The Trans-Pacific Partnership: Is It Everything We Feared for Health?
Bibliographic record
Abstract
BACKGROUND: Negotiations surrounding the Trans-Pacific Partnership (TPP) trade and investment agreement have recently concluded. Although trade and investment agreements, part of a broader shift to global economic integration, have been argued to be vital to improved economic growth, health, and general welfare, these agreements have increasingly come under scrutiny for their direct and indirect health impacts. METHODS: We conducted a prospective health impact analysis to identify and assess a selected array of potential health risks of the TPP. We adapted the standard protocol for Health impact assessments (HIAs) (screening, scoping, and appraisal) to our aim of assessing potential health risks of trade and investment policy, and selected a health impact review methodology. This methodology is used to create a summary estimation of the most significant impacts on health of a broad policy or cluster of policies, such as a comprehensive trade and investment agreement. RESULTS: Our analysis shows that there are a number of potentially serious health risks associated with the TPP, and details a range of policy implications for the health sector. Of particular focus are the potential implications of changes to intellectual property rights (IPRs), sanitary and phytosanitary measures (SPS), technical barriers to trade (TBT), investor-state dispute settlement (ISDS), and regulatory coherence provisions on a range of issues, including access to medicines and health services, tobacco and alcohol control, diet-related health, and domestic health policy-making. CONCLUSION: We provide a list of policy recommendations to mitigate potential health risks associated with the TPP, and suggest that broad public consultations, including on the health risks of trade and investment agreements, should be part of all trade negotiations.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".