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Non-Citizenship at Work: Labour Flexibility Behind the Counter in Western Canada

2020· book-chapter· en· W4229866211 on OpenAlexaboutno aff
Geraldina Polanco

Bibliographic record

VenuePolicy Press eBooks · 2020
Typebook-chapter
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipPrecarityAusterityFlexibility (engineering)Labour market flexibilityPrecarious workImmigrationVulnerability (computing)Political scienceWageLabour economicsPoliticsWork (physics)Development economicsPolitical economySociologyEconomic growthEconomicsLawEngineeringUnemployment

Abstract

fetched live from OpenAlex

This chapter analyses the role of immigration controls in furthering labour flexibility and worker vulnerability in Canada and the way that this flexibility and vulnerability dovetail with austerity. Non-citizenship is an uneven and contingent category, with social locations amplifying or ameliorating a migrant's experience of precariousness. In addition to a normative political discourse that criminalizes migrants and/or sees them as problems to be 'managed', regulations governing work and citizenship increasingly intersect, generating new and compounding insecurities, with the form of labour precarity depending on the specific immigration controls and labour regulation. The chapter explores how features of a new labour regime in Canada in the era of austerity and the increased presence of 'temporary migrant workers' in the quick-service restaurant industry promote increased labour flexibility and exacerbate migrant workers' vulnerability. Migrant workers face unique challenges, distinct from those of their domestic counterparts, and with their growing presence in low-wage Canadian worksites, the need to organize at the intersection of work and citizenship has become an urgent project.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.306
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.127
GPT teacher head0.382
Teacher spread0.254 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2020
Admission routes1
Has abstractyes

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