Should the Medical Humanities Be Vital to Curricula?
Notice bibliographique
Résumé
To the Editor: We find the recent appeal by Dr. Bleakley1 for early integration of medical humanities in educational curricula refreshingly warm. As medical students, we often notice the lens of skepticism through which our peers view the arts in medicine. After all, if material is unlikely to be tested on clinical rotations or standardized exams, it quickly falls to the bottom of a trainee’s list of priorities. As years progress, we learn that we are rewarded for memorizing differential diagnoses and clinical facts. Thus, spending precious time reflecting on a narrative poem or an abstract art piece becomes increasingly trivial. In doing so, however, our perspectives harden to the scientific mold of medicine. We begin seeing the body as a machine with faulty parts rather than a human being with empathetic needs. Although this is certainly natural and welcome during a physician’s professional development, we must not forget to acknowledge humanity along the process. By reminding us of our initial aspirations for pursuing medicine, Dr. Bleakley emphasizes the why, rather than the how, behind teaching the medical humanities. The author expresses that longitudinal, integrated curricula in the medical humanities can develop skills, such as navigating uncertainty as a basis to promoting patient–physician trust relations. His call for heightened awareness of this softer school of thought in the face of an often mechanical and traditionally patriarchal medical system is not new. Many have previously delineated and robustly studied the benefits of self-reflection using history, art, and literature in medicine. And yet, as these virtues have become more defined, incorporating the humanities into medical education has slowly morphed into an administrative, rather than a learner-centered, endeavor. We often ask: How do medical educators fit lessons of compassion into busy curriculum schedules when already pressed for time to teach the fundamentals of medicine? What long-term objective outcomes can be deciphered by exposing students to the arts early in their careers? Who will volunteer their time to influence medical trainees to embrace this seemingly subjective practice, when we are undeniably conditioned to achieve numerical accomplishments instead? We applaud Dr. Bleakley for ignoring these often-debated bureaucratic challenges and rather for approaching the topic with deeper meaning. Trainees in all aspects of medicine can profit from this philosophical outlook as motivation for learning lessons of compassion and humanity from a regularly forgotten but unquestionably vital piece of curriculum. Aleksandar RadonjicThird-year medical student, Faculty of Medicine, University of Ottawa, Ottawa, Canada; [email protected]; ORCID: https://orcid.org/0000-0003-0296-376X.Emily Louise EvansThird-year medical student, Faculty of Medicine, University of Ottawa, Ottawa, 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 | 0,006 | 0,044 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,004 |
| Communication savante | 0,006 | 0,006 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,016 | 0,031 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,004 |
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 ».