MENAKAR METAMORFOSIS NASIONALISME PERANAKAN TIONGHOA DI KELURAHAN KUTO PANJI DAN DESA LUMUT SEBELUM DAN SESUDAH REFORMASI
Bibliographic record
Abstract
Indonesian nationalism is constructed based on the concept of nativity in which the Chinese ethnic group is not included as a part of Indonesia as long as they do not assimilate themselves completely. The changes in policy and leadership also shift the position of Chinese ethnic group identity in Indonesia. Bangka Belitung is one of the regions with a fairly large population distribution of Chinese ethnic group. Lumut village and Kuto Panji sub-district are the regions with a large population of Chinese in Bangka. Therefore, this study aims to identify the changing of nationalism form of current half-breed Chinese. This research used the concept of nationalism proposed by Anthony D Smith who explained that nationalism is categorized based on two aspects, territorial region (sociological) and ethnicity (psychological). Furtherly, according to Smith, nationalism emphasizes more on historical and sociological explanations. However, the comprehension of this explanation is abstract that it includes emotion, symbol, memory, desire, social, and social psychological elements. This study used mix methodology. In addition, the source of primary data was obtained from observations, interviews, and questionnaires with 40 respondents in total, in which 20 respondents were from Lumut village, and 20 respondents were from Kuto Panji sub-district. The main finding of this study is the changing of nationalism of half-breed Chinese encounters several phases which are admitting being not purely Indonesian, self-acceptance, and admitting being Indonesian with state nationalism form. This study finds that age and education affect the nationalism of half-breed Chinese.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".