Bibliographic record
Abstract
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]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.015 | 0.028 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".