Impact of an Energy Efficiency Regulation in Northern Canada
Bibliographic record
Abstract
Extreme cold climates and Canada’s sparsely populated Northern regions have limited human and infrastructural capacity making it difficult to build energy-efficient homes. Despite such differences, homes are built based on codes and standards developed for Canada’s South. In 2008, a by-law was passed in Yellowknife, Canada requiring a minimum EnerGuide Housing (EGH) rating of 80 for all new single-family and two-family residential buildings. The EnerGuide’s Energy Rating Service (ERS) program is an energy assessment program for residential housing formerly known as the EnerGuide Rating for Houses (EGH). Homes are rated between 0 to 100; lower numbers represent homes that are less efficient and 100 represents an airtight and well-insulated house that is net-zero energy. 1002 homes from the City of Yellowknife evaluated since 1950s were studied from the ERS database, Performance metrics studied include energy intensity, EGH rating, ACH rating, window types, the thermal resistance of the building envelope, primary heating and hot water heating equipment’s efficiencies, total electricity used, and total energy used. The analysis identified the current state of housing in Yellowknife, past and present housing trends, and determined the effect of the city of Yellowknife’s new building by-law had on housing performance. The preliminary finding shows a pathway to significantly improve the energy efficiency of the housing stock in Yellowknife. This regulation shows other municipalities in Canada that legislations pushing energy efficient buildings can be very effective.
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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 | 0.000 | 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".