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Record W2899049904 · doi:10.1080/1070289x.2018.1537639

Narratives of exile twenty years on: long-term impacts of Indonesia’s 1998 violence on transnational Chinese-Indonesian women

2018· article· en· W2899049904 on OpenAlexafffund
Monika Winarnita, Carol Chan, Leslie Butt

Bibliographic record

VenueIdentities · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIndonesianDiasporaGender studiesPoliticsNarrativePsychological resilienceSociologyPolitical sciencePsychologySocial psychologyLaw

Abstract

fetched live from OpenAlex

In response to Indonesia’s 1998 riots, which included mass rape of Chinese-Indonesian women, many Chinese-Indonesian families sent their daughters out of country to try and ensure their safety. Drawing on interviews with Chinese-Indonesian women currently living in Singapore and Australia, this article considers the long-term effects on transnational families of this departure. In contrast to current views of Chinese-Indonesians as an affluent diaspora, we show Chinese-Indonesian women’s experience to be that of exile, living outside Indonesia with little possibility of permanent return. We illuminate the subtle and enduring effects of political violence on women’s marital, reproductive, and childrearing practices. Interviews reveal fragmented identities and contingent household formations which enabled family resilience for some but created long-term fissures for the majority. We argue for more critical attention to how gender mutually constitutes experiences of exile, and the long-term impacts of political violence on reproduction and family relations for Chinese-Indonesian women.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0130.010
Scholarly communication0.0040.004
Open science0.0010.008
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.296
Teacher spread0.284 · 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

Citations11
Published2018
Admission routes2
Has abstractyes

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