Bibliographic record
Abstract
Unsustainable amounts of waste are currently produced that need to be managed. As a result of detrimental economic, environmental, and social implications of the current dominant waste management options (landfill and incineration operations), there are increasing calls by policymakers, practitioners, and researchers to transition towards circular economies. In essence, a circular economy is a system in which wastes and other resources are reused, recycled, and recovered to achieve economic prosperity, environmental protection, and social equity. Such systems can operate from the micro level of products, companies, and consumers to national level and beyond. Circular economy manifestations already exist within and across the European Union (EU), and continue to be promoted as a result of its Circular Economy Package. Within the UK, for example, the city of Peterborough is aiming to be a circular city by 2050, while at the national level, the UK exports certain wastes to Sweden in order to be burnt at incineration plants for their district heating systems. Brexit will thus affect circular economy approaches with the UK because of such existing macro circular exchanges between the UK and other countries, in addition to EU waste laws largely having driven waste law within the UK. It is therefore anticipated that the amount of waste sent to landfill in the UK will increase in the short term. Simultaneously, Brexit has also been considered an opportunity for the UK to stimulate more localised circular economy systems. This paper therefore investigates possible positive and negative implications of Brexit for the circular economy within the legal context. These are identified through desk-based research.
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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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.057 |
| Scholarly communication | 0.024 | 0.033 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.017 | 0.013 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".