Bibliographic record
Abstract
The Comprehensive Economic and Trade Agreement (CETA) between the European Union (EU) and Canada is the most ambitious (New generation) free trade agreement the EU has ever negotiated. It is a “mixed” agreement with EU and member states competences. Most elements of the agreement for which the EU has "exclusive competence", including the chapter on tariffs and non-tariff barriers (the dismantling of all barriers to trade in goods and services and market access to foreign direct investment) can – after the European Parliament gave its consent on 15 February 2017 - be applied provisionally in Spring 2017. With a specifically constructed macro-economic trade and growth model for Austria, we simulate the impact of CETA on Austria. CETA will add to Austria’s real GDP 0.3 percentage points in the medium run and will stimulate bilateral trade and FDI. Our model is a small prototype model and can easily be applied to other FTAs the EU is planning. A comparison shows that TTIP – which is “politically” dead now – would have the biggest impact (1.7% more real GDP).The almost finished negotiated EU-Japan FTA would result in an increase of Austria’s real GDP by 0.4% in the medium run.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".