Reaching In and Reaching Out: Lessons Learned from the Co-Development and Co-Implementation of a Community-Engaged Physical Literacy Program
Bibliographic record
Abstract
Introduction UN SDG 11 Sustainable Cities and Communities and the CRPD Human Rights Article 9 Accessibility call for equitable approaches that prioritize accessibility for all, particularly marginalized young people experiencing disability. It is essential to acknowledge the intersectionality of disability with other factors, such as race/ethnicity, gender/sexuality, poverty, and social/cultural geography, which can exacerbate systemic oppression. Sustainable accessibility is crucial, yet it is a nuanced endeavour, requiring recognition of existing power structures and social injustices that hinder access to resources, services, and opportunities for marginalized disabled young people. Methodology MacPLAY (McMaster Physical Literacy for All Youth) and MacConnections are new community-engaged initiatives focusing on collaborations amongst all parties to co-learn, co-create, co-deliver, co-evaluate, and co-revise community-based physical literacy programming for children and youth experiencing disabilities in the city of Hamilton, Canada. Employing community-engaged participatory methodology, these co-linked projects are undergoing an initial piloting process, gathering diverse perspectives. Results Lessons learned include: (1) Both reaching in and reaching out as shared responsibilities, reciprocal collaborations, and respectful relationships; (2) working on new three Rs: reconciliation, restoration, and resonance; (3) Shifting from “for” to “with” and “by” in all processes; (4) Listening “to” and listening “for” to centre unheard and silenced voices; and (5) “Don’t just do it” as a collective reflexive practice. Conclusions EDIA (equity, diversity, inclusion, and accessibility) informed practice should be at the heart of creating and sustaining opportunities for young people with disabilities to participate in physical activity.
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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 | 0.039 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.006 | 0.018 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".