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Record W2343201504 · doi:10.1080/08865655.2016.1165132

Agribusiness and Informality in Border Regions in Europe and North America: Avenues of Integration or Roads to Exploitation?

2015· article· en· W2343201504 on OpenAlexvenueno aff
Travis Du Bry

Bibliographic record

VenueJournal of Borderlands Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsAgribusinessNegotiationWork (physics)Social capitalEthnographyImmigrationPolitical scienceEconomyProduction (economics)Capital (architecture)Socioeconomic statusEconomic growthAgricultureEconomic geographyGeographyRegional scienceSociologyEconomicsPopulation

Abstract

fetched live from OpenAlex

Agribusiness is a globalized industry typified by capital-intensive, large-scale production for domestic and foreign markets. The employment of both migrant and immigrant laborers, and the informality that surrounds use of these laborers, are important components to such production. This paper examines the adaptation to and negotiation of farm laborers in informal markets in conjunction with the socioeconomic development of rural communities in border regions. I present ethnographic research from two important border production zones: the Coachella Valley of Southern California in the United States, and the Campo de Dalías in Almería Province, Andalucía, Spain. Through comparison of these cases, I explore two interrelated aspects of informality in the agribusiness industry: obtaining work and finding a place to live. Establishing and maintaining social networks are key to overcoming social consequences that arise out of agribusiness practices, but their resolution differ in the Coachella Valley and Campo de Dalías. I conclude by discussing the implications of the comparison and possible avenues for further research.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.887

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.060
GPT teacher head0.366
Teacher spread0.307 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations9
Published2015
Admission routes1
Has abstractyes

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