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Record W4302066903 · doi:10.47886/9781934874110.ch41

Pacific Salmon: Ecology and Management of Western Alaska’s Populations

2009· book-chapter· en· W4302066903 on OpenAlexaboutno aff

Bibliographic record

VenueAmerican Fisheries Society eBooks · 2009
Typebook-chapter
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipMemorandum of understandingGovernment (linguistics)FishingPolitical scienceEnvironmental planningMarine protected areaBusinessEnforcementFisheryEnvironmental resource managementPublic administrationSustainabilityGeographyEcologyHabitatLawEconomics

Abstract

fetched live from OpenAlex

<em>Abstract.</em>—Watersheds in the Pacific Northwest have been the site of conflicts over access to salmon by commercial, aboriginal, and recreational groups, as well as conflicts among salmon users and other users over how to protect or restore salmon habitat, maintain a sustainable harvest rate, and define research priorities. Watershed and salmon users have sometimes chosen to form partnerships to solve common problems, making the conservation or sustainable management of salmon their central objective. Through examining a British Columbia example which illustrates principles of successful collaborative partnerships, as well as some failures to apply these principles, I consider what aspects of the Canadian experience might contain instructive precautionary lessons relevant to the Arctic-Yukon-Kuskokwim area. Five critical key conditions identified from this examination needed for successful partnerships include: (1) clarification of the role of government as a sponsor (funder) but not a convenor of the partnership, (2) a Memorandum of Understanding clearly spelling out the goals, the rights and duties devolved to partnership bodies, and government commitment not to violate them, (3) fishermen involvement in, and oversight of, all aspects of citizen science, including data collection, analysis of data, creation of fishing plans, monitoring and enforcement of adherence to the fishing plans, research, agenda setting, and (5) sufficient time for parties to develop trust in the process and other parties.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.642
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.315
Teacher spread0.272 · 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 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

Citations0
Published2009
Admission routes1
Has abstractyes

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