Asimilasi sebagai Terjemahan Bentuk Adaptasi dalam Resiliensi Komunitas Kampung Kota di Kampung Sudiroprajan Surakarta
Bibliographic record
Abstract
Resilience is a concept that integrates between mitigation, adaptation and innovation. On a smaller scale, community-based resilience forms a translation of strong social capital. In Indonesia the majority of the urban community is formed in a container called Kampung Kota. Kampung Kota has the character of tolerance, cohesiveness, and solidarity. Kampung Kota becomes important to be used as research setting because with its characteristic, Kampung Kota able to produce its own value so that it can face threat, pressure and turmoil with its way. Kampung Sudiroprajan is one of the kampung Kota in Surakarta City that has unique resilience experience especially related to the relationship between Javanese and Chinese. This study aims to determine the concept of resilience that is formed in Kampung Sudiroprajan as part of the Kampung Kota community. Kampung Sudiroprajan can give an idea of resilience concept of community scale which tend to original and typical. This research uses case study methodology by exploring the form of resilience conducted in Kampung Sudiroprajan. This study found the uniqueness of adaptation process of Kampung Sudiroprajan community. Adaptation is translated in the form of assimilation. The assimilation resulted in the social condition of the society which tends to be more fluid, especially in the face of several times the events that become threats, pressure, and turmoil for the Chinese. Assimilation creates a new value that becomes the glue of the relationship for the Javanese Ethnic community and the Chinese Ethnic Community.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".