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Record W3096545240 · doi:10.3167/ares.2020.110107

New Materialist Approaches to Fisheries

2020· article· en· W3096545240 on OpenAlexaff
Lauren Drakopulos

Bibliographic record

VenueEnvironment and Society · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBycatchMaterialismNormativeFisheryFisheries managementSustainabilitySociologyPolitical scienceEnvironmental ethicsEpistemologyFishingLawEcologyPhilosophyBiology

Abstract

fetched live from OpenAlex

For the past 40 years, bycatch has been a significant focus of fisheries science and management, yet bycatch has evaded clear definition persisting as a perennial fisheries concern. This article brings insights from new materialism to examine the ontological politics of bycatch. Building on new materialist approaches to oceans and fisheries, the article contributes to the bycatch debate by putting forth a new framework for understanding bycatch as multiple, enacted through the material-discursive practices of science and policy. Through a survey of policy and scientific documents, the article traces the emergence of “bycatch” as a global fisheries issue. The analysis broadens the orderings and normative understandings about human and nonhuman life inflected by post-humanist and new materialist traditions, as well as fisheries science and policy.

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)0.008
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0050.052
Scholarly communication0.0080.012
Open science0.0020.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.091
GPT teacher head0.248
Teacher spread0.156 · 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.

Study designTheoretical or conceptual
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

Citations4
Published2020
Admission routes1
Has abstractyes

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