Analysis of Construction Dispute Cases in Canadian Courts and Lessons Learned for Modular and Off-site Construction Contracts
Bibliographic record
Abstract
Construction projects involve several professionals from various disciplines over the contract duration; contract claims and disputes among various stakeholders are hence inevitable. Construction contracts become more complicated along with the increasing complexity in design, construction process, and construction technology. Recently, Modular and Off-site Construction (MOC) has gained popularity and expanded its global market shares. However, there are yet no standard contracts for MOC to this date. Stakeholders usually adopt pre-drafted standard contracts, originally structured for conventional construction, and modify them based on project requirements. In this respect, there is an urgent need to evaluate such contracts' suitability for MOC projects. This can be done by analyzing the contractual disputes and their root causes through the literature, litigation, and their correlation based on the features of the MOC. This thesis develops a comprehensive framework which consists of (i) developing a model composed of a comprehensive list of contractual dispute causes, as documented in the literature and classifying them; (ii) examining the critical factors by classifying the Canadian court cases to identify the major root causes of litigation disputes based on the proposed model; and (iii) identifying lessons to prevent the dispute causes in the MOC by evaluating the interrelations between the result of case analysis and Canadian standard construction contract documents. The Canadian court system at two levels (of Supreme and Superior Courts) has been scoped, and 191 cases have been selected and analyzed for this study. As a result, the finding of this thesis can help contract drafters/administrators and general contractors recognize common causes of disputes to enhance the contract administration and management in MOC when drafting and administering the contracts in the new projects.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".