Determining a reasonable concession period for private sector provision of public works and service
Why this work is in the frame
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Bibliographic record
Abstract
The concession period is one of the most important issues to be addressed in private sector provision of public works and services through concession arrangements as it, to some extent, demarcates the rights and responsibilities between public and private sectors in a project's life cycle, and it is also critical to the project's sustainable development. This paper proposes a methodology for the determination of an appropriate length of the concession based on a win–win principle for parties involved and exercises simulation techniques in measuring and evaluating construction and economic uncertainties and risks. A case study of a hypothetical infrastructure project is provided to demonstrate the application of the proposed methodology, mathematical model, and simulation techniques.Key words: build–own–transfer, concession, critical path method, financial management, infrastructure, Monte Carlo simulation, partnerships, procurement, risk analysis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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