Trade and the environment : Environmental assessments of regional trade agreements and policies for Zimbabwe.
Bibliographic record
Abstract
Environmental provisions have become a common inclusion in trade agreements. Their incorporation is somewhat far-reaching, and more comprehensive in a manner complimentary to the main trade liberalisation provisions. At the helm of this inclusivity is the concept of sustainable development, which is key in the successful establishment, and implementation of trade liberalization structures. Through this concept, environmental provisions among other considerations, have found their way into trade agreements be it at bilateral, regional or multilateral level. This inclusion can be attributed to the growing awareness of states of aspects such as climate change as well as the increased strive towards sustainable development. At the helm of this trade and the environment relationship, is the role of the WTO, which is the global regulating body of all thing international trade. Critics allege the failure by this body to effectively address sustainability and environmental issues that multilateral level albeit it’s supposed to then give a guide to regional and bilateral trading relationships. This dissertation clarified the incorporation of environmental and sustainability provisions in the SADC, COMESA, TFTA, AfCFTA and the IEPA trade agreements. It explored the extent of environmental assessments carried out to determine the effectiveness of the environmental provisions incorporated in the final agreement. Furthermore, this dissertation explored different regional and country approaches in how they have included environmental and sustainability provisions in their trade agreements as well as national policy and law. Close consideration was given to the USA, Canada and the EU, as they are leading jurisdictions in undertaking environmental assessments of trade agreements both ex post and ex ante. This comparison helped to demonstrate which approach seems more effective at causing change as well as providing information and guidance in policy formulation. Qualitatively, the research concluded that there is not yet established a one size fits all method of assessment. However, there is nothing barring states from using all the existing models of assessments for more definitive results. Further, the research established that it is important to carry out both ex post and ex ante assessments to ensure the state parties get the maximum benefits possible from trade agreements an policy
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".