Decommissioning of the Dutch cutter sector : Impact analysis of management measures on the fishery
Bibliographic record
Abstract
This study is part of an overarching socio-economic impact analysis of policy decisions on and developments in fisheries. The central research question for this study is: What are the socio-economic effects of the decommissioning scheme on the fisheries sector, the fish chain and fishing regions? Looking at the historical (2018-2021) activity of the vessels that were registered for scrapping, the expected effects of the removal of those vessels will mainly be felt in the beam trawl flatfish fishery. The relative changes in landings of sole and plaice are expected to exceed the change in quota share due to Brexit. For cod this is less clear and there is a risk that the landings decrease due to the exit of decommissioned vessels in a lesser proportion than the quota due to Brexit. The landings of pelagic species are not expected to change due to the scheme given that no pelagic vessels registered for the scheme, while the share of post-Brexit quotas will go down. All Dutch fisheries regions are expected to be impacted by the exit of scrapped vessels, either because a large part of the fleet is expected to be scrapped (as in Urk) or because a large proportion of the Dutch landings is landed in those regions (as in Southwest Netherlands, Kop van Noord-Holland, Wadden Coast and IJmuiden).
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".