The Globalization of Healthcare: International Agreements & Ontario Academic Health Science Centres
Bibliographic record
Abstract
Health systems are beginning to recognize the tremendous opportunity that globalization and international activities present for Academic Health Science Centres. This study explored the nature of international agreements within Ontario Academic Health Science Centres (OAHSC) and presents the exploratory findings to begin to develop an academically defensible body of literature on the topic. This study employed a constructivist grounded theory qualitative methodology, interviewing 14 participants who hold leadership positions within OAHSCs that actively participate in, or interface with, institutions that participate in international agreements (IAs). A conceptual framework is proposed that highlights the: (1) drivers, (2) barriers, (3) international activities, and (4) benefits for Ontario, that are associated with the IAs within OAHSCs. The findings highlight that IAs that are common to OAHSCs typically are either: humanitarian or business development in nature, in both cases, are focused on building health system capacity in the host country. Generally, IAs focus on three deliverables: (1) needs assessments, (2) advisory services, and (3) education training, however, in some instances, OAHSCs are starting to pursue licensing and third-party management of hospitals abroad as a part of the business development strategy.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.019 | 0.021 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".