Evidence-informed stakeholder consultations to promote rights-based approaches for children with disabilities
Bibliographic record
Abstract
Purpose: To strengthen the translation of evidence to actionable policy, stakeholder engagement is necessary to synthesize, prioritize and contextualize the academic research content into accessible language. In this manuscript we describe a multi-level evidence-based stakeholder consultation process and related outcomes proposed to promote awareness of and foster cross-sectorial collaborations towards human rights-based approaches for children with disabilities. Methods: Mixed-methods participatory action research done in three steps: (1) A literature review of peer-reviewed evidence on rights-based approaches in childhood disabilities; (2) Consultation with researchers in diverse fields, grassroot organizations, caregivers, and youth with disabilities; (3) A constructive dialogue with decision makers at federal and provincial levels in Canada to discuss consultations results. Results: Stakeholders value human rights approaches that can have a direct impact on practical aspects of their daily living. Organizations give high importance to adopting rights-based approaches to measure policy outcomes, while parents value service provision and youth emphasize accessibility. Conclusion: The implementation of rights-based approaches in childhood disabilities can support policy, services, and daily lives of children with disabilities and the ecosystems around them. It can also guide research priorities, and create a common language to foster collaborations across sectors and interested parties.
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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 | 0.279 | 0.312 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.005 | 0.030 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 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".