COMPARATIVE STUDY OF WATER CONSUMPTION PATTERNS IN BRAZIL AND CANADA
Bibliographic record
Abstract
Sustainable consumption of natural resources, particularly water, has gained prominence in global governmental agendas. Water, vital for food supply, hygiene, environmental equilibrium, and material asset maintenance, necessitates responsible management to ensure its availability for future generations. This underscores the need to comprehend consumer behaviors related to water, promoting sustainable practices. Motivational factors driving sustainable behavior adoption have been a focus of consumer behavior research. Contextual variables, encompassing social, economic, legal, political, and natural conditions, play pivotal roles in this context. Comparative studies exploring these factors in sustainable behavior adoption have gained significance, shedding light on how contextual designs stimulate sustainable behavior. Research has highlighted the importance of contextual influences on behavior intention and environmental awareness, emphasizing the role of norms, structural factors, environmental knowledge, and degrees of collectivity and individuality in driving sustainable behavior adaptation. This study contributes to the growing body of research in sustainable consumption by examining contextual variables and their impact on water-related consumer behaviors. Through a comparative analysis, it seeks to identify contextual designs that facilitate sustainable behavior adoption and shed light on the influence of norms, environmental knowledge, and collectivity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| 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".