Everyday complexity: A mixed-methods study of household and environmental dynamics influencing sustainable adoption of decentralized water systems in peri-urban northern British Columbia
Bibliographic record
Abstract
,This study examines factors influencing the adoption of decentralized water systems (DWS) in peri-urban northern British Columbia (BC), focusing on household dynamics and gender roles. Addressing a gap in research on DWS adoption in this context, the study is timely given growing climate-related pressures on water availability and the need for alternative management approaches. Using a mixed-methods design combining a systematic literature review and a case study, the research identifies and analyzes DWS adoption factors. The review revealed eight commonly studied factors: gender, age, income, education, rural/urban setting, sensorial perceptions, attitude, and environmental concerns. These informed an online survey with closed and open-ended questions, completed by twelve DWS specialists and thirty-three peri-urban users in Prince George, BC, between September and December 2024. Thematic analysis showed these eight factors were reshaped by lived experiences, resulting in four emergent themes that better reflect the complexity of DWS adoption in periurban northern BC: sociocultural and economic context, DWS knowledge, environmental context, and perceived health risks. Findings reveal that adoption is shaped not only by technical or economic factors, but also household decision-making, gendered responsibilities, and concerns about water safety, affordability, and sustainability. The study highlights the need for inclusive implementation strategies that reflect gender roles, local knowledge, and environmental values, supporting socially grounded, resilient water management in rural and peri-urban communities facing climate and infrastructure challenges.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".