Circular economy international trade: An investigation of the relationship between european union circularity and international trade
Bibliographic record
Abstract
Through increased international trade, circularity can be economically effective, motivating countries and industries to engage in circularity, which is urgently required to improve environmental outcomes. Therefore, this study empirically investigates whether higher national circularity can drive international trade in waste and scrap. This study builds on and tests previous theory on circular economy international trade using a large balanced panel dataset from all 27 European Union countries over 2011–2016. This study focuses on the factors—circular economy policy, circular research and innovation, or both—that influence countries' circular capabilities when trade is attractive. This study quantitatively explores drivers of circularity to facilitate the international trade of waste and scrap, including chemicals, metals, and plastics originating in the European Union, where circular material use rates are tracked. The findings reveal that circularity provides economic benefits through increased international trade. Additionally, policy and innovation factors increase a nation's circularity. This study builds on a growing research stream in circular economy international trade. • This study empirically investigates drivers of national circularity on waste trade. • The study employs large-scale quantitative analysis of EU data over several years. • Waste and scrap include chemicals, metals, and plastics originating in the EU. • Circularity provides economic benefits through increased international trade. • Empirical evidence reveals an export-magnification effect of offshoring.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 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; a candidate call from one teacher head, 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".