Analysis of Policies and Implementation of Railway Crossing Regulations in Indonesia: A Multi-Stakeholder Approach to Enhance Compliance and Safety
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examines the implementation of railway crossing regulations in Indonesia, employing a multi-stakeholder approach to enhance safety and compliance. Utilising a quantitative methodology, the research surveyed 500 respondents across various stakeholder groups. Structural Equation Modelling-Partial Least Squares analysis revealed that a multi-stakeholder approach significantly influences the effectiveness of regulation implementation (β = 0.68, p < 0.001). Inter-agency coordination emerged as the second most crucial factor (β = 0.55, p < 0.001), mediating the relationship between the multi-stakeholder approach and implementation effectiveness. The study also found a strong correlation between implementation effectiveness and regulatory compliance (β = 0.71, p < 0.001). Whilst community involvement and technology integration showed smaller influences, they remain significant contributors to implementation effectiveness. Notably, perceptions were consistent across stakeholder groups, indicating a shared understanding of key issues. The findings underscore the need for collaborative platforms in policy formulation and implementation, increased investment in technology and community engagement programmes, and adaptive regulatory frameworks that accommodate Indonesia's diverse contexts. This research contributes to the literature on transportation safety in developing countries and provides empirical evidence for policy reforms in railway crossing safety management in Indonesia.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it