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Record W2526223896 · doi:10.1111/jir.12311

Community participation of youth with intellectual disability and autism spectrum disorder

2016· article· en· W2526223896 on OpenAlexafffund
Ami Tint, Andrea Maughan, Jonathan A. Weiss

Bibliographic record

VenueJournal of Intellectual Disability Research · 2016
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsYork University
FundersCanadian Institutes of Health Research
KeywordsAutism spectrum disorderIntellectual disabilityPsychologyAutismIntervention (counseling)Diversity (politics)Social engagementClinical psychologyDevelopmental psychologyPsychiatryPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Community participation is associated with a range of positive developmental outcomes; however, the frequency, depth and resources associated with participation for youth with intellectual disability (ID) and autism spectrum disorder (ASD) are not well understood. METHOD: Caregivers of 212 youth with ASD and ID and only ID, aged 11-22 years, completed an online survey. Comparisons were made of caregiver reports of diversity and frequency of participation, levels of participation involvement and related environmental barriers and supports. RESULTS: The diversity and frequency of community participation of youth with ASD and ID approximated that of youth with ID only. Youth with ASD and ID were reported to be significantly less involved in the community activities in which they participated. Environmental features, and in particular, the social demands of community-based activities, were significant barriers to youths' participation. CONCLUSIONS: The current study highlights individual and environmental factors amenable to intervention that may foster successful community participation among youth with ASD and ID.

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.002
Research integrity0.0000.000
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 head0.141
GPT teacher head0.386
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 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

Citations59
Published2016
Admission routes2
Has abstractyes

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