Bibliographic record
Abstract
This chapter critically examines the intellectual property rights holders' growing use of investor-state dispute settlement (ISDS) to resolve international intellectual property disputes. It begins by highlighting the criticisms of ISDS, including those that are related to the arbitration process, the arbitrators' interpretations and final arbitral outcomes. The chapter then examines the various upgrades that the Trans-Pacific Partnership (TPP) Agreement has provided to the ISDS mechanism. It concludes by outlining the conceptual and institutional improvements that could strengthen ISDS. This chapter retains its analytical focus on the TPP investment chapter despite the United States' withdrawal from the pact in January 2017. The retained focus is due largely to the adoption of that chapter as part of the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP), which was established among the eleven remaining TPP partners in January 2018. The only provisions in the original investment chapter that the CPTPP has suspended are those concerning "investment agreement" and "investment authorisation."
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".