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Record W3132012700 · doi:10.3389/fmars.2021.634484

Coastal Fishers Livelihood Behaviors and Their Psychosocial Explanations: Implications for Fisheries Governance in a Changing World

2021· article· en· W3132012700 on OpenAlexafffundabout
Evan J. Andrews, S. E. Wolfe, Prateep Kumar Nayak, Derek Armitage

Bibliographic record

VenueFrontiers in Marine Science · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of WaterlooMemorial University of Newfoundland
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLivelihoodCorporate governancePerceptionSustainabilityFisheries managementNarrativePsychosocialFisheryEnvironmental resource managementGeographyEconomicsPsychologyEcologyFishingAgriculture

Abstract

fetched live from OpenAlex

This research is a critical examination of the behavioral foundations of livelihood pathways over a 50-year time period in a multispecies fishery in Newfoundland and Labrador, Canada. Fishers make difficult decisions to pursue, enjoy, and protect their livelihoods in times of change and uncertainty, and the resultant behaviors shape efforts to advance sustainability through coastal and marine fisheries governance. However, there is limited evidence about fishers’ behavioral changes over long time periods, and the psychosocial experiences that underpin them, beyond what is assumed using neoclassical economic and rational choice framings. Our analysis draws on 26 narrative interviews with fishers who have pursued two or more fish species currently or formerly. Fishers were asked about their behavioral responses to change and uncertainty in coastal fisheries across their entire lifetimes. Their narratives highlighted emotional, perceptual, and values-oriented factors that shaped how fishers coped and adapted to change and uncertainty. The contributions to theory and practice are two-fold. First, findings included variation in patterns of fisher behaviors. Those patterns reflected fishers prioritizing and trading-off material or relational well-being. With policy relevance, prioritizations and trade-offs of forms of well-being led to unexpected outcomes for shifting capacity and capitalization for fishers and in fisheries more broadly. Second, findings identified the influence of emotions as forms of subjective well-being. Further, emotions and perceptions functioned as explanatory factors that shaped well-being priorities and trade-offs, and ultimately, behavioral change. Research findings emphasize the need for scientists, policy-makers, and managers to incorporate psychosocial evidence along with social science about fisher behavior into their models, policy processes, and management approaches. Doing so is likely to support efforts to anticipate impacts from behavioral change on capacity and capitalization in fleets and fisheries, and ultimately, lead to improved governance outcomes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.013
GPT teacher head0.257
Teacher spread0.244 · 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.

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

Citations20
Published2021
Admission routes3
Has abstractyes

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