Study of Green Building Certification in Canada - Limiting Factors to Attain Net-Zero Standards -
Bibliographic record
Abstract
Countries around the world are aiming to reduce carbon footprint to halt climate change. The building sector being responsible for carbon emissions, green building certification programs establish the current standards in order to construct green buildings, and such programs gradually are regularly updated to have standard levels increased. The Leadership in Energy and Environmental Design (LEED) program is widely used in over 150 countries in the world, including Canada. With standards higher than LEED, programs such as the Living Building Challenge (LBC) program, targets net-zero waste, water and energy. This paper outlines the current state of green buildings in Canada and the limiting factors of these buildings to reach standards of net-zero waste, water and energy, such as described by the Living Building Challenge program. Firstly, the paper describes Canada’s current green building standards by analyzing data of LEED certified buildings provided by the Canada Green Building Council. Second, a thorough analysis of the scorecards of the Platinum level buildings will be analyzed to identify the limiting factors of these buildings to achieve net-zero standards. Results indicate that the major limiting factor for each category is Water is Innovation and Technology, for Energy is to Optimize Energy Performance, and for Waste is Building Reuse.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".