Risk-Based Comparison of Collaborative Delivery Methods in Canadian Construction: Progressive Design Build, Integrated Project Delivery and Project Alliancing
Bibliographic record
Abstract
In response to an aging infrastructure network, population growth, and the rising complexity of project delivery, Canada's infrastructure procurement landscape has undergone significant transformation in recent years.In light of this, collaborative project delivery methods, including Progressive Design-Build (PDB), Integrated Project Delivery (IPD) and Project Alliancing (PA) have recently gained traction in Canada as alternatives to traditional models by fostering teamwork, aligning commercial outcomes, and promoting collective accountability among stakeholders.This paper provides the results of a targeted review of existing literature on risk management characteristics of PDB, IPD, and PA across four dimensions: risk allocation and mitigation strategies, risk sharing and incentives and flexibility/adaptability in managing risk.The analysis emphasizes how these models address inefficiencies in traditional delivery systems by promoting collaboration and aligning risks and rewards equitably.To analyze the extent of adoption of the aforementioned delivery methods in Canada, this study surveys Canadian projects that have implemented PDB, IPD, or PA.The compilation of these projects forms a foundational database that supports future research on the influence of risk management practices on collaborative project delivery adoption and implementation in the Canadian context.This study identifies distinct risk management approaches across PDB, IPD, and PA, shaped by their underlying contractual frameworks.Preliminary findings from Canadian projects suggest that delivery method selection is influenced by sector-specific risk profiles and the level of risk integration each delivery method supports.
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How this classification was reachedexpand
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 | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".