MétaCan
Menu
Back to cohort
Record W1979804533 · doi:10.1080/08941920903229254

Broadening Participation in Fisheries Management Planning: A Tale of Two Committees

2010· article· en· W1979804533 on OpenAlexaffabout
Neil Davis

Bibliographic record

VenueSociety & Natural Resources · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFisheries managementStakeholderGroundfishBusinessPlan (archaeology)FisheryAdvisory committeeEnvironmental resource managementPolitical scienceEconomicsPublic relationsGeographyPublic administrationFishing

Abstract

fetched live from OpenAlex

Management agencies increasingly seek to broaden stakeholder participation in fisheries decision making beyond commercial fisheries groups. This precipitates the challenge of meaningfully involving additional stakeholders without unjustifiably diminishing the role of commercial users. This research examines participants'; evaluations of one attempt to broaden but balance participation in groundfish management planning on Canada's Pacific coast. Commercial fishery and noncommercial fishery stakeholders were separated onto two advisory committees with more and less control over the design of the management plan, respectively. Respondents from the noncommercial fishery committee were accepting of this asymmetrical arrangement, provided they had sufficient opportunities to influence the design of the advisory process and define overarching objectives that would bound potential outcomes. Findings suggest several reasons that involvement in these early steps may be particularly important to meaningful participation of noncommercial fishery stakeholders within asymmetrical, multicommittee processes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.289
Teacher spread0.273 · 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.

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

Citations7
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueSociety & Natural ResourcesSame topicMarine and fisheries researchFrench-language works237,207