The Arrangement of Dynastic Politics in Regional Head Elections in Indonesia
Bibliographic record
Abstract
The practice of dynastic politics has been going on for almost 20 years, arguably the first and longest-existing dynasty in Kediri Regency. The research questions in this paper are: how do political dynasties in Indonesia operate and maintain power? And how can political dynasties in Kediri Regency develop? This research explains the origins or history of this dynasty, which began with business affairs and then progressed to politics. In the development of this dynasty, only those closest to the party are capable and able to implement or continue programs that have been created and not yet implemented. Many relatives, from businessmen to officials, from the village to the regional level, are ready to help and serve this dynasty in order to obtain rewards. This dynasty will also continue to occur if the regulations or laws governing a democratic system do not undergo definite changes. Because of its inclusive and closed nature, a political dynasty is very difficult to find fault with. At first glance, there is nothing wrong with dynastic politics, especially when referring to the democratic principle that every citizen has the same right to be elected and to vote. However, it cannot be denied that the political dynasties that have developed so far have harmed the essence of democracy itself.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".