Key performance indicators for small and medium-sized urban water systems in a semi-arid region: a case study of Okanagan Valley, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Drinking water, wastewater, and stormwater are three components of an Urban Water System. Maintenance of these components requires evaluation of the existing performance of the water system. The evaluation becomes more significant in small and medium-sized water systems because these systems wrestle with various constraints, such as insufficient funds, inadequate infrastructure and water governance. In this study, Key Performance Indicators (KPIs) are identified for each UWS component considering six performance criteria. A questionnaire was distributed to water utilities across the Okanagan Valley. KPIs were identified by combining Delphi technique and Preference Ranking Organization Method for Enrichment Evaluation methods. Ninety-six KPIs were identified with 39, 30, and 27 KPIs for drinking water, wastewater, and stormwater. Based on the available literature, agriculture water use, low impact development implementation (LID), average annual life cycle investment, and swimming advisories are a few notable KPIs that are unique to the Valley.
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.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it