MétaCan
Menu
Back to cohort

Normative Beliefs and Economic Life: A Case Study of the Fishing Industry in Two Communities in Rural Newfoundland

2021· article· en· W3177144115 on OpenAlexaffabout
R. Jeffrey Frost

Bibliographic record

VenueJournal of Fisheriessciences.com · 2021
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsQueen's University
Fundersnot available
KeywordsNormativeFishingResource (disambiguation)Fish <Actinopterygii>Corporate governanceInequalityAffect (linguistics)Fishing industrySociologyEconomic growthPolitical scienceEconomicsFisheryManagementLaw

Abstract

fetched live from OpenAlex

Abstract This paper seeks to outline the normative beliefs that fish harvesters in two communities in rural Newfoundland -Twillingate and Fogo Island, have about their economic lives. These beliefs have the potential to substantively affect communities’ engagement with resource governance and regulatory policies. Specifically, this paper examines three sets of beliefs. The first is how harvesters view the relationship between the resources they extract and the towns those resources sustain. The second looks at when inequality is acceptable or unacceptable in these communities. The third concerns the circumstances under which people should be able to buy or sell their right to harvest a resource. This paper uses 21 interviews with fish harvesters in Twillingate and Fogo Island, as well as evidence from previous anthropological and economic studies, to examine the harvesters’ normative beliefs and what impact they might have on policies and policymakers.

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)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.573

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.008
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.060
GPT teacher head0.376
Teacher spread0.316 · 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
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Fisheriessciences.comSame topicIndigenous Studies and EcologyFrench-language works237,207