How Trainees Become Multimodal Changemakers
Notice bibliographique
Résumé
To the Editor: Medical school for many students is a further step to greater changemaking. A new trainee will be exposed to a parade of potential role models, such as leaders in education, accomplished researchers, and those dedicated to clinical and community service. Students are often encouraged to select from the standard leadership areas above. Yet, just as there are many medical specialties, there are many changemaking modalities, and new trainees will benefit from early and broad exposure rather than foreclosing on those first identified or commonly found. Although less frequently mentioned in mainstream medical education, physicians across the country create change through entrepreneurship, holding political office, partnership with industry, and grassroots nonprofits, to name a few. For trainees who find themselves called to make change on issues they feel passionate about, finding the right combination of changemaking modalities can be crucial to both the impact of their efforts and personal satisfaction in their work. Part of this search for a fitting combination involves understanding how one’s personality and life experiences intersect with a given changemaking method. Those who desire maximal autonomy and control over timelines may be better suited to entrepreneurship, while others who desire social policy change may gravitate toward political advocacy. Regardless of whether an explored modality becomes a part of one’s regular repertoire of methods for changemaking, such exploration can give trainees new mental models, problem-solving techniques, and professional networks that will be invaluable for future endeavors. Within increasingly complex health care systems, multimodal avenues of changemaking synergize to increase opportunities for collaboration, personal growth, and satisfaction. To fully unlock the potential of multimodal changemaking, trainees should appreciate the impact of traditionally endorsed methods and also acknowledge the existing bias within the hidden curriculum of medical education. This provides a foundation for open-minded exploration of less common changemaking modalities that can be explored through identifying local mentors in the field or reaching for inspiration outside of medicine. Finally, trainees should reflect on how any given project can be better supported with different modalities of changemaking and which modalities better empower their own strengths and skills. This paradigm can better position a trainee to use their medical education to tackle ever-evolving problems that will require new solutions in the decades to come. Acknowledgments: The authors would like to thank the amazing mentors in changemaking they have had the benefit of learning from during their time as medical students at the University of British Columbia.
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 | 0,052 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,006 | 0,004 |
| Communication savante | 0,006 | 0,007 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,010 | 0,018 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,015 | 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 ».