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Record W2170120574 · doi:10.1139/f05-056

Are marine protected areas a red herring or fisheries panacea?

2005· article· en· W2170120574 on OpenAlexvenueno aff
Michel J. Kaiser

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMarine protected areaFisheries managementFisheryPanacea (medicine)FishingFisheries scienceBusinessMarine reserveEnvironmental resource managementSustainabilityWork (physics)HabitatEnvironmental scienceEcologyEngineeringBiology

Abstract

fetched live from OpenAlex

Chronic failures in marine fisheries management have led some to suggest that marine protected areas (MPAs) are the solution to achieve sustainable fisheries. While such systems work for certain habitat-specific and nonmobile species, their utility for highly mobile stocks is questionable. Often the debate among proponents and critics of MPAs is confused by a lack of appreciation of the goals and objectives of such systems. The current consideration of MPAs as the basis of future fisheries management is a symptom of, and not the singular solution to, the problem of inappropriate implementation of fishing effort controls. The latter will provide greater overall conservation benefits if properly applied. Any future use of MPAs as an effective tool to achieve sustainable fisheries management in temperate systems should be treated as a large-scale, rigorously designed experiment to ensure that the outcome of using MPAs is interpreted correctly and not discredited for false reasons.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.004
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.024
GPT teacher head0.205
Teacher spread0.181 · 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 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

Citations155
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicCoral and Marine Ecosystems StudiesFrench-language works237,207