Health inequalities in the Caribbean: increasing opportunities and resources
Bibliographic record
Abstract
Social inequalities in health are not a priority in the Caribbean region. However, a few studies suggested such disparities and indicators show important socioeconomic disparities between and within countries. There are indications that governments' investment in health and other social programs is insufficient in the region and that regional health institutions that guide national health policies and programs do not make the reduction of social inequalities a priority. Furthermore, the public health sector is generally weak and health services are mainly focusing on curative services. The author argues that there is a need to develop and to implement social policies that include equity and social justice as core values. In order to increase the focus on health inequalities in the region, there is also a need to strengthen the Public Health field that integrates Health Promotion strategies. It is also suggested that international, regional and national health sectors that include academic and research institutions, health-related journals and associations, and non-governmental organizations put health inequalities in the Caribbean on their agenda. Furthermore, there should be a fundamental switch from a biomedical perspective of health to a paradigm that considers health as the expression of political, social and economic circumstances.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.001 |
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".