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Record W4296299184 · doi:10.1016/j.marpol.2022.105281

Fishing safely during COVID-19 in Newfoundland and Labrador, Canada: Making it happen

2022· article· en· W4296299184 on OpenAlexaffabout
Barbara Neis, María Andrée López Gómez, Emily Reid‐Musson, Brenda Greenslade, David G. Decker, Joel Finnis, Christine Knott

Bibliographic record

VenueMarine Policy · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFishingLivelihoodScale (ratio)PandemicFisheryBusinessVulnerability (computing)Coronavirus disease 2019 (COVID-19)Work (physics)GeographyEnvironmental resource managementEngineeringEconomicsMedicine

Abstract

fetched live from OpenAlex

Globally, fisheries have been the site of multiple documented outbreaks of COVID-19. Existing studies point to the threat posed by the pandemic to livelihoods and health among migrant industrial fishery workers, small-scale fish harvesters, and fishing communities. They show the pandemic enhanced safety, economic, social and political layers of vulnerability in fisheries, while also showcasing examples of resilience. Case studies of COVID-19 response provide an opportunity to explore how existing organizational structures, leadership and networks in fisheries can enable the rapid co-development of customized strategies for fishing safely during large-scale global disruptions such as pandemics. This article contributes to our understanding of governance and fishing safety in small-scale fisheries during the early pandemic, examining the response of small-scale fisheries in the Canadian province of Newfoundland and Labrador. These seasonal fisheries successfully opened with regulator approval after a short delay and operated without documented COVID-19 outbreaks during 2020. Findings draw from key informant interviews with a safety sector association and union leader, complemented with insights from an anonymous online survey of small-scale harvesters. Interviews capture the organizational processes and resources mobilized to rapidly co-develop the COVID-19 Safe Work Practice Guideline. Online survey findings indicate that fifty-nine percent of respondents (crew and skippers) had no COVID-19-related concerns while fishing in 2020; older harvesters and owner-operators were significantly more likely to indicate concerns. When asked about the relative practicality of listed COVID-19 precautions, respondents commonly identified sanitization, reduced interactions with shore workers, social distancing, protection equipment, modifications to eating/rest areas, and reduced crew as impractical. These assessments are generally consistent with those of the interviewed leaders and the Guideline approach. This suggests the co-developed Guideline provided tailored and practical COVID-19 prevention strategies. Pre-existing governance structures and networks can help address small-scale fisheries vulnerabilities to pandemics by supporting co-development of organizational resources and evidence-informed prevention strategies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.723

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.021
GPT teacher head0.311
Teacher spread0.290 · 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

Citations3
Published2022
Admission routes2
Has abstractyes

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