Energy Conservation in the Canadian Residential Sector : Revealing Potential Carbon Emission Reductions through Cost Effectiveness Analysis
Bibliographic record
Abstract
The study uses Cost Effectiveness Analysis (CEA) as a method to analyse the economicand environmental impact of carbon dioxide (CO2e) emission abatement projects in theCanadian residential sector. It includes the more traditional environmental andeconomic criteria, yet it incorporates a behavioural component to the analysis. Adetailed account of the environmental specifications, emission reductions, and economicconsiderations of 11 abatement projects are used as input for the CEA. In addition,behavioural variables, such as disposable income, home ownership, and home repairskills, are taken into account to complement the study.The results indicate that the implementation of several of these carbon abatementprojects, such as insulating hot water pipes, replacing incandescent light bulbs,installing a programmable thermostat, etc. can bring about large emission reductionstogether with a net economic benefit, and in most cases, without altering the levels ofcomfort. This method can serve as a template for the evaluation of other related projectswithin the climate change mitigation context in Canada and in other countries, in anattempt to increase adoption rates of such projects.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".