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Record W4410869354 · doi:10.1177/17446295251344355

Belonging involves mutuality, agency, and acceptance: An ethnographic exploration of belonging with adults labelled with intellectual disability

2025· article· en· W4410869354 on OpenAlexafffundabout
Paige Reeves, David McConnell, Shanon Phelan

Bibliographic record

VenueJournal of Intellectual Disabilities · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsDalhousie UniversityUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Alberta
KeywordsAgency (philosophy)Intellectual disabilityEthnographyDiversity (politics)SociologyParticipatory action researchInclusion (mineral)Sense of agencyPsychologySocial psychologyGender studiesSocial science

Abstract

fetched live from OpenAlex

An experience of belonging is commonly absent in the lives of adults labelled with intellectual disability, negatively impacting health, well-being, and quality of life. This ethnographic study, informed by critical disability and feminist relational theory, explored the belonging experiences of five adults labelled with intellectual disability in a Canadian city. Using participatory methods, the research identified mutuality, agency, and acceptance as key factors shaping their experiences. Findings emphasize the role of genuine relationships, the connection between agency and belonging, and the need to continue to build community capacity to embrace diversity. Findings call for further research exploring the relationship between belonging, mutuality, agency, and acceptance as one step towards collectively supporting the social inclusion of people labelled with intellectual disability. This work demonstrates how spaces, places, and relationships of belonging identified by people labelled with intellectual disability have generative potential - acting as promising examples of the conditions that enable belonging to flourish.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.006
Scholarly communication0.0000.002
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 head0.037
GPT teacher head0.336
Teacher spread0.299 · 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 routes3
Has abstractyes

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