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Racial Capitalism, Slavery, Labour Regimes and Exploitation in the Canadian Seasonal Agricultural Workers Program

2020· article· en· W3095132336 on OpenAlexvenueaboutno aff
Julie Ann McCausland

Bibliographic record

VenueCaribbean Quilt · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsComplicityRacializationAgricultureCapitalismLabour economicsAssertionWage labourWageFace (sociological concept)Political scienceEconomicsDemographic economicsBusinessEconomic growthSociologyGeographyLawPolitics

Abstract

fetched live from OpenAlex

This paper will attempt to critically examine Canada’s Seasonal Agricultural Workers Program (SAWP) with an intent of connecting four themes: the Canadian agricultural industry, indentured servitude, the labour regime in Canada, and the racialization of the SAWP. It has been argued that the workers from the Caribbean who participate in the Temporary Agricultural Workers Program are should consider themselves fortunate to be given such an opportunity. I argue that this assertion is problematic because it overlooks the hardship the workers face in Canada as a result of their non-citizen status. I also examine the fact that many of the workers enlisted in the SAWP are forced to migrate for a living wage due to poor economic conditions in their countries of origin, and that these conditions are a direct consequence of unequal trade policies and structural adjustment programs. Finally, I demonstrate Canada’s complicity in benefiting from these programs.

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)0.002
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: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.275

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.007
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.001
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 head0.025
GPT teacher head0.283
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

Citations2
Published2020
Admission routes2
Has abstractyes

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