Bibliographic record
Abstract
This research aims to develop a strategy to increase community participation in instigating a Detailed Spatial Plan (RDTR) for the Southern Region of Kota Denpasar to minimize deviations during its implementation.This research used a mixed method, preceded by a qualitative data collection, and then progressed to a quantitative data collection.Distribution of questionnaires aided both started in January and ended in May 2024.Three forms of analysis are used: qualitative descriptive analysis, interval analysis, and SWOT.Study findings show that the stage of community participation falls into the category of consultation level -the fourth step on Arnstein's participation ladder.This is included in the degree of tokenism category.Based on the internal-external (IE) matrix analysis results in SWOT, the position of community participation is in cell II.The appropriate strategy to be used is the growth and development strategy.At this stage, the required actions are either intensive (information, dissemination, strengthening regulations, and innovation) or integrative (controlling information, strengthening human resource capacity, and cooperation/partnership).This research also leads to a range of opportunities to conduct further studies discussing community participation in policy conformance, land utilization control, and the application of e-participation and partnership.
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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 | 0.003 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.009 |
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".