A study of the operationalization of management controls in United Kingdom Private Finance Initiative contracts
Bibliographic record
Abstract
Utilizing evidence from a United Kingdom (UK) road case study Private Finance Initiative (PFI) project, this article considers how the UK central government's infrastructure strategy is operationalized through accounting‐based performance measures and incentive systems, and articulates how the adoption of such systems is moderated by trust practices. The findings indicate that initial government policy objectives, translated as performance indicators in the case study, failed to offer adequate incentives for contractors and created tensions. However, controls were later developed through inter‐party trust practices for managing performance and relational risk. These findings have important implications for PFI policy and practice, including that negotiation can: (i) lead to pragmatic controls being introduced to foster cooperation and trust‐building; and (ii) provide opportunities for adapting the monitoring and incentive mechanisms. This study also contributes to the previous literature where PFI control systems were largely regarded as inadequate for dealing with unforeseen conflicts between parties.
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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 | 0.043 | 0.133 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".