Bibliographic record
Abstract
Investor-state dispute settlement (ISDS) came to the centre of the world stage during the negotiations for the Trans-Pacific Partnership Agreement (TPP), held between 2008 and 2015. The TPP, had the United States remained a party, would have been the largest trade agreement in the world. This agreement would have shift ed US focus to Asia, joining the other partners to the pact: Brunei, Chile, New Zealand, Singapore, Vietnam, Peru, Canada, Japan, Malaysia and Mexico. Given the massive scope of this agreement, and the number of prominent countries participating in the negotiations, the TPP gained significant press attention and became more mainstream in conversation than most other trade agreements. At the forefront of the heated debates involving this agreement was its ISDS provision. These debates, featuring strong arguments as to why ISDS should no longer be included in trade agreements, came amid a growing worldwide trend away from ISDS. While the TPP may be at the centre of current worldwide discussion, due to its prominence in the news, there are several prominent trade agreements around the world that laid the foundation for this newer agreement. In North America, the North American Free Trade Agreement, between Canada, Mexico and the United States, was a landmark agreement that came into effect in 1994. This agreement created an explosion of trade between the countries, and greatly integrated the three economies. However, it met with a mixed reaction in the US, the largest economy of the parties to the agreement. This agreement once again came to the forefront of discussion, very much at the same time as the TPP, with US President Trump promising to abolish the agreement when he first came to office in 2016. This led to renewed negotiations on the agreement, and the rise of the new version of the agreement, known as the United States – Mexico – Canada Agreement (USMCA). The world’s oldest and most established economic community is the European Economic Community, now the EU, which was created after the Second World War. Twenty-seven countries are now party to the EU, which is now more expansive than just an economic union. The EU is now a sophisticated organisation of policy bodies as well, with specific regulations governing everything from climate and the environment to health and security, and from justice to migration.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.075 | 0.014 |
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".