Design, decision-making and trade-offs in the Centre for Sustainable Development (La Maison du développement durable) in Canada
Bibliographic record
Abstract
Abstract In order to fight climate change and reduce carbon emissions, professionals in the construction sector often strive for optimal mechanical / technical solutions and assume that a “best” solution exists at a given time and in a given place. But what happens in sustainable building projects when different sustainability or project objectives run at odds with one another? The Maison du développement durable or Centre for Sustainable Development (CSD) – a LEED platinum certified building — is recognized as one of the most sustainable buildings in Canada. This mixed-use building, conceived to be a social and environmental hub in downtown Montreal, houses 3000 m2 of office space and conference rooms. The design included a series of innovations, such as a five-storey biofiltering wall and an under-floor air delivery system. In 2018, the Fayolle-Magil Construction Research Chair in Architecture, the Building Sector and Sustainability from Université de Montréal and the Canadian NGO Équiterre partnered to conduct a post-occupancy evaluation (POE) of the MDD. The study focused on six functional and architectural aspects of the MDD and involved analyzing 12 integrated design workshops, dozens of project documents, and specifically gathering new data. The results show that finding what is “best” is not what happened in reality. Instead, professionals were required to make a series of trade-offs in decision-making. Some examples of these tradeoffs include: adaptability vs. cost, air quality vs. energy performance, shared spaces vs. building floorplate efficiency, and innovation in the design phase vs. long-term operations. This paper shows that tradeoffs adopted during the design phase impacted the MDD’s performance. The results of this study are not only valuable to the project’s partners, but also to the construction industry in general, offering insight into design compromises in sustainable office buildings.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".