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Record W3216180274 · doi:10.15273/jue.v11i3.11242

“We Become Capable of Handling Everything”: Gender and Gulf Migration in Kerala, South India

2021· article· en· W3216180274 on OpenAlexvenueno aff
Kathryn Gerry

Bibliographic record

VenueJournal for Undergraduate Ethnography · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipGender studiesAutonomyEthnographyEmigrationNarrativeSex workState (computer science)ModernityWork (physics)SociologyGeographyPolitical scienceHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

Women have a uniquely gendered experience with worker migration from Kerala, South India to the Gulf, a phenomenon which touches virtually every household in this state. Drawing on ethnographic fieldwork in Kerala, this article examines the intersections of gender and migration; I argue that migration fuels significant social change in terms of gender expectations and the role of women as economic agents. My fieldwork reveals that women work abroad due to personal circumstances and to conform to local ideas about modernity. Migrants’ wives also experience increased autonomy in their daily lives. These two categories of women, migrant women and the wives of male migrants, are attuned to others’ perceptions of their roles vis-à-vis migration. Despite occasional negative feedback, women report that they are empowered by worker migration. This project builds on scholarship examining the status of women in Kerala (Eapen and Kodoth 2003), the experiences of migrant spouses (Osella 2016), and female Christian nurses’ Gulf migration (Percot 2006). I extend this work by analyzing the personal narratives of individual women who work in the Gulf, head their own households in Kerala, and experience stigmatization because of emigration. Finally, I explored the broader implications of migration for the lifestyles and aspirations of women in Kerala.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.040
GPT teacher head0.321
Teacher spread0.281 · 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 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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

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