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Record W2462213582 · doi:10.1177/194277861400700109

Low-Wage Capitalism, Social Difference, and Nature-Dependent Production

2014· article· en· W2462213582 on OpenAlexaff
Raju J Das

Bibliographic record

VenueHuman Geography · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsYork University
Fundersnot available
KeywordsShrimpWageCapitalismProduction (economics)ReproductionAquacultureShrimp farmingAgricultureWork (physics)Low wageEconomicsLabour economicsFish <Actinopterygii>FisheryBiologyEcologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Internationally, neoliberalism is often associated with the export-oriented production of nontraditional agricultural goods from poorer to richer countries. Shrimp aquaculture is a very important aspect of this process. Economic geographers, sociologists, and others have critically analyzed the problems of shrimp farmers and the adverse environmental effects of shrimp aquaculture. But they have generally neglected a crucial dimension: the conditions under which men, women, and children work for a wage in producing shrimps. The story of shrimp culture has been, more or less, the story of the missing wage laborer. Drawing on in-depth interviews in India, this paper discusses the conditions of laborers in export-oriented shrimp culture. It shows how the export-oriented production of shrimps results in the reproduction of a working class that works for abysmally low wages and under very poor conditions. The exploitation and domination of aqualaborers happens in ways in which capitalist relations are mediated by place-specific relations of difference and the specificities of nature-dependent production.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

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 studies0.0030.025
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0000.001
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 head0.010
GPT teacher head0.236
Teacher spread0.227 · 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 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

Citations7
Published2014
Admission routes1
Has abstractyes

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