“Location Is Surprisingly A Lot More Important Than You Think”: A Critical Thematic Analysis Of Push And Pull Factor Messaging Used On Caribbean Offshore Medical School Websites
Bibliographic record
Abstract
Background: Offshore medical schools are for-profit, private enterprises located in the Caribbean that provide undergraduate medical education to students who must leave the region for postgraduate training and also typically to practice. This growing industry attracts many medical students from the US and Canada who wish to return home to practice medicine. After graduation, international medical graduates can encounter challenges obtaining residency placements and can face other barriers related to practice. Methods: We conducted a qualitative thematic analysis to discern the dominant messages found on offshore medical school websites. Dominant messages included frequent references to push and pull factors intended to encourage potential applicants to consider attending an offshore medical school. We reviewed 38 English-language Caribbean offshore medical school websites in order to extract and record content pertaining to push and pull factors. Results: We found two push and four pull factors present across most offshore medical school websites. Push factors include the: shortages of physicians in the US and Canada that require new medical trainees; and low acceptance rates at medical schools in intended students’ home countries. Pull factors include the: financial benefits of attending an offshore medical school; geographic location and environment of training in the Caribbean; training quality and effectiveness; and the potential to practice medicine in one’s home country. Conclusions: This analysis contributes to our understanding of some of the factors behind students’ decisions to attend an offshore medical school. Importantly, push and pull factors do not address the barriers faced by offshore medical school graduates in finding postgraduate residency placements and ultimately practicing elsewhere. It is clear from push and pull factors that these medical schools heavily focus messaging and marketing towards students from the US and Canada, which raises questions about who benefits from this offshoring practice.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".