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Record W3170600745 · doi:10.1002/psp.2487

The governance of the <i>Kafala</i> system and the punitive control of migrant domestic workers

2021· article· en· W3170600745 on OpenAlex
Rhacel Salazar Parreñas, Rachel Silvey

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePopulation Space and Place · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaNational Science Foundation
KeywordsPunitive damagesMigrant workersCorporate governanceFace (sociological concept)Political scienceBusinessSociologyLawEconomicsEconomic growthFinance

Abstract

fetched live from OpenAlex

Abstract In the United Arab Emirates, the kafala system binds migrant domestic workers to employment with one employer‐sponsor. While various studies have identified the labour conditions elicited by the kafala system, research has paid less attention to the forces that underpin workers' interest in accommodating the constraints of the kafala . This article examines the effects of two punitive legal mechanisms that discipline domestic workers to remain within the kafala : cancellation and illegalisation. To be cancelled means to have one's contract revoked by one's employer‐sponsor and consequently be forcibly deported; illegalisation is the consequence that migrants face if they choose to “abscond” from their sponsor‐employer without permission. By examining the punitive legal system in which the kafala system is embedded, this article contributes to understanding the legal mechanisms that discipline migrant domestic workers into servitude in the UAE.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.831
Threshold uncertainty score0.989

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 head0.006
GPT teacher head0.239
Teacher spread0.233 · 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