Organization Intelligence and Bureaucracy Reform at Public Organization in Indonesia
Bibliographic record
Abstract
Organization intelligence and bureaucracy reform are important part of public administration. It is values and credibility agreed (the shared value and beliefs) which is learnt, applied continuity becoming main characteristic as guidance for organization members have behaviors, concurrently increasing its performance. It achieved through bureaucracy reform. In taking an easy way of explaining and more operational bureaucracy reform, thus government proclaims nine programs of acceleration bureaucracy reform. Illustrating paradigm changing, organization structure, management, policy, framework term and human resource intelligence work that are guided to budget conserving, rectifying public service quality, stimulating government performance mechanism efficiently and effectively. Tidying up of organization intelligence by one of its dimension is the difficult act into bureaucracy reform implementation while compared with intelligence process, structure and procedure. This research is done by applying descriptive methods of qualitative analysis include in a case study research. The result shows that one of public organization has implemented integrity values, professional and accountable in an internal area of nine programs on bureaucracy reform acceleration. There are nineteen activities becoming part of following up of these programs that totally reflect on an organization intelligence dimension, the suggestion of this model and able to overcome obstacle factor. In accelerating realize apparatus whose have integrity, professional and accountable need a lot of activities as following up of survey result of nine programs on bureaucracy reform acceleration program both of internal or external areas cooperate with independent institution.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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".