THE ROLE OF EU INSTITUTIONS IN COMMON TRADE POLICY: AN ASSESSMENT ON EU-CANADA COMPREHENSIVE ECONOMIC AND TRADE AGREEMENT
Bibliographic record
Abstract
What are the roles of the European Union (EU)’s main institutions in common trade policy? To address this question, this study uses a political-economic approach. The positions of the European Commission, Council of the European Union and European Parliament on EU-Canada Comprehensive Economic and Trade Agreement (CETA) are examined. The study uses content analysis as a research methodology, based on a categorization of values and economic interests projected by the EU’s contemporary trade strategy “Trade for All”. Differently from previous studies which use a political-economic approach to analyze the EU’s external relations with developing countries, this article makes a contribution to EU trade policy literature by combining a political-economy perspective with an institutional one to examine a EU trade agreement signed with a highly industrialized country. Within this context, the findings reveal that the Parliament and Council are more value-oriented, than economic interest-oriented. The Commission is instead found slightly more economic interest-oriented than value-oriented. However, the priorities of three institutions do not diverge significantly in terms of political economy. Each institution manages to impose its own priorities on both the (value-related) normative and (interest-related) material parts of CETA and agrees on producing a neoliberal economic outcome.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".