MétaCan
Menu
Back to cohort
Record W4387906253 · doi:10.4324/9781003453192-4

Resource Management and Spatial Competition in Newfoundland Fishing: An Exploratory Essay

2023· book-chapter· en· W4387906253 on OpenAlexaboutno aff
Raoul Andersen, Geoffrey Stiles

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFishingCompetition (biology)FisheryResource (disambiguation)BusinessGeographyComputer scienceEcologyBiology

Abstract

fetched live from OpenAlex

This chapter explores the nature and limits of the application of such ‘resource management’ in traditional Newfoundland fishing, and beyond that to analyse the kinds of contemporary events which may influence this phenomenon, so that we may more adequately understand the recent reactions by fishermen and industry to the exploitative threats of ‘outsiders’. The greatest amount of eco-spatial competition in fishing centred on being first in effectively positioning the more mobile techniques employed, e.g. handlines, trawls and gillnets. The production and support operations of the offshore fishery also represented a source of seasonal employment and/or supplementary income for those participating in the inshore fishery, or permanent employment for many who decided to seek a living outside the inshore fishery. The foregoing examination of traditional approaches to marine resources and recent development effecting increased resource competition in Newfoundland fisheries has distinguished between resource and spatial management.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.297
Threshold uncertainty score0.598

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.004
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.225
Teacher spread0.205 · 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 designNot applicable
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

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicMarine Bivalve and Aquaculture StudiesFrench-language works237,207