How research-based theatre is a solution for community engagement and advocacy at regional medical campuses: The Health and Equity through Advocacy, Research, and Theatre (HEART) program
Bibliographic record
Abstract
BACKGROUND: Regional medical campuses are often located in geographic regions that have different populations than the main campus, and are well-positioned to advocate for the health needs of their local community to promote social accountability within the medical school. METHODS: At the Niagara Regional Campus of McMaster University, medical students developed a framework which combined research, advocacy, and theatre to advocate for the needs of the local population of the regional campus to which they were assigned. This involved a qualitative study using semi-structured interviews with homeless individuals to explore their experience accessing the healthcare system and using a transformative framework to identify barriers to receiving quality healthcare services. Findings from the qualitative study informed a play script that presented the experiences of homeless individuals in the local health system, which was presented to health sciences learners and practicing health professionals. Participants completed two instruments to examine the utility of this framework. RESULTS: Research-based theatre was a useful intervention to educate current and future health professionals about the challenges faced by homeless individuals in the region. Participants from both shows felt the framework of research-based theatre was an effective strategy to promote change and advocate for marginalized populations. CONCLUSION: Research-based theatre is an innovative approach which can be utilized to promote social accountability at regional medical campuses, advocating for the health needs of the communities in which they are located, with the added bonus of educating current and future health professionals.
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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 | 0.044 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.020 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.005 | 0.034 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".