Value for Money and Risk Relationships in Public–Private Partnerships: Evaluating Program‐based Evidence
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
Abstract Value for money – VfM (the provision of improved public infrastructure and services at lower cost) – is a central rationale for the deployment of public–private partnerships (P3s). However, it remains unclear how VfM is actually created in P3s. There are several issues that surround the ex ante evaluation conducted during P3 assessment, including: transparency of the process, engagement of stakeholders, potential restrictions on current and future public sector flexibility, and political influences that call into question the legitimacy of the process. This study examines these issues using Alberta's P3 projects executed since 2003, and interviews 35 key participants and stakeholders. The findings suggest that while the transfer of risk from the public to the private sector is a key driver of VfM, it may overstate the extent to which planning related risks can be transferred. This paper recommends enhanced VfM component disclosures and transparency as the evaluation process evolves. Furthermore, a more rigorous approach to risk conceptualisation and valuation should be adopted. Risk allocation should be about managing not only occurrence, but also impact of the risk factor. Finally, political interference must be moderated to allow for the optimal realisation of the best possible choices presented by P3 deployments.
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 | 0.012 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.000 |
| 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