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Record W4210616620 · doi:10.15173/glj.v13i1.4456

Structuring Workers' Bargaining Power in Mexico's Strawberry Fields

2022· article· en· W4210616620 on OpenAlexvenueno aff
Matthew Fischer-Daly

Bibliographic record

VenueGlobal Labour Journal · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsnot available
Fundersnot available
KeywordsCollective bargainingSettlement (finance)Power (physics)Bargaining powerStructuringCollective actionWageRepresentation (politics)FellProduction (economics)Labour economicsEconomicsBusinessPolitical sciencePoliticsLawGeographyMicroeconomicsFinance

Abstract

fetched live from OpenAlex

Workers shut down production and transportation of strawberries during the peak of the 2015 harvest in San Quintín, Mexico, which supplies winter berries to US markets. In the years since the strike, strike-settlement wage increases have eroded, commitments to register workers in the national social security system fell far short, and no workers gained representation by a union in collective bargaining with their employer. This case analyses the limited strike outcomes and persistent gaps in labour law compliance based on interviews and observation in 2019 and 2020. Building on the power resources approach, it highlights the historical character of structural power. Falling short of achieving strike demands underscored constraints on workers’ disruptive capacity. The case suggests that reading structural power as a dynamic complex of actions by employers, national states and workers enhances the concept’s ability to predict effects of collective action on social relations of production. KEYWORDS: Mexico; agriculture; supply chains; bargaining power; structural power

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.252
Teacher spread0.240 · 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 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

Citations7
Published2022
Admission routes1
Has abstractyes

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