Achieving an 80% reduction in Ontario residential heating energy consumption by 2030: a tiered framework and preliminary implementation strategy
Bibliographic record
Abstract
The increasing prevalence of climate change impacts and rising energy prices has highlighted the need to achieve deep energy savings now. To accomplish this, stricter prescriptive performance requirements for residential buildings are needed. The intent of this work is to develop a framework and policy implementation strategy to achieve an 80% reduction in Ontario residential heating energy consumption by 2030. A tiered framework of consumption targets was developed using OBC 2012 SB-12 requirements as a baseline and sample compliance packages created for each tier. Construction costs for the baseline and each tier compliance package were estimated and simple payback periods determined. Impacts of fuel escalation rates on payback periods were also considered. Significant cost premiums were found between the baseline consumption and overall 80% heating energy reduction target. Lack of experience and perceived risk were found to be the greatest barriers to achieving the overall energy reduction target. A preliminary strategy and supporting policy tools was developed, taking into consideration the observed barriers to adoption.
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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 | 0.011 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".