Advocacy in community-based service learning: perspectives of community partner organizations
Bibliographic record
Abstract
Background: Health advocacy is a core competency for physicians, which can be developed through community-based service-learning (CBSL). This exploratory study investigated the experiences of community partner organizations (CPOs) participating in CBSL in the context of health advocacy. Methods: A qualitative study was conducted. Nine CPOs at a medical school participated in interviews on topics pertaining to CBSL and health advocacy. Interviews were recorded, transcribed, and coded. Major themes were identified. Results: CPOs perceived a positive impact from CBSL through student activities and connecting with the medical community. There was no unifying definition of health advocacy. Advocacy activities varied depending on the individual's role (i.e., CPO, physician, and student), which encompassed providing patient care or services, raising awareness of healthcare issues, and influencing policy changes. CPOs had different perceptions of their role in CBSL from facilitating service-learning opportunities to teaching students in CBSL, while a few desired to be involved in curriculum development. Conclusion: This study provides further insight into health advocacy from the lens of CPOs, which may inform changes to health advocacy training and the CanMEDS Health Advocate Role to better align with the values of community organizations. Engaging CPOs in the broader medical education system may improve health advocacy training and ensure a positive bidirectional impact.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.022 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.030 | 0.020 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".