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Record W4365146828 · doi:10.1111/joac.12541

Discipline and resistance in southwestern Ontario: Securitization of migrant workers and their acts of defiance

2023· article· en· W4365146828 on OpenAlexaffabout
Chris Ramsaroop

Bibliographic record

VenueJournal of Agrarian Change · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsCanada Auto WorkersWorkers Compensation Board of British ColumbiaInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsSecuritizationAgricultureState (computer science)Resistance (ecology)BusinessMigrant workersFarm workersEconomic growthDevelopment economicsEconomicsGeographyFinance

Abstract

fetched live from OpenAlex

Abstract COVID‐19 has had deep impacts on a wide range of vulnerable communities in Canada. Migrant agricultural workers in the southwestern region of Ontario were particularly impacted. Fearing the threat of the ‘racialized foreign other’, the Canadian state produced myriad securitization responses with heightened surveillance. This paper will examine both state and non‐state forms of securitization and the response from both workers and activists such as the advocacy group Justicia for Migrant Workers (J4MW). While there has been ample discussion of how vulnerable migrant agricultural workers were affected during the pandemic, there has been less attention paid to how state policies have heightened and targeted specific groups such as migrant agricultural workers through modes of securitization. Central to this was to ensure that labour needs would be met to ensure the viability of Canada's multi‐billion agricultural industry. This paper shows how securitization and control were vital to ensure no disruptions to production levels and Canada's role as a leading agricultural export producer.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.056
GPT teacher head0.241
Teacher spread0.185 · 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

Citations8
Published2023
Admission routes2
Has abstractyes

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