Acknowledging a Holistic Framework for Learner Wellness: The Human Capabilities Approach
Notice bibliographique
Résumé
To the Editor: We commend Gengoux and Roberts’ recent Invited Commentary1 for raising important issues about student mental health and wellness. Wellness programs clearly need to be evidence- based and tailored to meet individual learner needs and circumstances. They also need to be respectful of issues arising from intersections of—among other facets of identity—race, culture, socioeconomic status, and gender in the context of medical education training. We also agree that this is not just a matter of respecting identities and legitimate differences in the human condition, it is about actively challenging social stigma and the tendency to reduce others to a single negatively framed characteristic that condemns them to a socially excluded and pilloried class. In response to the “epidemic of burnout”2 in medicine, wellness initiatives at our institution, the Cumming School of Medicine, are increasingly focusing on early prevention and intervention through engagement, advocacy, and scholarship. Wellness depends, we believe, on a core principle of embracing individual differences and vulnerability. If we recognize that everyone has abilities and disabilities, everyone is unique, there is no superordinate class or characteristic, and anyone can struggle with issues arising from their circumstances, then we can begin to address wellness at a more fundamental systems level. To that end, we draw on Nussbaum’s human capabilities approach,3 which is based on the principle that the freedom to achieve well-being is of primary moral importance, and . . . that freedom to achieve well-being is to be understood in terms of people’s capabilities, that is, their real opportunities to do and be what they have reason to value.3 By attending to opportunity as well as competence, we aim to orient and integrate wellness initiatives and programing and the scholarship we build around them. This approach is central to the Wellness Innovation Scholarship for Health Professions Education and Health Sciences (WISHES) laboratory at our institution. WISHES is taking a holistic approach that focuses on areas of wellness, such as mental, physical, occupational, social, and intellectual domains for individual learners and teachers; health professions education/training programs; and the intersection of the higher education system and the health care system.4 By using a human capabilities approach, we consider the interplay between competence and opportunity when addressing issues associated with wellness, and by doing so, we are seeking to have a positive impact not just on the individuals that make up our community but on the systems that influence wellness for all. Aliya Kassam, PhDAssistant professor, Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; [email protected]Rachel Ellaway, PhDProfessor, Department of Community Health Sciences, and director, Office of Health and Medical Education Scholarship (OHMES), Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
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 | 0,013 | 0,062 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,015 |
| Communication savante | 0,011 | 0,016 |
| Science ouverte | 0,009 | 0,005 |
| Intégrité de la recherche | 0,035 | 0,073 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,003 |
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 ».