KAJIAN PERBANDINGAN KEBIJAKAN PEMERINTAH LOKAL DAN STRATEGI PARTISIPASI PUBLIK
Bibliographic record
Abstract
This research tries to explain development policies of urban affairs area that seen based on public involvement strategy in course of city development planning. This research was aimed at identifying: (1) characteristic of economy social area compared; (2) strategy difference developed at two local governments based on: (a) government openness; (b) public participation; (c) environment communities empowerment; and (d) willingness and public agreement. Research method used in this policy comparison study is descriptive method passes literature study by using documentation technique. Analysis towards a success data collected done to pass test of two samples (independent sample test). Finding shown that Canada adapted a scope broader from public participation technique relates to: willingness and public agreement, environment and strategic plan, and e-government. While America shown, that more possible to promot e public participation passes mechanism likes referendum and annual society meetings towards public rumors. In public policy process, brainstorm about policy communities become s an ideal design for future policy process that can accommodate participation values, collectivities, inclusively, and the most important, sustainable. For that reason next forwards need government behaviour reorientation (public government) and society (including civil society and private sector inside), that the power not only belongs to the government, but be networking balance also between stakeholders in every public policy process, no exception in urban affairs development context. Kata Kunci: Policy comparison; participation; local government
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".