Sustainability impact assessments of free trade agreements
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Trade negotiations are frequently accompanied by sustainability impact assessment (SIA) to evaluate the potential economic, environmental, social and human rights effects of a possible agreement. SIAs can help promote environmental protection, and support the better integration of women, vulnerable populations, and small businesses into the global economy, as well as address growing concerns from civil society. They provide a critical opportunity for dialogue among stakeholders and trade policy makers, and thereby help to rebuild confidence in the trading system. However, SIA approaches -including economic modelling, qualitative causal chain analysis and stakeholder consultations -each have their strengths, challenges and limitations. Those need to be understood by policy makers if reliable and policy relevant conclusions are to be provided. This paper offers a perspective on the challenges and opportunities of various approaches and discusses best practices for assessing the sustainability impact of trade and trade agreements.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 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 it