MétaCan
Menu
Back to cohort

<scp>T</scp>he last generation? Perspectives of inshore fish harvesters from Change Islands, Newfoundland

2013· article· en· W1778463555 on OpenAlexaffvenueabout
Derek Smith, Kelly Vodden, Maureen Woodrow, Ahmed Khan, Bojan Fürst

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsUniversity of OttawaMemorial University of NewfoundlandCarleton University
FundersWorld Bank Group
KeywordsFishingRationalization (economics)FisheryBusinessFish <Actinopterygii>Fisheries managementCommercial fishingCompetition (biology)Natural resource economicsGeographyEnvironmental resource managementEnvironmental planningEconomicsEcology

Abstract

fetched live from OpenAlex

Abstract Our investigation examines the perspectives of fish harvesters on key challenges facing the inshore fishery in Newfoundland and Labrador. The findings, based primarily on in‐depth interviews with harvesters in the town of Change Islands, show that fishers are deeply concerned about ineffective regulations, low prices for their catch, and rationalization policies. They explain how existing regulations restrict traditional cooperative fishing practices and impose rules that are not suited for local environmental conditions. Low prices for fish landed, they argue, are caused in part by lack of competition among buyers and a bonus system that favours larger enterprises. These conditions, combined with policies aimed at reducing the fishing fleet and barriers to youth involvement, threaten the long‐term survival of coastal communities. Overall, current policies keep inshore harvesters on the sidelines of an increasingly industrialized fishery. Local fish harvesters have valuable local, place‐based knowledge that can be used to develop more effective fishery management policies and marketing strategies, and in this article we share their recommendations on how to build more sustainable fisheries. However, traditional fishing communities—along with the potential social, cultural, economic, and environmental benefits of smaller‐scale, community‐based fishing—need to become more visible for these changes to occur.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.010
GPT teacher head0.175
Teacher spread0.165 · 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 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

Citations13
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Geographies / Géographies canadiennesSame topicCoastal and Marine ManagementFrench-language works237,207