Notice bibliographique
Résumé
We thank Dr. Pivalizza and colleagues for their interest in our article and for providing U.S. experiences in contrast to the Canadian context. Oversight of Canadian postgraduate education comes from the Royal College of Physicians and Surgeons of Canada and the Canadian College of Family Physicians, while undergraduate training is regulated by the Association of Faculties of Medicine of Canada. In contrast to the United States, while all three bodies include competency in health advocacy and promotion as a key foundational principle,1–3 and in proposed visions for the future of medical education,4 there is no specific mandate to include training on legislative and regulatory issues at either the undergraduate or postgraduate level. Our call to action highlighted the need to include training on a variety of advocacy strategies within Canadian medical education, of which objectives specific to legislative and regulatory considerations could be one part. This inclusion would certainly see some of the barriers highlighted by Dr. Pivalizza and colleagues arise in academic settings, which would require educators to address key concerns in a manner that respects and seeks consensus between competing interests, employing formal processes to incorporate internal and external stakeholders’ input into curriculum development. Advocacy training must also carefully tread the line between developing learners’ skills and calling them to action. Too often, teaching of the latter nature has drawn criticism and opposition against previous curricular inclusion efforts. Advocacy training must therefore avoid imposing viewpoints on trainees and instead focus on developing the skills necessary to assess and engage in advocacy consistent with trainees’ own values and opinions, should they so desire. Regardless of how curricular development proceeds, the importance of formal advocacy training in contemporary medical education cannot be ignored. As the discourse on health and health care becomes increasingly contentious and crowded with myriad voices, it is untenable for physicians to remain passive observers without developing needed skills in this arena. Medical trainees and physicians must ensure that their experiences and evidence are part of discussions that shape the systems and communities that impact our patients’ health and well-being. Thus, despite different national contexts, an ongoing transborder dialogue between Canadian and U.S. educators is critical towards creating a shared vision for advocacy training and social accountability in medical education. Tahara D. Bhate, MD, MHSc Resident physician, Department of Family Medicine, University of Calgary, Calgary, Alberta, Canada. Lawrence C. Loh, MD, MPH Associate medical officer of health, Peel Public Health, Mississauga, Ontario, Canada, adjunct professor, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada, clinical lecturer, Department of Family Medicine, Queen’s University, Kingston, Ontario, Canada, and director of programs, The 53rd Week Ltd., Brooklyn, New York; [email protected]
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 | 0,008 | 0,072 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,006 |
| Communication savante | 0,007 | 0,011 |
| Science ouverte | 0,006 | 0,004 |
| Intégrité de la recherche | 0,045 | 0,068 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,010 |
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 ».