An Added Dimension for the Cost of Retrofits: A Social Life Cycle Assessment of Single-family House Retrofits
Bibliographic record
Abstract
Residential retrofits are a way to make older houses more energy efficient in an effort to decrease emissions. To encourage homeowners to retrofit, governments have implemented financially based programs that have been assessed based on potential to decrease emissions; this leaves the social cost of retrofitting unassessed. The novel application of social life cycle assessment (SLCA) to single-family house archetypes and their retrofit scenarios in Toronto, ON was performed to provide insight into the social and socioeconomic impact of retrofitting on society, occupants and workers. EnergyPlus was used to simulate 26,244 retrofit scenarios and extract energy use, mechanical and geometric data. Based on the partial SLCA, it was found that a maximum of just over 5 years of occupants’ full health were lost, while 4.75 years for society and 16 years for workers were gained by retrofitting. A comparison of recommendations based on SLCA results, heating and cooling energy use intensity (EUI) and cost-benefit showed the need to include social costs in feasibility studies of construction projects. It was found that site specificity in SLCAs go beyond determining thresholds in impact assessment, to influence the breadth of potential impacts that are identified. The importance of audience and stakeholder involvement to increasing the effective use and value of SLCA results was illustrated. Findings contribute to the development of SLCA by providing another instance of application, identification of the difference it could make in decision-making, and the value that unique characteristics like site specificity and stakeholder involvement bring to SLCA results.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".