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Record W2468881232 · doi:10.29173/cjs22284

Migration Management, Disciplinary Power, and Performances of Subjectivity: Agricultural Migrant Workers’ in Ontario

2016· article· en· W2468881232 on OpenAlexaffvenueabout
Tanya Basok, Danièle Bélanger

Bibliographic record

VenueThe Canadian Journal of Sociology · 2016
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversité LavalUniversity of Windsor
Fundersnot available
KeywordsDisciplineCoining (mint)SubjectivitySociologyAgriculturePower (physics)MobilitiesGender studiesSocial scienceGeography

Abstract

fetched live from OpenAlex

Agricultural migrant workers, recruited to work in Canada under the Temporary Foreign Workers Program (TFWP), are disciplined to be compliant and productive. Based on ethnographic data, we draw attention to several ways in which Spanish-speaking migrants, employed in agriculture in a rural community in Southwestern Ontario, respond to this disciplinary power. Most migrants discipline themselves and others to be productive and compliant workers. We refer to these acts as “performances of self-discipline.” At other times, some (albeit, few) migrants challenge this disciplinary power either individually or collectively. We refer to these performances of subjectivity as “performances of defiance.” Another way migrants may respond to the disciplinary power is by attempting to escape from it. Coining these performances “performances of escape,” we discuss how some agricultural migrant workers drop out of the program and remain in Canada without authorization. By turning attention to these performances of subjectivity, the article fills a gap in the literature on migration management and its disciplinary practices in Canada.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.789
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.041
GPT teacher head0.326
Teacher spread0.284 · 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

Citations39
Published2016
Admission routes3
Has abstractyes

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