Assessment of p otential socio-economic imp acts of the West Sumatra -Riau toll road: a comp rehensive study for the city of Payakumbuh, Indonesia
Bibliographic record
Abstract
The West Sumatra - Riau toll road is expected to generate a favourable influence on the local economy, thereby enhancing the overall wellbeing of society. However, this progress does not eliminate some of the potential negative impacts, because the construction of toll roads will divert some of the public's transportation movements, thereby posing a threat to business activities along the diverted transportation routes. To anticipate these potential impacts, it is important to conduct a study that focuses on anticipating the potential socio-economic impacts of the construction of the West Sumatra – Riau toll road. A Focus Group Discussion was conducted with delegates from several Payakumbuh Municipal Government. A total of nineteen participants, comprising ten males and nine females, participated in the focus group discussion. The discussion remarks were methodically categorised and analysed. The study findings elucidate many potential ramifications of the construction of the West Sumatra - Riau toll road on Payakumbuh City, as well as proposed measures that might be implemented to mitigate these ramifications. The research findings can serve as a foundation for developing a regional development strategy for Payakumbuh City. The objective is to optimise the effects of toll road construction on the social and economic well-being of the community, ensuring equitable and balanced outcomes.
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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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".