Governance Regimes for Large Complex Projects
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a framework for building governance regimes for large complex projects. The framework is based on three sources: 1) a re-examination of a study of 60 large capital projects (Miller & Lessard, 2000), 2) the institutional, corporate, and project governance literatures and 3) interviews centered on the revision of the British Private Finance Initiative and on the development of the Norwegian project approval process. The literature tends to treat governance issues as being static, but project development processes and environments are dynamic. The governance regimes must adapt to the specific project and context, deal with emergent complexity, and change as the project development process unfolds. Learning to manage project governance regimes is difficult for organizations that are not involved in great numbers of large complex projects. The framework based on the progressive shaping of the project through the project development life cycle is designed to help overcome this dilemma.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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