Art during tough times: reflections from an art-based health promotion initiative during the COVID-19 pandemic
Bibliographic record
Abstract
With the current COVID-19 pandemic impacting communities across the globe, diverse health promotion strategies are required to address the wide-ranging challenges we face. Art is a highly engaging tool that promotes positive well-being and increases community engagement and participation. The 'Create Hope Mural' campaign emerged as an arts-based health promotion response to inspire dialogue on why hope is so important for Canadians during these challenging times. This initiative is a partnership between a health promotion network based in Vancouver and an 'open air' art museum based in Toronto. Families were invited to submit artwork online that represents the concept of hope. This paper discusses the reflections of organizers of this arts-based health promotion initiative during the early months of the pandemic in Canada. Our findings reveal the importance of decolonizing practices, centring the voices of those impacted by crisis, while being attentive to the social and political context. These learnings can be adopted by prospective health promoters attempting to use arts-based methods to address social and health inequities.
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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 | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.059 | 0.039 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.011 | 0.028 |
| Insufficient payload (model declined to judge) | 0.005 | 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".