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Towards an ecosystem approach to fisheries in Europe: a perspective on existing progress and future directions

2011· article· en· W1783384766 on OpenAlexaff
Simon Jennings, Jake Rice

Bibliographic record

VenueFish and Fisheries · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsSustainabilityDirectiveBusinessWater Framework DirectiveMarine Strategy Framework DirectiveFisheries managementEnvironmental resource managementPoliticsCorporate governanceEcosystemEnvironmental planningEnvironmental economicsFisheryEconomicsEcologyPolitical scienceGeographyFinance

Abstract

fetched live from OpenAlex

Abstract European countries are committed to adopting an ecosystem approach. These commitments are expected to influence the forthcoming reform of the Common Fisheries Policy (CFP) and thus progress towards implementing an ecosystem approach to fisheries (EAF). We suggest that the major impediments to adopting an EAF in the current CFP are the low specificity and incompatibility of environmental, social and economic objectives, no agreed guidance on the priority to be given to objectives when trade‐offs have to be made, a decision‐making system that is strongly influenced by short‐term national interests, and low societal and political will to pay the high short‐term costs of making the transition to sustainability. Notwithstanding, a high‐level policy framework to support the ecosystem approach and EAF, along with many of the tools needed to support an operational system, is now emerging. The rate of progress towards an operational EAF following CFP reform will be influenced by the requirement for a reformed management system to help achieve Good Environmental Status for ecosystem components and attributes, in support of European policy for the marine environment (principally the Marine Strategy Framework Directive). However, the willingness and capacity of member states to meet high short‐term transition costs, the extent of their support for transferring tactical decision‐making to regional bodies and their views on acceptable transition rates are likely to have more influence on progress towards meeting the objectives of an EAF.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.661
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.039
GPT teacher head0.254
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations86
Published2011
Admission routes1
Has abstractyes

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