“This Is What You Get When You Lead with the Arts”: Making the Case for Social Wellness
Bibliographic record
Abstract
Like other key terms in the medical and health humanities-empathy, creativity, and reflection, to name just a few-wellness has become a weasel word, rife the language of optimization, duty, and self-perception. While alternative vocabularies exist-well-being and quality of life among them-these options usually privilege the objectives of academic (often psychological) research, health institutions, and the economic state apparatus, rather than people themselves. In mind of these concerns, why attempt to make a case for wellness at all? We present a historically informed, theoretically driven, praxis-guided framework for a renewed vision of social wellness (a concept first defined in the late 1950s). While definitions since Bill Hettler's "hexagonal" model (1980) have included mutual respect for others and the assumption of cooperative behaviors, conspicuously absent from contemporary definitions and usage is any mention of the aesthetic realm, which we-alongside philosophers like Amartya Sen and Martha Nussbaum-take as a central human capability. How can the relational possibilities of arts engagement be understood as not just a means of promoting individual wellness, but also as a method and outcome of social wellness? We propose that social wellness is ultimately premised on the interplay between wellness of the collective and the strength of the relational encounters it engenders. We turn to a key practice paradigm-community arts engagement-as both a vehicle for and site of social wellness. With brief reference to a Canadian exemplar, we conclude with concrete recommendations for addressing critical opportunities for advancing arts-led social wellness initiatives involving academic and community partners.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.110 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.008 | 0.013 |
| 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".