Bottled Water Use On the Land: Economic, Social and Policy Implications of Water Consumption Choices While Pursuing Livelihoods and Undertaking Recreational Activities
Bibliographic record
Abstract
Defensive expenditures on bottled water for home use are related to: incomes, aesthetics (taste, convenience) and health risk perceptions (Dupont and Jahan, 2010; Lloyd-Smith et al., 2014). The previous literature is silent on two issues of relevance to WEPGN’s mandate of improving understanding of water’s role in Canadian society and economy. The first issue is identifying what are the determinants of water consumption choices on the land (particularly, water used in pursuit of livelihoods and/or recreational activities that require travel from home, including trapping, hunting and fishing practices). The second is an investigation of water choices and health risk perceptions of individuals in Canada’s Northern communities. Nickels et al., (2006) notes the use of bottled water by Aboriginal peoples as a substitute for streams/rivers due to perceptions of poor water quality. Project partners are interested in learning whether this is an increasing phenomenon in the Northwest Territories (NWT). This is of concern for two reasons: such expenditures may be wasteful for individuals and also result in potential pollution. The research team will design and implement a survey to elicit perceptions and relate them to defensive expenditures. Researchers will also examine methods for communicating and eliciting risk perceptions to provide the project partners with knowledge to improve communications about water quality. This research will inform decisions around programming, specifically, source water protection planning.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".