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Record W3178510266 · doi:10.1111/joac.12441

Ocean frontier assemblages: Critical insights from Canada's industrial salmon sector

2021· article· en· W3178510266 on OpenAlexafffundabout
Christine Knott, Charles Mather

Bibliographic record

VenueJournal of Agrarian Change · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsMemorial University of Newfoundland
FundersOcean Frontier Institute
KeywordsFrontierResource (disambiguation)ScholarshipPoliticsAssemblage (archaeology)GeographyEnvironmental resource managementEconomicsPolitical scienceEconomic growthLawArchaeology

Abstract

fetched live from OpenAlex

Abstract The ocean frontier has become central to a range of new and emerging strategies aimed at realizing the potential of the ocean economy. The purpose of this paper is to critically examine the configuration of the ocean as a frontier and its role in transforming marine spaces through the case of salmon aquaculture in Canada. To this end, we engage with ‘frontier assemblage’, an analytic that is developed from scholarship on agrarian and extractive resource frontiers in Asia. We use this approach to identify and extend three interrelated conceptual sensibilities. First, we use ‘frontierization’ to suggest that ocean frontier spaces are not only articulated at leading edges. Instead, frontierization happens at indeterminate sites, including those that have undergone earlier rounds of capitalist resource extraction. Second, we explore how ocean frontier resource extraction is assembled in ways that are indeterminate, but not radically open. Using the case of salmon aquaculture in Newfoundland, we show how resource extraction could have been ‘otherwise’. Third, we critically assess the promissory politics that are key to the ocean frontier. We argue that the frontier assemblage analytic—and the sensibilities we use—provides an approach to critically assess strategies aimed at realizing the ‘untapped’ resources of the ocean frontier.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.218
Teacher spread0.181 · 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 designNot applicable
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

Citations11
Published2021
Admission routes3
Has abstractyes

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