Comparison of Quebec’s Project Delivery Methods: Relational Contract Law and Differences in Contractual Language
Bibliographic record
Abstract
The province of Quebec, Canada, seeks to implement relational alternate project delivery methods to achieve sustainability and energy efficiency in public construction. However, the relational differences between the formal written parts of different delivery methods have yet to be analyzed and understood, as is the case with the relational aspects of contracts and the achievement of sustainable and energy-efficient infrastructure. Using a hermeneutic interpretation of Macneil’s relational contract norms and grounded theory, 26 contracts involving Quebec’s largest public client of vertical infrastructure and representing three different types of project delivery methods (design–bid–build (DBB), design–Build (DB), and construction manager–general contractor/integrated project delivery (CMGC/IPD)) were analyzed using NVivo. It was found that CMGC/IPD is the most relational project delivery method available to Quebec’s public clients, namely because of the public client’s active involvement in the realization process, the increasing complexity of roles, the multitude of common management structures, and the internalization of sustainability measures and conflict resolution. Furthermore, Quebec’s CMGC/IPD was found to be an IPD-ish delivery method, lacking the early involvement of the construction manager and the risk/reward sharing mechanisms necessary to achieve pure IPD status. The findings and theoretical considerations discussed here will help policymakers, contract drafters, and public clients interested in implementing relational contracting practices in public construction projects.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".