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Record W7039336502

Local and Regional Strategies for Rebuilding Fisheries Management Institutions in Coastal British Colombia: What Components of Comanagement are Most Critical?

2014· article· en· W7039336502 on OpenAlexfundaboutno aff

Bibliographic record

VenueDigital Library Of The Commons Repository (Indiana University) · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBeetle Biology and Toxicology Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFishingIntertidal zoneFisheries managementGovernment (linguistics)Process (computing)PoliticsCoastal management
DOInot available

Abstract

fetched live from OpenAlex

"Aboriginal and nonaboriginal fishing-dependent communities on the coast of British Columbia, Canada, having lost traditional fisheries management institutions along with significant fishing opportunity, are in the process of rebuilding local and regional institutions to allow their survival. Sometimes, the rebuilding effort involves the creation of largely new institutions. It can also involve the reactivation, reinvention, or repositioning of older ones. We consider the aspirations, strategies, and activities of organizations in two regions of the coast involved in two different fisheries: salmon on the north coast and intertidal clams in the Broughton Archipelago. We analyze what the two regions have in common, as well as their differences, to generate general predictions and recommendations about what preconditions appear to be necessary for success in rebuilding institutions in communities and regions at these scales and what actions are likely to be most effective, according to a body of literature on self-management and comanagement. In both cases, we found favorable conditions in the communities, the external political arena, and in government to support the rebuilding goals of the organizations working in the two regions. Although both areas would benefit from greater financial resources, the most critical need is for external support in the form of alliances, issue networks, and access to multiple sources of power."

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.405

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.196
Teacher spread0.183 · 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 designQualitative
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

Citations0
Published2014
Admission routes2
Has abstractyes

Explore more

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