A four‐part ecological model of community‐focused therapeutic recreation and life skills services for children and youth with disabilities
Bibliographic record
Abstract
AIM: This article presents a four-part model of community-focused therapeutic recreation and life skills services for children's rehabilitation centres. METHOD AND RESULTS: The model is based on 15 years of clinical and management practice in a Canadian context combined with evidence from the literature on community-focused service delivery. The model incorporates an ecological approach and principles from models of therapeutic recreation, community capacity building, and health promotion, as well as client/family-centred care. The four pillars of the model reflect a set of integrated services and principles designed to support the participation of children and youth with disabilities in community activities. The pillars involve providing community outreach services, providing community development services, sharing physical and educational resources with community partners, and promoting the organization as a community facility that provides adapted physical space and specialized instruction. The lessons learned in implementing the model are discussed, including the importance of ensuring the sustainability of community recreation programmes. CONCLUSIONS: The model will be of use to managers and service organizations seeking to develop an integrated programme of community-focused therapeutic recreation and life skills services based on a collaborative capacity-building approach.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".