Do Water Service Provision Contracts with Neighbouring Population Centres Reduce Drinking Water Risk on Canadian Reserves
Bibliographic record
Abstract
As of 2011, 39% of drinking water systems on Canadian First Nations’ reserves could be classified as high risk, or unequipped to safely deal with the infiltration of a pollutant (Neegan Burnside 2011a). In recent years, some First Nations have contracted water services from neighboring population centres through ‘Municipal Type Agreements’, or ‘MTAs’. Using a unique data set of 804 First Nation water systems, we explore both factors that influence participation in MTAs, and the effect of participation on the likelihood that a First Nation will be under a boil water advisory. Our empirical analysis consists of two probit models. The first model describes the likelihood that a MTA agreement will emerge between a First Nation and neighbouring population centre. The second estimates the likelihood that a First Nation will be under a boil water advisory. Our primary finding is that MTAs reduce the likelihood of a boil water advisory being in effect on a reserve. This is an important consideration when developing incentives or institutions that influence infrastructure collaboration between First Nations and Canadian population centres.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.007 |
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; both teacher heads agree on what is shown here.
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".