Prevalence and Clustering Patterns of Pro-Environmental Behaviors among Canadian Households in the Era of Climate Change
Bibliographic record
Abstract
This study examined the prevalence and clustering patterns of pro-environmental behaviors that are conducive to socially and environmentally sustainable living among Canadians. Cross-sectional data from the 2015 Households and the Environment Survey (HES) were used. Prevalence was calculated by province and each pro-environmental behavior. Observed/expected prevalence ratios were computed to assess clustering patterns and logistic regression analyses were performed to examine the pairwise associations. Among 8816 Canadian households, prevalence of engaging in pro-environmental behaviors ranked as the following: engaging in green consumer behavior (88%), composting food/yard waste (84%), being active outdoors (82%), gardening (72%), and recycling electronics (45%). While only 14% engaged in ≤2 pro-environmental behaviors, 25.1% of Canadians engaged in all pro-environmental behaviors. By province, British Columbia was the greenest province (81%), followed by Ontario (77%) and Nova Scotia (76.9%) while the least green provinces were Newfoundland and Labrador (62.9%), Saskatchewan (69.2%), and New Brunswick (68%). The most apparent clustering of behaviors was found between recycling electronics and gardening (Observed/Expected: 3.65, 95% CI: 1.98–5.32). Pairwise associations between any two pro-environmental behaviors were statistically significant for all possible combinations (Odds ratios ranged 1.23–2.24). Prevalence of engaging in different sets of pro-environmental behaviors varied greatly by province. Sub-optimal clustering of pro-environmental behaviors and varying pairwise synergetic associations were observed in Canadian households. To promote more holistic, sustainable lifestyles and create sociocultural environments that are conducive to the environment in the era of climate change, future work should investigate barriers and opportunities in adopting more pro-environmental behaviors in Canadian households.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 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".