Adoption of best practices for the environmental management of road salt in Ontario
Bibliographic record
Abstract
There are increasing concerns regarding the adverse environmental impacts of chloride from road salts. A web-based survey was conducted to determine how the Code of Practice for the environmental management of road salts has influenced the adoption of best practices in Ontario, Canada. The majority of large Ontario municipalities have salt management plans that adequately address safety and the environment. Most municipalities train a high percentage of permanent staff but only half of seasonal workers and 21% of private contractors are trained. Most training programs cover key learning goals defined by the Code of Practice. There is little improvement in the management of salt-vulnerable areas. Many existing snow disposal sites are poorly designed and do not manage snowmelt quality. The Code has strongly contributed to the adoption and improvement of salt management practices in Ontario by helping to standardize practices and advance the rate of implementation of best practices. Barriers to further implementation of the Code include understanding the Code, institutional will, liability, limited technical/financial resources and public expectation of high service levels. Further benefits can be achieved by aggressively promoting the Code and improving education and training programs for the public, private contractors and staff of road authorities.
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 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 | 0.006 | 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) | 0.002 | 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 teacher head, 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".