Bibliographic record
Abstract
Although it remains unclear which of the nearly thirty chapters 6 -or, more importantly, which specific provisions in those chapters-will be included in the final text of the TPP Agreement, the negotiations have been quite controversial.In addition to the usual concerns about having high standards that are heavily lobbied by industries and arguably inappropriate for many participating countries, the TPP negotiations have been heavily criticized for their secrecy and lack of transparency, accountability, and democratic participation.7 The draft text of the TPP intellectual property chapter, for example, was hitherto available only through WikiLeaks.8 Since then, the TPP chapter on environmental standards has also been publicly leaked.9 This Article does not seek to continue this line of criticism, although transparency, accountability, and democratic participation remain highly important.Nor does the Article aim to explore the agreement's implications for each specific trade sector, which have already received book-length treatments.10 Instead, this Article focuses on the ramifications of the exclusion of four different parties or groups of parties from the TPP negotiations: ( 1) China; (2) BRICS and other emerging economies; (3) Europe (including members of the European Union and other countries in the region such as Switzerland); 6 .Deborah Kay Elms, The Trans-Pacific Partnership Trade Negotiations: Some Outstanding Issues for the Final Stretch, 8 ASIAN J. WTO & INT'L HEALTH L. & POL'Y 379, 384 (2013) [hereinafter Elms, TPP Trade Negotiations].7.
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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.031 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.005 | 0.016 |
| Insufficient payload (model declined to judge) | 0.009 | 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".