First Nations wastewater treatment systems in Canada: Challenges and opportunities
Bibliographic record
Abstract
The Government of Canada has prioritized the availability of water and wastewater services for the Canadian First Nations Communities (CFNC) and introduced the First Nations Water and Wastewater Action Plan. Several studies explore that many wastewater treatment systems (WWTS) in the CFNC do not meet the effluent discharge limits. The objectives of this study were to examine the existing WWTS in CFNC, investigate the progress and improvement opportunities, evaluate the risk levels, encapsulate the financial condition, and provide recommendations for the overall improvement of the WWTS in CFNC. The authors found significant improvement in 2011 when 98% of the Canadian First Nations houses received wastewater services in comparison to only 50% in 1978. However, 1,777 First Nations houses did not receive any wastewater services. In 2011, 21% of the wastewater systems were operated exceeding the facilities’ design capacities. The overall high-risk and medium-risk wastewater systems have reduced from 14 and 51% in 2011 to 6 and 41% in 2014–2015, respectively. The Government of Canada committed to provide $4.2 billion for the 10-year period (2011–2021) against the estimated cost of $6.3 billion. Increasing and proper utilization of the allocated budget is recommended to fill up the financial gaps.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".