Navigating the burden of proof and responsibility: A narrative inquiry into Indigenous medical learners' experiences
Notice bibliographique
Résumé
INTRODUCTION: Many medical schools have well-established admission pathways and programming to support Indigenous medical workforce development. Ideally, these efforts should contribute to attracting highly qualified Indigenous applicants which, in turn, may improve accessible, quality care for Indigenous people. However, it is difficult to evolve and tailor these approaches without a situated understanding of Indigenous learners' experiences. In this paper, we focus on the Canadian context, sharing Indigenous learners' stories about their journey towards and throughout medical training. METHODS: The conceptual underpinnings of narrative inquiry and key principles from Indigenous methodologies were drawn upon throughout both data collection and analysis. Participants were Indigenous learners (medical students and residents) and a recently graduated physician (n = 5) from one Canadian medical school. Both spoken (formal recorded interviews) and visual (photographs) texts were used to make meaning of participants' experiences. RESULTS: Participants' experiences during medical training showed a striking resemblance at three points in their transition to, and progression through, medical education: preparing for and applying to medical school, completing undergraduate medical training and determining specialty choice. Participants' stories revealed a tug-of-war between their identities as an Indigenous person and as a medical trainee, with these tensions sometimes compromising their perceived sense of belonging within both Indigenous and academic circles, creating, at times, a heavy burden to shoulder. CONCLUSION: Meaningful representation of Indigenous people in the medical workforce is about more than training additional health care providers; it requires understanding Indigenous learners and recently graduated physicians' experiences as they enter and navigate the medical profession. By amplifying their voices, we stand to gain a more holistic representation of the factors that contribute to and potentially impede the recruitment and retention of Indigenous people into the medical profession.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,000 |
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 tête enseignante, 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 ».