Fuelling the decline in UK fishing communities?
Bibliographic record
Abstract
Abstract Abernethy, K. E., Trebilcock, P., Kebede, B., Allison, E. H., and Dulvy, N. K. 2010. Fuelling the decline in UK fishing communities? – ICES Journal of Marine Science, 67: 1076–1085. Volatile fuel prices are a threat to the viability of UK fishing communities. The economic and social impacts of rising fuel costs for fishers and communities in southwest England are examined. Fuel prices doubled between early 2007 and mid-2008, whereas fish prices remained relatively stable throughout as a result of the price-setting power of seafood buyers. It was the fishers who absorbed the increased costs, resulting in significant loss of income, reduced job security, and problems in recruiting crew. All gear types were affected, but fishers using towed gears were most adversely impacted. Fishing vessels with recent investment have greater fuel efficiency, so appeared to be more able to cope and to adapt to increased fuel costs. Fishing behaviour also altered as skippers attempted to increase fuel efficiency at the cost of reduced catches. Most skippers reported fishing closer to port, reducing their exploratory fishing, and ceasing experimentation with fishing gears with lesser environmental impact. Therefore, a threat to fishing community viability may have linked environmental effects. The impacts of this fuel price volatility foreshadow a likely future impact of rising fuel prices attributable to climate change adaptation and mitigation and forecasts of rising oil prices. Without proactive planning and policy development, rising fuel prices have the potential to cause job losses and economic hardship additional to problems that may arise from poor management and stock decline, in all fishing-related sectors of the industry.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".