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Record W4328052067 · doi:10.1111/1467-9655.13911

Breeding sovereignty: the production of race, nature, and capital in Venezuela

2023· article· en· W4328052067 on OpenAlexfundno aff
Aaron Kappeler

Bibliographic record

VenueJournal of the Royal Anthropological Institute · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Society in Latin America
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsRace (biology)SovereigntyCapital (architecture)Production (economics)Political scienceHistoryEconomicsSociologyGender studiesAncient historyLawMicroeconomics

Abstract

fetched live from OpenAlex

Abstract This article explores the efforts of the Venezuelan government to improve food security and rural livelihoods with an experimental cattle‐breeding project. It investigates the activities of a state enterprise in the western plains and how the selective‐breeding practices of veterinary experts intersect with the logic of capital and biopolitics. Contributing to debates on the interaction between society and environment, the analysis suggests that ‘endogenous development’, or the reduction of poverty through internal markets, draws on systems of knowledge that treat the biology of animals as a field of intervention for the resolution of social contradictions. To reduce reliance on petroleum rent and food imports, Venezuelan experts have sought to create a new breed of cattle suited to the nation's diverse ecologies. But the knowledge systems which guide this project are embedded with a host of cultural and economic assumptions that subvert the successful application of this biotechnology. Ultimately, this article seeks to increase knowledge of the techno‐politics of resource states at the start of the twenty‐first century and the ways in which cultures of expertise impact food sovereignty.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.340
Teacher spread0.310 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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