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 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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".