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Record W2901070185

Justice on Our Fields: Can 'Alt-Labor' Organizations Improve Migrant Farm Workers' Conditions?

2018· article· en· W2901070185 on OpenAlexaboutno aff
Manoj Dias-Abey

Bibliographic record

VenueSSRN Electronic Journal · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessEconomic JusticeEnforcementWork (physics)AlliancePublic relationsLabour economicsPolitical scienceLawEconomicsEngineering
DOInot available

Abstract

fetched live from OpenAlex

This article examines how non-traditional labor organizations, also known as “alt labor,” can improve the working conditions of migrant farm workers in the United States and Canada. I consider the work of three labor organizations — the Agricultural Workers Alliance (Canada) (“AWA”), Justice in Motion (U.S.) (“JIM”), and the Coalition of Immokalee Workers (U.S.) (“CIW”) — by focusing on the variety of “legal engagements” that these organizations have to create better working conditions for migrant farm workers. I argue that labor organizations engage with the law in numerous ways, including: improving the rights consciousness of workers; supplementing the work of regulators to increase compliance; undertaking private enforcement of their own; instituting new rights and entitlements through court challenges; building and coalescing social movements; and designing and implementing private regulatory system. I find that the AWA and JIM perform important work to build the rights consciousness of workers and improve compliance with existing legal standards in ways which public regulators are unable to do. However, most workers do not bring forth claims because they fear employer retaliation. The CIW, on the other hand, has devised a private regulatory system that overcomes some of the limitations of public regulatory systems, for example, by allowing farm workers to vindicate their rights regardless of their migration status. Most importantly, the CIW’s private regulatory system requires business entities at the top of the supply chain to take responsibility for working conditions on farms. This system engages with the political economy of the food system because those businesses at the top of the supply chain are best positioned to effect working conditions. I conclude by suggesting that labor organizations actively trying to achieve justice on our fields, like the AWA, JIM and CIW, may point the way for a rejuvenated labor movement.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.135
Threshold uncertainty score0.269

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0170.012
Scholarly communication0.0070.004
Open science0.0020.008
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.011
GPT teacher head0.269
Teacher spread0.258 · 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 designQualitative
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

Citations35
Published2018
Admission routes1
Has abstractyes

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