Perencanaan Partisipasi Menuju Keadilan Sosial Studi Kasus Inklusi Sosial Orang Berkebutuhan Khusus Bagaimana Memberdayakan Orang Berkebutuhan Khusus dalam Perencanaan Transportasi
Bibliographic record
Abstract
Participatory planning for disabled people in transportation planning processes has become important. Because, it gives insight in what the disabled-peoples preferences are, improve decision making and advance justice. It is inline with regulation that United Nation made and also Traffic and Road Transportation Act No 9/2009 that Government of Indonesian was made. But, there are some barriers of participation to include disabled people; it can be time and money consuming. Other problems are related to the accessibility of facilities; physical impairment, unfamiliar procedure and willingness to participate by disabled people. It is important for the policy makers to know how to empower disabled people and increase their participation in planning processes by considering these barriers. This study investigates how to include disabled people in transportation planning processes. It provides lessons learned from United Kingdom and Canada as the best practice of inclusion disabled people in transportation planning processes. The inclusion of disabled people is analyzed based on a case study of Bus Rapid Transit-Transjakarta, Indonesia. Data were gathered using interviews, questionnaire, literature and document review. A descriptive qualitative analysis was used to analyze the data. The result show that applied participatory tools to empower disabled people in planning processes was not sufficient enough. A higher level of participation can be strived for by changing the legal framework, investments in accessible facilities, commitment of the government, and the network of organization at international, national, and local level. Last but not least, inclusion disabled people is hard to implement. But, at least we try to make social justice in our services.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".