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Exchange Relationships in Inshore Fisheries<sup>1</sup>

2008· article· en· W2017527665 on OpenAlexaff
Sean Lauer

Bibliographic record

VenueSociological Forum · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTransaction costEthnographySocial exchange theoryContext (archaeology)Variety (cybernetics)FisheryInformation exchangeParticipant observationBusinessSociologyEconomicsMicroeconomicsGeographySocial scienceBiologyComputer science

Abstract

fetched live from OpenAlex

Research on the long‐term, informal exchange strategies of harvesters and dealers working in inshore fisheries has been important to theory surrounding economic exchange. In transaction costs economics, this research provides evidence for economic exchange governed by trust, and in exchange theory, it provides evidence for the emergence of cooperation and trust. In this article I examine the emergence of economic exchange relationships in the new sea urchin fishery. The research is ethnographic in nature, utilizing a variety of data sources including participant observation, in‐depth interviews, and existing quantitative data. I find that, just as experience or improved efficiency can have an impact on the emergence of trust between exchange partners, potential exchange partners can be deemed untrustworthy based on general characteristics unrelated to the particular individual. Once established, these assessments become part of the strategic context of exchange in the fishery.

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)0.005
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: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0030.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.159
GPT teacher head0.339
Teacher spread0.180 · 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

Citations4
Published2008
Admission routes1
Has abstractyes

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