Development Framework for Performance-Based Output Specifications to Encourage Innovation in Public-Private Partnerships
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Public-Private Partnerships (PPPs) have been emerged as a successful delivery approach for driving large-scale infrastructure projects to provide affordable services and to meet the public requirements. The successful development of performance-based output specifications (PSOS) for PPP infrastructure projects have been under the attention of many procurement agencies and public authorities. Many diverse groups from both public and private sector believe that the current practice of PSOS needs to be enhanced. The lack of guidance to ensure that the performance is properly linked with the designed end product is identified as the major challenge to develop a high quality PSOS. In this study, a set of performance criteria and a generic framework for developing high quality PSOS based on the hierarchy of system engineering approach is proposed. Moreover, two infrastructure projects were considered as case studies to evaluate the PSOS implemented and to compare the results obtained, with the proposed framework.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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