TALKING TRADE OVER WINE: ASSESSING THE ROLE OF TRADE ASSOCIATIONS, BUREACRATIC AGENCIES AND LEGISLATIVE BODIES IN THE UNITED STATES-EUROPEAN UNION AND CANADA-EUROPEAN UNION WINE TRADE DISPUTES
Bibliographic record
Abstract
After more than two decades of on and off negotiations, the United States and Canada resolved their respective wine trade disputes with the European Union (EU).The resolution of the disputes represented important victories for US and Canadian government officials that had worked for more than twenty years on agreements that would guarantee their respective wine exporters fairer access to the European market.The purpose of this dissertation is to provide a descriptive analysis of the US-EU and Canada-EU wine trade disputes and the negotiations that helped resolve them.Using data collected from interviews with representatives from Canadian and US wine trade associations and Canadian and US governmental officials directly involved in the trade talks with the EU, it seeks to explore three distinct relationships that existed throughout the trade negotiation process: 1) within government (between legislative bodies and bureaucratic agencies); 2) within the private sector (between private sector trade associations, domestic and international); and 3) between government and the private sector (between legislative bodies, bureaucratic agencies, and trade associations).The ultimate findings suggest that despite differences in the institutional configuration of democratic states (presidential vs. parliamentary systems) such as the US and Canada, these states actually followed quite similar paths during the trade policy making process.Furthermore, this research argues that these similarities can be attributed to four key variables present in both cases: 1) common external problems; 2) common internal pressures; 3) common international governmental institutions; 4) common international non-governmental organizations.
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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 | 0.045 | 0.126 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.020 | 0.011 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".