Translating Ideals Into Practice: A Pragmatic Approach to Advocacy for Medical Trainees
Bibliographic record
Abstract
To the Editor: Medical trainees face barriers to engaging in advocacy, including time constraints, challenges to obtaining institutional support, and concern that advocacy will be perceived as unprofessional or less valuable than other scholarly endeavors. Using the Resident Interest Group in Social Advocacy (RIGSA) in the internal medicine program at the University of Toronto as an example, there are 3 actionable ways medical trainees can be empowered as agents of change: Create a collaborative space for advocacy: The creation of a formal advocacy group with institutional support in training programs reduces barriers for trainees to become involved in advocacy work. RIGSA was created by a resident in the internal medicine program after identifying a lack of a shared space for trainees interested in advocacy. With 3 faculty champions, including the program director, the group was formally adopted with over 20 residents who collaborated on projects. These faculty champions have identified advocacy as essential to—rather than contrary to—the concept of professionalism. Enact near-peer teaching of practical skills for allyship: There is a gap between knowing the theory of antioppression and having the skill set to implement it in practice, particularly within the context of power dynamics in medicine. Although oppression is a systemic problem warranting systems-level interventions, it is also empowering for medical learners to have formal training for disrupting discrimination in clinical contexts. RIGSA has delivered academic half-day workshops with a didactic component addressing the systemic, intersectional nature of oppression followed by an interactive small group component for trainees to practice principles of allyship. It is particularly important that trained workshop facilitators have lived experience (i.e., are Black, Indigenous, or people of color in workshops addressing racism) and are near-peers who understand the power dynamics at play. At the University of Toronto, faculty members also participated in allyship workshops to foster cultural change. Find clinical opportunities to work with marginalized populations: Social medicine elective opportunities are a direct way for trainees to understand the interplay between structural disadvantage and health. It is critical that faculty with long-standing relationships with community organizations are involved in these endeavors to properly serve the local communities of institutions. Learning objectives should be developed with community organizations. RIGSA is in the process of developing a social medicine elective. Collectively, these strategies illustrate how medical trainees and faculty can collaborate to translate ideals of advocacy into practice. Acknowledgments: The author thanks Dr. Lisa Richardson, Dr. Arno Kumagai, and Dr. Jeannette Goguen for their support in creating RIGSA.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".