Remembering Water: Immigrant water narratives in Waterloo Region
Bibliographic record
Abstract
What water priorities are embedded in the personal water narratives of immigrants in Waterloo Region? How can immigrant water meanings transform local waters? The purpose of this qualitative research was to understand immigrants’ diverse experiences of water and consider what immigrants might contribute to the Canadian water agenda. Fifteen adult immigrants in Waterloo Region were recruited through opportunistic and snowball sampling methods, drawing from the researcher’s personal connections with immigrant settlement organizations and the broader community. Participants offered their water narratives through oral history interviews and follow-up group discussions. Following a collaborative oral history approach, participants were invited to share authority in the thematic analysis of the water narratives. Research into water meanings, translocality, and placemaking offered a theoretical context for the interpretation process. During interviews and follow-up group discussions participants emphasized water’s sacredness and cultural importance, and voiced concerns about who controls water and how we—individually and collectively—can take more responsibility for water. As water practitioners and advocates strive for changes in local water culture, immigrants should not be overlooked as potential agents of change. This research indicates that immigrants may have strong motivations to protect Canada’s waters and contribute to placemaking efforts through which local waters can be restored and revered.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.015 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".