COVID-19 provides an opportunity to advance a sustainable UK fisheries policy in a post-Brexit brave new world
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Brexit creates a systemic shock that provides a unique opportunity for the UK to implement a new sustainable Fisheries Policy to better manage the multiple stocks on which future fishers will depend on leaving the European Union. At the same time, the global slowdown of commercial fishing as a result of COVID-19 has reduced pressure on some threatened stocks to levels not seen since the Second World War. In combination, Brexit and the COVID-19 slowdown have created a unique opportunity to facilitate the recovery of a threatened resource. Nevertheless, challenges remain as fisheries represent only 0.12% of UK economic output, presenting a risk that opportunities for more sustainable management will be lost during wider trade negotiations. Reduced fishing pressure during the COVID-19 era will enable stocks an opportunity to recover if supported by a new UK Fisheries Policy that focuses on: (a) re-establishing the role of Maximum Sustainable Yield to set limits that enable the recovery of fish populations initiated during the COVID-19 era; (b) ensuring that catch targets are set with the aim to maintain biomass at 120% of that which will achieve Maximum Sustainable Yield; (c) improving coherent resource management that also considers the expensive use of carbon associated with unsustainable fishing, and the need to protect fish throughout their life-cycle; and (d) constructing and effectively enforcing protection of a resilient network of Marine Protected Areas despite potential protests from EU member states.
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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 | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.030 | 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 it