Lead Service Lines: Management and Public Perception in 21 Utilities
Bibliographic record
Abstract
Utility and homeowner surveys were completed in 2015 to document the number of lead service lines (LSLs) in Canadian utilities, share utilities’ knowledge, and formulate recommendations on LSL management. LSLs represented <1 to 22% of the service line connections in the distribution systems considered (average 23 LSLs/1,000 people). With the exception of two utilities, mostly partial LSL replacements (LSLRs) were conducted by the utilities surveyed; flushing procedures post‐LSLR varied. Considering both surveys, the following recommendations are suggested: improve LSL records by registering the materials on both the public and the private sides after LSLR; harmonize flushing procedures post‐LSLR; develop a collaborative approach between contractors and utility staff to increase awareness, maintain LSL records, and ensure post‐LSLR flushing; combine funding, increased awareness, and provision of contractors to homeowners with fixed costs to increase full LSLRs; and assess the possibility of mandatory LSL detection and full LSLR at the time of house resale.
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.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".