Development of a Management Framework for Rural Roads in Developing Countries
Bibliographic record
Abstract
During the past decade, considerable efforts have been made to valuate the benefits of investments in rural roads in developing countries. Although the outputs of those studies have led to a global rethinking of traditional road appraisal methods, limited attempts have been made to integrate these findings into the rural road management process. The problem that arises from the analysis is a missing link between the appraisal of the socioeconomic impact and the management of rural roads. The main objective of the present study was to develop a methodology that combined all key aspects required for the sustainable management of rural roads in developing countries. For this, social, technical, economic, political, and sustainability aspects must be considered at the different levels of the management process. A case study developed in Chile is presented to illustrate the application of the proposed framework at the strategic and the network levels. From the application it was concluded that it was possible to combine in a practical and integrated tool all key factors affecting the process of management of rural roads in developing countries.
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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 | 0.009 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".