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Record W2498119030 · doi:10.1177/1539449216659859

Participation in Out-of-Home Environments for Young Children With and Without Developmental Disabilities

2016· article· en· W2498119030 on OpenAlexafffund
Chun Yi Lim, Mary Law, Mary A. Khetani, Nancy Pollock, Peter Rosenbaum

Bibliographic record

VenueOTJR Occupational Therapy Journal of Research · 2016
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsMcMaster University
FundersNational Institutes of HealthEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentHealth Research BoardMcMaster UniversityHamilton Health Sciences
KeywordsDevelopmental psychologyPsychology

Abstract

fetched live from OpenAlex

This study examines caregivers' perceptions of participation patterns and environmental supports and barriers for young children with and without developmental disabilities within their child care/preschool and community settings. The Young Children's Participation and Environment Measure (YC-PEM) was completed by 151 parents of Singaporean children (0-7 years old) with and without developmental disabilities. Setting-specific summary and item-level scores of these children were compared using ANCOVA, Mann-Whitney U, and Pearson chi-square tests. Children with developmental disabilities had significantly lower participation and environment summary scores in both settings as compared with children without developmental disabilities (p < .05; [Formula: see text] = 0.03-0.31). Group differences were also evident at the item level, particularly when comparing the percentage of parents who desire change in their child's activity participation. Adequate financial support, public awareness, programs, and services have been identified as environmental factors that are potentially important to parents of children with developmental 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 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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.184
GPT teacher head0.473
Teacher spread0.289 · 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.

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

Citations36
Published2016
Admission routes2
Has abstractyes

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