Representation, activism, health promotion, and communication: The role of art in advancing global health and social justice
Bibliographic record
Abstract
This viewpoint advocates for the inclusion of art in global health discourse and practice. We explore four areas in which art can be leveraged to improve global health: (1) to amplify disenfranchised voices, (2) to advance social justice activism, (3) to strengthen communities and individuals, and (4) to improve global health communication. Drawing on community-driven art initiatives, we argue for an inclusive approach that respects diverse cultural perspectives and uplifts marginalized voices. Emphasizing interdisciplinary collaboration and ethical engagement, our framework invites global health discourse and practice to integrate art in order to foster empathy, challenge systemic inequities, and envision sustainable futures. By centering art, we seek to enrich the global health discipline with insights and transformative potential grounded in human experiences, cultural diversity, and shared humanity.
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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 | 0.017 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.105 |
| Scholarly communication | 0.022 | 0.012 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".