Evaluation and Strategy: Strengthening Indonesia Council of Representatives of the Regions
Bibliographic record
Abstract
The Council of Representatives of the Regions emerged through the 1945 Constitution third amendment. The Council of Representatives of the Regions intended to represent regional interests and regional society in the central legislation making processes and products, to perform checks and balances principle on The People’s Representative Council which is a political representation that brings and struggles the aspirations and interests of political parties at the central level. The Council of Representatives of the Regions also acts as a guardian of decentralization and regional autonomy. The most fundamental problem for The Council of Representatives of the Regions is its institutional weaknesses. In legislation weaknesses terms, budgeting, and supervision have affected The Council of Representatives of the Regions in maximizing its performances. The Law regarding Indonesia Legislative Branch does not mandate legislation as The Council of Representatives of the Regions tasks. This provision can not be used as a guideline to describe the scope of duties, which are the limits of their authority in The Council of Representatives of the Regions order. On the other hand, after the Constitutional Court Decision Number 92/PUU-X/2012 and Number 79/PUU-XII/2014 issued, the relations that were later present were the three-party discussion model of The People’s Representative Council-The Council of Representatives of the Regions-President (Tripartite). Based on those facts, this article focuses on the evaluation of 15 years of The Council of Representatives of the Regions establishment and strategy to strengthen it.
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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 | 0.028 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".