Measure What Matters: Toward Multi-Sectoral Action to Improve Child and Youth Health and Well-being
Bibliographic record
Abstract
Despite Canada’s strengths and widespread acknowledgment of the importance of children and youth, this country recently ranked 30th among 38 high-income countries on indicators of their well-being (UNICEF Innocenti 2020). While there are limited data readily available for monitoring within and across jurisdictions, Alberta compares worse than Canadian averages on indicators of early development vulnerability and child abuse (PHAC 2023a). The Alberta government convened a Child and Youth Well-being Review (GOA 2021) and Action Plan (GOA 2022a) to understand and address the pandemic’s adverse impacts. Indigenous and racialized children and youth, children in low-income families and children with disabilities were highlighted as being disproportionately impacted. In addition, the review found significant gaps in mental health, education, social data and evidence along with fragmentation of data within ministries and service systems (GOA 2021). Influences on child and youth health, well-being and health inequity have social, environmental and economic origins that extend beyond health policy boundaries (Lopez et al. 2021; Vargas-Barón, Diehl and Small 2022; Clark et al. 2020; Patton et al. 2016). Yet, public policy can be a powerful intermediary between children’s conditions and outcomes (UNICEF 2020). Cross-sectoral, whole-of-society approaches are required to improve child and youth health and well-being and government ministries have important roles to play (Akseer et al. 2020; De Montigny, Desjardins and Bouchard 2019; Leppo et al. 2013). Meaningful and accessible measurement and monitoring information is required to support co-ordinated, cross-sectoral decision-making and policy strategies to improve health outcomes and reduce health inequities (OECD 2021). Information is required about child and youth material living standards, physical and mental health, social lives and learning and education (OECD 2021). While definitions of child and youth well-being vary depending on diverse perspectives and cultural, social and local contexts, many established indicators and frameworks can be tailored to local community needs and priorities (OECD 2021).
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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 | 0.101 | 0.092 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.007 | 0.027 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".