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Record W2921275323 · doi:10.1002/9781118392607.ch1

Governance of marine fisheries and biodiversity conservation

2014· other· en· W2921275323 on OpenAlexaff
Serge M. Garcia, Jake Rice, Anthony Charles

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsSaint Mary's UniversityFisheries and Oceans Canada
Fundersnot available
KeywordsCorporate governanceBiodiversityConvergence (economics)FisheryBiodiversity conservationGeographyScale (ratio)Marine conservationSTREAMSPolitical scienceEnvironmental resource managementEcologyEconomicsBiologyEconomic growthManagement

Abstract

fetched live from OpenAlex

The governance of marine fisheries and biodiversity conservation has evolved significantly since its origin. The chapter describes its evolution, at a global scale, using the international events compiled from the literature as data. The history of the two streams of governance is rich and reflects a constant quest to improve performance with mixed results. These streams have important common roots in pre-capitalistic and pre-colonial communities. They tend to emerge more clearly during the 19th century as a utilitarian and an aesthetic branch of conservation with tumultuous relationships. In fisheries, centralized forms of governance already existed in the 13th century. In marine conservation, they were practically absent until the 1960s and have emerged forcefully since the mid-20th century. From 1970 onwards, the emergence of the Law of the Sea (LOSC) and a number of cross-sectoral summits established institutional bridges between the two streams, accelerating conceptual convergence.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.005
Scholarly communication0.0070.003
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.005
GPT teacher head0.155
Teacher spread0.149 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations8
Published2014
Admission routes1
Has abstractyes

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