Community - Based Water Monitoring : Build Your Own Water Monitoring Logger
Bibliographic record
Abstract
Water security for Indigenous communities is an urgent issue. Approximately one third of Indigenous communities in Canada are currently grappling with safe drinking water access, compromised environmental water quality, and associated health issues. Surface water monitoring is often limited in rural and remote regions. This is in part due to the difficulty of accessing remote sites. Even when monitoring is conducted it is usually expensive and intermittent , with results that can be difficult for communities to interpret. There is a need for low-cost, appropriate technology that enables communities to conduct fresh water monitoring. Our Innovation This manual describes how to build a cheap, portable, robust surface water monitoring device. The device is called a “data logger.” It uses open-source technology: anyone can use this Manual to build the device. The logger has a simple design, and can be easily built and repaired with mail-order parts, hence well adapted for use by rural and remote communities. The device can be easily transported by users who are traveling on land or water, or installed at a stationary point. The approximate assembly time is 3–5 hours. The approximate cost is $600, substantially cheaper than commercially available data loggers. What does the data logger test? The logger records electrical conductivity (which is a proxy indicator for contamination) and GPS location. This allows users to collect water data at a precise location, and later return for additional water testing if necessary. This device is not intended as a substitute for lab tests or more sophisticated water monitoring. Rather, the device is designed to enable users to identify specific areas that require more detailed testing. Authors The idea for this logger originated at a Water Bush Camp organized by Caleb Behn (then-Executive Director of Keepers of the Water), in the traditional territory of Halfway River, Saulteau, and West Moberly First Nations at Carbon Lake in 2015. The logger is an adapation of a device built by Dr. Mark Johnson (UBC) to log and monitor water in remote and humid environments in the tropics. While the data loggers previously developed by Dr. Johnson’s group were stationary, the vast reaches of the north inspired a mobile unit that might be towed by a boat and used to sweep for potential contamination. Teddy Eyster, an MSc student working with Dr. Johnson, worked to adapt the monitor for mobile use and test the device in two locations in NWT and Manitoba. This manual was then written by a collective of authors associated with the Sustainable Water Governance and Indigenous Law Project, housed at UBC on the traditional, ancestral, and unceded territory of the Musqueam people.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".