Current practices in private water well management in Rural Central Alberta
Bibliographic record
Abstract
Approximately 238,000 to 450,000 Albertans rely on private water wells for their water needs. In Canada, private well owners are responsible for monitoring and maintaining the quality of their water well, yet studies in Alberta indicate that owners do not undertake regular well maintenance or testing. This survey obtained information regarding farming and water well management practices, and drinking water preferences among private well owners in central Alberta. Questionnaires, water samples and drilling report information collected from 97 respondents between March 2015 and June 2017 were evaluated. Total coliforms were present (TC+) in 20/97 samples. There were no significant associations between well design and construction characteristics and the presence of TC+. Twenty-four and 20 respondents reported undertaking annual bacterial and chemical testing, respectively. Twenty-five respondents indicated their well had been shock chlorinated within the past three years. Concern about contamination (n = 28) was not significantly associated with increased frequency of water quality testing, well maintenance with shock chlorination, or purchasing of bottled water as an alternative drinking water. There has been little change since 2010 in the uptake of free water testing provided by Alberta Health Services. The organoleptic properties of water reported by respondents indicated shock chlorination might benefit a number of premises. Poultry producers are more likely to test their well water for bacterial and chemical contamination on an annual basis due to mandatory requirements stipulated by the poultry industry. There may be potential for a similar mandatory water testing guideline to be implemented for beef producers in Alberta. There is a need for education programs targeting rural well owners. The Working Well program information packages provided by the Government of Alberta provide an excellent source of information for water well owners. This survey indicates that new ways to disseminate this information to a broader audience are required.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.003 | 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".