.1111/jar.70070

‘We're Not Really Into Helping, We're Into Being Useful’: Service Provider Practices That Support Belonging Opportunities in the Lives of Adults Labelled With Intellectual Disabilities

2025· article· en· W4410548897 on OpenAlexafffund
Paige Reeves, David McConnell, Shanon Phelan

Bibliographic record

VenueJournal of Applied Research in Intellectual Disabilities · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsDalhousie UniversityUniversity of Alberta
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsReflexivityAutonomyService providerIntellectual disabilityInclusion (mineral)Thematic analysisPublic relationsLearning disabilityEthnographyCitizen journalismService (business)SociologyPsychologySocial psychologyQualitative researchPolitical scienceDevelopmental psychologyBusinessSocial sciencePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Social inclusion focussed on belonging is increasingly emphasised by disability advocates and policymakers, yet belonging often remains absent for adults labelled with intellectual disabilities. People labelled with intellectual disabilities often rely on service providers to support their belonging. METHODS: In this critically informed ethnographic work, we draw on interviews with nine disability services leaders and prolonged participatory field explorations with five adults labelled with intellectual disabilities, their friends and support workers to explore how service providers support opportunities for belonging. RESULTS: Reflexive thematic analysis generated three themes: centering inclusion, belonging and rights; creating opportunities for self-exploration and 'dreaming'; and facilitating connections to people and place. CONCLUSIONS: Findings highlight supporting belonging as complex work that requires a relational understanding of autonomy, work environments that support reflexivity, and the redistribution of resources to allow for higher staff wages, larger individual support contracts and funding for staff training and post-secondary education.

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)0.010
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), 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 score0.088
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.006
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.002
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 head0.169
GPT teacher head0.414
Teacher spread0.245 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

Explore more

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