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Record W2134596331 · doi:10.1177/0011392113484453

Migrating against all the odds: International labour migration of Bangladeshi women

2013· article· en· W2134596331 on OpenAlexafffund
Danièle Bélanger, Mahmuda Rahman

Bibliographic record

VenueCurrent Sociology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsWestern University
FundersInternational Development Research CentreUniversité Laval
KeywordsNegotiationGender studiesSociologyPerspective (graphical)OddsPoliticsOrder (exchange)Migrant workersStigma (botany)Demographic economicsPolitical scienceEconomic growthSocial scienceEconomicsPsychology

Abstract

fetched live from OpenAlex

Of all temporary unskilled migrant workers who originated from Bangladesh in 2010, women accounted for less than 3%. This extremely low proportion of women results from the numerous sociocultural, religious and political barriers women labour migrants encounter. Based on 23 in-depth interviews collected in 2009 in Bangladesh with former migrant domestic workers who worked in the Gulf region, the article argues that women actively negotiate these barriers prior to going abroad and upon return. Using a micro-sociological perspective of gender and family relations, the article shows that, depending on women’s family situation and relationships, they were more or less at risk of suffering stigma in the pre-departure and return stages of temporary labour migration. The article builds on a solid body of research that examines how international labour migration challenges the global and local patriarchal gender order. The findings show how international migration of women may unsettle the patriarchal gender order, but can also serve to further subordinate women after they return home.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.028
GPT teacher head0.331
Teacher spread0.303 · 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 source (direct Gemma or distilled Codex), 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

Citations54
Published2013
Admission routes2
Has abstractyes

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