Global Health Diplomacy Amid the COVID-19 Pandemic: A Strategic Opportunity for Improving Health, Peace, and Well-Being in the CARICOM Region—A Systematic Review
Bibliographic record
Abstract
Increased globalization has ushered in changes in diplomatic purposes and practices. As such, global health diplomacy (GHD) has become a growing field connecting the urgencies of global health and foreign affairs. More academics and policy-makers are thinking about how to structure and utilize diplomacy in pursuit of global health goals. This article aims to explore how the health, peace, and well-being of people in the region can be achieved through global health diplomacy. A systematic review of the literature was conducted on various terms such as “Global Health Diplomacy OR Foreign Policy”; “Disasters”, “Infectious disease epidemics” OR “Non-Communicable diseases” AND “Caribbean” by searching PubMed, Scopus, Embase, Web of Science databases, and Google Scholar search engines. A total of 33 articles that met the inclusion criteria were analyzed, and the critical role of GHD was highlighted. There is an increasing need to understand the complex global health challenges, coupled with the need to design appropriate solutions. Many regional initiatives addressing infectious and chronic diseases have been successful in multiple ways by strengthening unity and also by showing directions for other nations at a global level, e.g., the Port of Spain Summit declaration. GHD has a great scope to enhance preparedness, mitigation, peace, and development in the region. Amid the COVID-19 pandemic, the region needs to strengthen its efforts on equity issues, health promotion, and sustainable development to promote peace and well-being.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".