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).Deze studie maakt deel uit van een overkoepelende impactanalyse van de sociaal-economische gevolgen van beleidsbeslissingen en ontwikkelingen voor de visserij.De centrale onderzoeksvraag voor deze studie is: Wat zijn de sociaal-economische effecten van de sanering op de visserijsector, de visketen en de visserijregio's?Kijkend naar de historische (2018-2021) activiteiten van de vaartuigen die zich voor sloop hebben aangemeld, zullen de verwachte effecten van de sanering van die vaartuigen vooral merkbaar zijn in de boomkorvisserij op platvis.De relatieve veranderingen in de aanvoer van tong en schol zullen naar verwachting groter zijn dan de verandering in het quota-aandeel als gevolg van de Brexit.Voor kabeljauw is dit minder duidelijk en bestaat het risico dat de aanvoer als gevolg van de sanering van vaartuigen minder sterk afneemt dan de afname van het quotum als gevolg van de Brexit.De aanvoer van pelagische soorten zal naar verwachting niet veranderen als gevolg van de saneringsregeling, aangezien er geen pelagische vaartuigen voor de regeling zijn aangemeld, terwijl het quota-aandeel na de Brexit is gedaald.Alle Nederlandse visserijregio's zullen naar verwachting gevolgen ondervinden van de sanering van vaartuigen, hetzij omdat een groot deel van de vloot naar verwachting zal worden gesloopt (zoals op Urk), hetzij omdat een groot deel van de Nederlandse aanvoer in die gebieden wordt aangeland (zoals in Zuidwest-Nederland, de Kop van Noord-Holland, de Waddenkust en IJmuiden).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".