Globalization and International Trade in the Twenty-First Century: Opportunities for and Threats to the Health Sector in the South
Bibliographic record
Abstract
Globalization and international trade are important forces at the turn of the century. This article explores how freer international trade will affect developing countries that are net importers of health care goods and services. Four commodities are used as special cases for discussion: pharmaceuticals, health care technologies, pesticides, and tobacco and its related products. The authors discuss the role of international specialized agencies, such as the World Trade Organization, World Health Organization, and World Bank, that are concerned with international trade and its health and health care consequences, and argue that closer collaboration is required among these agencies if the negative effects of trade liberalization on developing countries are to be mitigated. The authors pose a number of research questions that could help in developing proactive policies for the South on the trade of goods and services with harmful effects on health as well as those with potential health and economic benefits.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".