Results of a Groundbreaking Integrated Delivery Project: Multi-Stakeholder Assessments and Lessons Learned from the Waaban Crossing Bridge
Bibliographic record
Abstract
The Waaban Crossing bridge project located in Kingston, Ontario, Canada, was delivered with an integrated project delivery (IPD) approach. In 2020, it was recorded that this project was the first major public infrastructure project in North America to be contracted with a tri-party agreement and managed through an IPD approach. The project stakeholders selected an IPD for various and differing reasons, including risk reduction, collaborative decision making, and fiscal transparency. As the project was completed in December 2022, project stakeholders can reflect on the outcomes and lessons learned. Online surveys and semi-structured interviews of project stakeholders surface hits and misses for the project. Project participants’ answers are revealed and documented to determine the extent to which initial goals and objectives for the project were realized. Data are collected individually, so that the unique perspectives of owner, designer, prime contractor, and specialty contractor are contrasted. The project was reported a success by all stakeholders, yet fundamental business drivers that can put entities at odds with one another were present. The findings can inform planners of IPD projects on how to manage project delivery and to structure financial incentives that address the business needs of all key stakeholders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.027 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| 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".