Chinese Indonesians in a rapidly changing nation: Pressures of ethnicity and identity
Bibliographic record
Abstract
Abstract: Throughout periods of political instability and economic adversity – from Dutch colonial rule, through President Suharto's period in office, to more recent times – ethnic Chinese in Indonesia have been recurrent scapegoats for violence. Suharto, especially, manipulated local perceptions of the Chinese in the economic and political arenas, to suit the needs of his government. Yet, circumstances have changed since the 1998 riots in Indonesia and Suharto's departure. Subsequent presidents have introduced legislation aimed at reducing legal restrictions on Chinese Indonesians and they, in turn, are beginning to have greater public voice through a diversity of outlets. These include the growth of numerous new print and television media; a flourishing literature sphere; the rise of a variety of political parties, both ethnicity‐based and more wide‐ranging; and the development of non‐political organisations, some tackling discrimination and others focusing upon Chinese sociocultural needs. These channels are facilitating the appearance of new and re‐emerging ethnic Chinese identities, some surfacing from over 30 years of imposed dormancy. This paper is a preliminary investigation of manifestations of these identities among ethnic Chinese in Indonesia's contemporary public realm.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".