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Record W2884814417 · doi:10.5539/ass.v14n8p119

Voices of Indonesian Migrant Workers at Home and Abroad

2018· article· en· W2884814417 on OpenAlexvenueno aff
Howard Lorne Martyn

Bibliographic record

VenueAsian Social Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability, Governance, and Employment Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndonesianVocational educationGovernment (linguistics)PoliticsWork (physics)Economic growthIndonesian governmentWork abroadPolitical scienceSociologyBusinessPublic relationsBrain drainEconomics

Abstract

fetched live from OpenAlex

In this paper I discuss interviews conducted with Indonesian village women, concerning their decisions to sojourn abroad for work. The women detail three factors that they believe compel them to seek work abroad: lack of job opportunities, lack of educational and training opportunities and personal desire to experience life outside the confines of family and village life. They also raise the issue of government biases in educational and vocational planning that negatively affects villagers’ abilities to find employment within Indonesia, and particularly within rural environments.I also interviewed community support workers who mention political patronage as a factor in allocating funds for educational and training projects. Recent studies indicate that the Indonesian government has, for many years, prioritized formal education at the public-school level in urban centers and larger provincial towns, but that poorer rural villages lack access to similar opportunities. Many Indonesian women working in laboring positions abroad emanate from these poorer villages.Participant recommendations include delinking village educational funding from political patronage, and allocating more funds to remote villages, not only in terms of building more primary and secondary schools but also in terms of providing long-term vocational training, particularly for young adults, which, in combination with increased employment opportunities, may decrease the necessity to migrate.Data was collected through interviews and written journals in Indonesia and Hong Kong between 2005 and 2017.

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 categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.998

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 studies0.0030.010
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 head0.014
GPT teacher head0.319
Teacher spread0.305 · 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; both teacher heads agree on what is shown here.

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

Citations9
Published2018
Admission routes1
Has abstractyes

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