Public Policy: Inconsistency of Online and Conventional Land Transportation Regulations in Indonesia on Social Conflict Implications
Bibliographic record
Abstract
This scientific journal research analyzes a public policy on regulatory inconsistencies made by public officials that cause social conflict in society. The research problem focuses on PM 12/2019 regulations with UULLAJ/2009. The research approach method was qualitative. Creswell defines the qualitative method as a research method based on a constructive perspective, that is various meanings; meanings that are constructed socially and historically to develop a theory or pattern. The researchers collected and developed open data, intending to develop themes from the data obtained. This research aims to describe in depth the facts related to the inconsistency of regulations made by public officials which have an impact on the conflicts between the riders of online-based motorcycle taxi and conventional motorcycle taxi as land transportation in Indonesia. The data collection technique used document study. The observations carried out were passive participatory observations because the researchers only visited the research location and observed any events that occurred related to the conflict between online GOJEK riders and conventional OJEK riders in the research site. The research used interactive data analysis technique. Activities in data analysis consisted of: (1) data reduction; (2) data presentation; and (3) conclusion/verification. Based on the research data, it could be concluded that there were inconsistencies of public policy regulations regarding motorcycles (two-wheeled vehicles), as online-based public transportation vehicles based on PM 12/2019 with UULLAJ/2009, Article 47. In this case, motorcycles are not included in the category of public transportation types. The immediate solution should be made based on the results of research on online-based land transportation to date in Indonesia, since it has not been regulated by regulations on public transportation. Moreover, the technology platform service providers can no longer deny that their services are actually public transportation services. Online-based land transportation must also be regulated in the form of laws and regulations on public transportation and under the law on road traffic and transportation. This indicates that Law Number 22 of 2009 on Road Traffic and Transportation needs to be revised, and at the same time provides a legal protection for the regulations related to online-based land transportation.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".