A new generation of trade policy: potential risks to diet-related health from the trans pacific partnership agreement
Bibliographic record
Abstract
Trade poses risks and opportunities to public health nutrition. This paper discusses the potential food-related public health risks of a radical new kind of trade agreement: the Trans Pacific Partnership agreement (TPP). Under negotiation since 2010, the TPP involves Australia, Brunei, Canada, Chile, Japan, Malaysia, Mexico, New Zealand, Peru, Singapore, the USA, and Vietnam. Here, we review the international evidence on the relationships between trade agreements and diet-related health and, where available, documents and leaked text from the TPP negotiations. Similar to other recent bilateral or regional trade agreements, we find that the TPP would propose tariffs reductions, foreign investment liberalisation and intellectual property protection that extend beyond provisions in the multilateral World Trade Organization agreements. The TPP is also likely to include strong investor protections, introducing major changes to domestic regulatory regimes to enable greater industry involvement in policy making and new avenues for appeal. Transnational food corporations would be able to sue governments if they try to introduce health policies that food companies claim violate their privileges in the TPP; even the potential threat of litigation could greatly curb governments' ability to protect public health. Hence, we find that the TPP, emblematic of a new generation of 21st century trade policy, could potentially yield greater risks to health than prior trade agreements. Because the text of the TPP is secret until the countries involved commit to the agreement, it is essential for public health concerns to be articulated during the negotiation process. Unless the potential health consequences of each part of the text are fully examined and taken into account, and binding language is incorporated in the TPP to safeguard regulatory policy space for health, the TPP could be detrimental to public health nutrition. Health advocates and health-related policymakers must be proactive in their engagement with the 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 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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 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".