Value for money factors in Indian public-private partnership road projects: An exploratory approach
Why this work is in the frame
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Bibliographic record
Abstract
For the Government projects, Value for Money (VFM) is an important parameter based on which the projects are procured through Public-Private Partnership (PPP) by the public sector. The objective of this paper is to identify and evaluate perceptions of VFM factors affecting Indian road projects undertaken by PPP. Eighteen VFM factors were shortlisted through a literature survey and were validated with experienced professionals. A questionnaire survey was conducted to investigate the most important VFM factors and was grouped into three categories: financial implications, the expertise of the private sector, and contract efficiency using factor analysis. Important VFM factors were identified using the Importance Index Method. The perception was analyzed with various statistical tools. The findings from this study provide more information and understanding about VFM in an early stage, which will be helpful for decision making about PPP.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.006 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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