Bibliographic record
Abstract
Public health measures taken by States have been subject to mounting arbitration legal challenges. These challenges resulted in an argument that investment agreements in general and the prevalence of the Investor-State Dispute Settlement (ISDS) mechanism, in particular, may force governments to refrain from introducing new legislative or policy measures due to a fear that the measures could be contested by investors. This situation, a fear to adopt legislative and similar other measures, is often referred to as “regulatory chill.” Recent arbitration cases show, however, that some of the cases involving pharmaceutical and similar other companies have been decided in favor of State Parties to the ISDS. In this regard, the legal claims initiated by Eli Lilly against the Government of Canada or the arbitration claims brought by Philip Morris against the Government of Australia and Uruguay can be cases in point. Due to these recent cases, some scholars have argued that the ISDS decisions (such as Eli Lilly and Government of Canada) demonstrate that regulatory chill may not be States’ concern anymore. This paper examines the obligations of State Parties to the International Covenant on Economic, Social and Cultural Rights (ICESCR or Covenant) to ensure access to affordable health technologies (medicines, vaccines, etc.) and the likelihood of investment agreements to result in a “regulatory chill” that hinders the realization of the obligations. In order to do so, the paper takes the TPP’s (now CPTPP) investment chapter as a case in point.
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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.020 | 0.021 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.025 | 0.024 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".