Notice bibliographique
Résumé
To the Editor: Drs. Palazuelos and Dhillon1 summarize a popular mind-set around phvysicians’ involvement in global health experiences abroad: that everyone who wants to ought to be able to do global health work abroad. Unfortunately, simple logic suggests it is not feasible to provide meaningful work abroad to the two-thirds of U.S. medical students who express interest.2 Yet, this ideal drives an ever-growing number of trainees and young physicians to invest in master of public health degrees and research/study-abroad electives, and promotes efforts by specialties not traditionally involved in population-level health work abroad (e.g., surgery) to label their work “global health” in competing with more traditional fields (e.g., public health or primary care) for attention and resources. Others argue that global health should be a recognized physician specialty, with accredited training programs and defined career positions within a particular practice profile. This would address the striking parallels with “start-up” culture as described by Drs. Palazuelos and Dhillon, where few of many entrepreneurs “make it” against seemingly insurmountable barriers, often at great personal sacrifice and/or thanks to circumstantial advantage. Those who fail are left to reprioritize after having invested time, passion, and money. Directing some practitioners towards a formal training and career pipeline might provide greater stability and direction. Indeed, what Drs. Palazuelos and Dhillon describe as “wild cards” are various life priorities, for which the choice of career is no different, and often in competition with other seemingly immovable priorities, such as massive debt, or a domestically focused spouse/partner. At present, pursuing an expatriate career leads to inevitable sacrifices without guarantee of success, which makes the global health “tax” described by the authors more realistically an “ante.” The authors conclude that without support, many will ultimately exit the field of global health. While unfortunate, this is reasonably expected as individuals reprioritize, which means at minimum any support should include improved career mentorship and guidance. The establishment of formal training programs leading to defined employment might also help rationalize the existing “start-up” environment. Formally trained specialists would resemble the differences between public health physicians and physicians interested in public health; the former are vocationally trained, the latter are clinicians with side projects. Should global health work continue to solely exist “on the side,” then much like early clinician–researchers chasing their first grant, interested practitioners will ante up hoping to “make it” into an expatriate career—perhaps against their better judgment. Lawrence C. Loh, MD, MPH Adjunct professor, Clinical Public Health, Dalla Lana School of Public Health, University of Toronto, Toronto, 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 | 0,005 | 0,045 |
| 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 | 0,003 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,004 | 0,001 |
| Intégrité de la recherche | 0,015 | 0,028 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,007 |
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 ».