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Record W2038192962 · doi:10.1080/1343900032000117187

Setting the Scene Speaking Out: Chinese Indonesians After Suharto

2003· article· en· W2038192962 on OpenAlexaff
Sarah Turner

Bibliographic record

VenueAsian Ethnicity · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsMcGill University
Fundersnot available
KeywordsEthnic groupPoliticsMultitudeEthnic chineseIdentity (music)Political scienceGender studiesPolitical economySociologyColonialismLawAesthetics

Abstract

fetched live from OpenAlex

This article is an initial analysis of new and re-emerging expressions of identity among ethnic Chinese in Indonesia's contemporary public domain. As long ago as Dutch colonial times in Indonesia, the ethnic Chinese have frequently been the scapegoats for violence, especially during times of political uncertainty and economic hardship. Under President Suharto's rule the identity of the Chinese was politically contested further as Suharto manipulated local understandings of the Chinese in the economic and political spheres. However, since the 1998 riots and the downfall of President Suharto, things have begun to change, and ethnic Chinese are speaking out. Alternative discourses of identity have surfaced through a multitude of different avenues. These have included the actions of a range of political parties, some based on ethnicity, and others more broad-based; non-political organisations including those fighting discrimination and others examining Chinese socio-cultural needs; literature; and the print and television media. It is now, through such means, that new and re-emerging ethnic Chinese identities, some suppressed for more than thirty years, are becoming apparent.

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)0.002
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 score0.116
Threshold uncertainty score0.230

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0330.010
Scholarly communication0.0070.004
Open science0.0010.005
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.304
Teacher spread0.286 · 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

Citations35
Published2003
Admission routes1
Has abstractyes

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