Resident Equity, Diversity, and Inclusion Committee: A Mechanism for Programmatic Change
Notice bibliographique
Résumé
To the Editor: In recent years, the importance of selecting a physician body that reflects the population it serves has been recognized as fundamental to excellence in training and patient care. To this end, North American medical education programs have developed policies and programs to increase diversity in medicine. However, learners from marginalized backgrounds are still disproportionately overrepresented in reported experiences of discrimination, harassment, and intimidation. 1 The resident equity, diversity, and inclusion (EDI) committee at the University of Toronto Paediatric Residency Program was conceptualized by residents and program leadership with 3 goals: (1) ensure that that program policies, practices, and organizations align with evidence-based EDI principles; (2) bring an intersectional, antioppressive, and antiracist lens to resident education; and (3) create initiatives to promote an organizational culture of EDI. The committee has a consultative role with separate oversight of other resident committees, and reports to the residency program committee and program director, to ensure the power to enact systems-level change. The committee brings together resident EDI experts who reflect diverse identities, experiences, and perspectives. Two resident co-chairs were identified by the program director after which 5 resident representatives were selected for their EDI expertise, and 1 member with experience in a different training program was chosen to provide an external perspective. Individuals from historically marginalized groups were prioritized. The program director also sits on the committee with the option for on-camera discussions and consultation with experts. The committee operates on a consensus-based decision-making model to allow for nuanced exploration of EDI issues. Established in 2021, the committee identified goals through an action priority matrix, organized resident education sessions about antioppression principles to recognize and address anti-Black/Indigenous racism, and supported residents through rising anti-Asian racism and the Israeli–Palestine conflict. Work is ongoing to establish a longitudinal resident EDI curriculum, recognize EDI work in awards, reduce barriers to learners celebrating non-Eurocentric holidays, critically review the resident selection process, and establish EDI-themed morbidity and mortality rounds. We hope that sharing the underlying principles, goals, composition, and decision-making structure of our resident EDI committee can serve as both a launching point for dialogue and action and a blueprint for establishing similar trainee-led committees at other programs with the goal of ensuring justice in residency programs at individual and systemic levels. Acknowledgments: The authors thank Dr. Adelle Atkinson and the other members of the Resident EDI Committee—Dr. Ashna Asim, Dr. Yamna Ali, Dr. Bonnie Cheung, Dr. Sabrina Lue Tam, and Dr. Lorna Sampson-Riden—for their guidance and input throughout this process.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
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 | 0,040 | 0,162 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,008 | 0,007 |
| Communication savante | 0,008 | 0,006 |
| Science ouverte | 0,006 | 0,006 |
| Intégrité de la recherche | 0,016 | 0,023 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 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 ».