Assessing occupant satisfaction and energy behaviours in Toronto’s LEED gold high-rise residential buildings
Bibliographic record
Abstract
Purpose – This paper aims to present four purposes: to assess occupant satisfaction with indoor environmental quality (IEQ); to determine if occupants appear to be operating their dwellings in an energy efficient manner; to suggest ways that occupant satisfaction and behaviour can help or hinder energy efficiency; and to show that the post-occupancy evaluation approach is an effective tool in diagnosing and improving satisfaction and energy efficiency in high-rise residential buildings. Design/methodology/approach – Beyond measuring occupant satisfaction with IEQ, this paper uses scores and user comments from occupant questionnaires to identify success and indicate frustration and/or confusion with particular building technologies. It also extrapolates the energy efficiency implications of these responses in four Leadership in Energy and Environmental Design Gold residential towers. Findings – The research highlights where problems occur, particularly with the adoption of new technologies which may not be well understood by the occupants. It also identifies behaviour patterns that may negate energy efficiency strategies. Research limitations/implications – The lack of dwelling metre data prevents this research from making causal links between behaviours and their energy implications. Also, the lack of Canadian benchmarks for satisfaction of occupants means that comparisons can only be made to cases from the UK, which is less robust. Originality/value – This type of work has never been done in Canadian residential high rise towers before. It helps to better understand the process of ensuring that occupants successfully adopt innovation that can lead to energy savings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".