Advantages and Disadvantages of Signing a Comprehensive Economic and Trade Agreement (CETA) for the Еconomies of the EU and Canada
Bibliographic record
Abstract
This article presents an analysis of the main provisions of the Comprehensive Economic and Trade Agreement (CETA) signed by the government of Canada and the European Parliament at the end of 2016. In particular, the author analysed such aspects of the agreement as the abolition of customs tariffs, the introduction of common quality standards, access to the procurement market, modification of the system of investment disputes, etc. According to the results of the study, there was a mixed effect of the agreement for both Canada and the EU. For some sectors of the economies of the participating countries, the implementation of the CETA promises to create exceptional conditions for development, while for others the signing of a multilateral agreement is unprofitable or means losses. It should be noted that at the present stage the pros and cons of the СЕТА can be considered only at the theoretical level. It will be possible to draw objective conclusions about the impact of the multilateral trade agreement on the development of trade and economic relations between the countries only a certain time later after the ratification of the agreement by all parties. At the current stage of development of Canada-EU relations within the framework of the СЕТА, it can be noted that only the dynamic development and further improvement of the mechanisms of the multilateral agreement will make a trade and economic relations between the countries more open and transparent.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".