Environmental attitudes and energy consumption among tenants in a high-rise multi-unit residential building in Toronto, Canada
Bibliographic record
Abstract
The influence that environmental knowledge and belief have on people’s behaviour is one of the important issues in the fields of engineering, environmental study, management and other related areas. However, currently, there is not enough study on household energy use at an occupant level or on evaluation of elements that can affect household's energy use such as environmental knowledge and pro-environmental attitudes in Canadian MURBs. As such, studying household’s energy use and the interrelated effects on their energy consumption is believed to be a crucial step towards reducing energy consumption. Considering the significance of the issues stated above, the present study attempts to evaluate energy consumption and its possible correlation with environmental attitudes among the tenants of a Toronto high-rise multi-unit residential building. The research methodology is based on a quantitative survey method, and the focus of the study is on historical annual energy consumption from April 2011 to June 2013. The main tool for collecting data is a developed questionnaire, and Dunlap’s NEP scale is used for measuring environmental attitudes. With regards to data analysis, the survey data and historical energy consumption data from April 2011 to June 2013 were analysed. The statistical sample size consisted of the 50 tenants who completed the NEP survey from July 29 to August 18, 2014. The detailed statistical results show that there is a negative correlation between environmentally-conscious attitude and energy consumption of the participants which is in agreement with the study’s presented hypothesis. In essence, this means that having high environmentally-conscious attitudes towards the energy consumption has a positive effect on occupant’s energy consumption level.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".