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Record W2037433075 · doi:10.2182/cjot.06.10

Successful Participation: The Lived Experience among Children with Disabilities

2007· article· en· W2037433075 on OpenAlexaffvenue
Tom Heah, Tara Case, Brianna K. McGuire, Mary Law

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2007
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsMcMaster UniversityThe Sisters of Charity of OttawaVancouver Coastal Health
Fundersnot available
KeywordsLived experienceOccupational therapyPsychologyDevelopmental psychologyMedicinePsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Children with disabilities are at risk for limited daily occupational participation. This paper presents a phenomenological study describing the meaning of participation in activities outside of school to children with physical and neurological disabilities and their parents. METHODS: Semi-structured interviews were conducted with eight children and their parents. RESULTS: Nine themes, organized under three categories, describe what successful participation means, and the personal and environmental supports and barriers to participation. Successful participation is defined in terms of being with others and being able to perform tasks independently. CONCLUSIONS: This study demonstrates that children with physical and neurological disabilities enjoy the same activities as those children without these disabilities. Activities allowing children to experience enjoyment have the best chance of ensuring children's participation. The role of the parent in providing opportunities for participation, and the importance of environmental and personal resources are particularly important. Finally, implications for occupational therapy and research are discussed.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.008
Scholarly communication0.0040.003
Open science0.0010.006
Research integrity0.0010.002
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 head0.310
GPT teacher head0.516
Teacher spread0.206 · 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 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

Citations195
Published2007
Admission routes2
Has abstractyes

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