Translating Ideals Into Practice: A Pragmatic Approach to Advocacy for Medical Trainees
Notice bibliographique
Résumé
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.
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Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,041 | 0,128 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,010 | 0,018 |
| Communication savante | 0,011 | 0,011 |
| Science ouverte | 0,005 | 0,009 |
| Intégrité de la recherche | 0,019 | 0,041 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».