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Record W2996262376

Globalization, Fisheries and Recovery

2013· report· en· W2996262376 on OpenAlexfundaboutno aff
Martha LaSalette MacDonald, Peter Sinclair, Deatra Walsh

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2013
Typereport
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsnot available
FundersResearch and Development Corporation of Newfoundland and Labrador
KeywordsGroundfishFishingGlobalizationContext (archaeology)FisheryFishing industryFish <Actinopterygii>BusinessFisheries managementEconomicsGeographyMarket economy
DOInot available

Abstract

fetched live from OpenAlex

This project looks at fisheries and fishing-dependent communities of western Newfoundland in the context of broader regional and globalization processes, \nespecially those affecting labour markets and markets for fish products. We hope to answer several inter-related questions: 1) How is the fishing industry functioning in the post-moratorium period and what are its future prospects? 2) How can we best understand the current situation of, and prospects for, communities that have been dependent on the fishery? 3) How have they adjusted to the collapse of the groundfish fisheries? 4) What new opportunities are being pursued and what challenges exist, particularly in terms of labour and markets? In the course of our research, we also found evidence of social and cultural change in these communities, which we will take into account as we address the core questions.

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)0.001
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.351
Threshold uncertainty score0.697

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.008
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.044
GPT teacher head0.282
Teacher spread0.238 · 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
GenreOther

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

Citations5
Published2013
Admission routes2
Has abstractyes

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