MétaCan
Menu
Back to cohort
Record W2163414594 · doi:10.1080/j006v26n04_06

Creating Connections

2006· article· en· W2163414594 on OpenAlexaffabout
Kerry Wynn, Debra Stewart, Mary Law, Therese Moning

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2006
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsMcMaster UniversityGlenrose Rehabilitation Hospital
Fundersnot available
KeywordsParticipatory action researchInclusion (mineral)Participatory evaluationPsychologyOccupational therapyCitizen journalismPopulationCommunity-based participatory researchMedical educationSpecial populationsCommunity participationGerontologyApplied psychologySociologyMedicinePolitical scienceSocial psychologyEnvironmental healthPsychotherapistSocioeconomicsPsychiatry

Abstract

fetched live from OpenAlex

The transition to adulthood presents many challenges for youth with disabilities and their families. Barriers in the environment often limit the full inclusion of these youth in daily community life. The purpose of this paper is to describe a community capacity-building (CCB) approach to facilitating the transition to adulthood for youth with developmental disabilities and their families. A pilot project that used a CCB approach with this population in one community in southcentral Ontario is described. The results of a qualitative, participatory evaluation demonstrate the benefits and challenges of this approach, with themes of increased community connections for youth and a greater awareness of their strengths and capacities. The perceived outcomes of the participants and the "lessons learned" for future initiatives using a CCB approach with different populations are discussed, as well as the fit between community capacity-building and occupational therapy. This pilot project demonstrates that a CCB approach has the potential to assist youth with disabilities to participate within their own communities.

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)0.000
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 score0.066
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.069
GPT teacher head0.411
Teacher spread0.342 · 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

Citations12
Published2006
Admission routes2
Has abstractyes

Explore more

Same venuePhysical & Occupational Therapy In PediatricsSame topicFamily and Disability Support ResearchFrench-language works237,207