Characterizing air source heat pump market segments: A Canadian case study
Bibliographic record
Abstract
Electric air source heat pumps (ASHPs) appear to be a key technology for decarbonizing space heating in existing residential buildings, yet their current market share in much of North America remains low. To explore how the potential future ASHP market may differ from the present one, we use a subset of data from the Canadian Home Heating Survey (n = 461) to provide a comprehensive characterization of three market segments of British Columbian homeowners: Pioneers (heat pump owners), Potential Early Mainstream buyers (homeowners currently willing to purchase an ASHP), and Late Mainstream buyers (homeowners currently unwilling to purchase an ASHP). We assess variable associations with market segments according to the Attitude-Behavior-Context theory, which posits that pro-environmental behavior is shaped by attitudinal, contextual, and socio-demographic factors. We also compare how market segmentation changes before and after respondents receive technical information on different home heating systems. Relative to Pioneers and the Potential Early Mainstream (PEM), we find that the Late Mainstream (LM) are generally lower income, lower educated, less environmentally- and technologically-oriented in their lifestyles, less open to change, less familiar with heat pumps and home energy efficiency, more negative in their perceptions about heat pumps, and less aware and supportive of policies aimed at reducing residential emissions. We also find that after respondents read technical information about home heating systems, approximately 10% of heat pump non-owners shift from the LM to the PEM; however, within the PEM, there is little growth in high willingness to adopt.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".