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Record W4414122799 · doi:10.3390/disabilities5030078

Inclusion as a Facilitator of Social and Physical Activity for People with Physical Disabilities

2025· article· en· W4414122799 on OpenAlexafffund
Kayla Korolek, Kirsten Ward, Heather Lamb, Christopher B. McBride, Katherine Bailey, Chelsea Pelletier

Bibliographic record

VenueDisabilities · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsSpinal Cord Injury BCUniversity of British ColumbiaUniversity of Northern British Columbia
FundersCanadian Institutes of Health Research
KeywordsFacilitatorInclusion (mineral)Physical activityThematic analysisSocial engagementGeneral partnershipPhysical disabilitySocial relation

Abstract

fetched live from OpenAlex

The aim of this study was to explore the perceived relationship between inclusion and participation in social and physical activities for people with physical disabilities. In partnership with a local disability-focused non-profit organization, we completed semi-structured interviews with 12 individuals with physical disabilities. Interview transcripts were analysed using an inductive thematic approach considering the social–ecological model and quality participation framework for people with disabilities. We developed three themes to describe the relationship between inclusion and participation in social and physical activities: physical accessibility of spaces and places, advocates are needed to share knowledge, and social inclusion and social/physical activities influence each other. Participants discussed the facilitating role of social inclusion on physical and social activities and the bi-directional relationship between inclusion and community participation. Fostering social inclusion through increased accessibility, education, and awareness at the community or program level can facilitate full community participation for people with physical disabilities.

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)0.008
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0070.005
Scholarly communication0.0030.003
Open science0.0010.013
Research integrity0.0010.001
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 head0.020
GPT teacher head0.371
Teacher spread0.351 · 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 designObservational
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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