Exploring the adoption of low-impact development in Atlantic Canadian municipalities
Bibliographic record
Abstract
End-of-pipe systems divert often untreated runoff into municipal sewers that connect to receiving waters, endangering the health of aquatic and riparian ecosystems. Low-impact development (LID) can improve the quality and quantity of runoff yet adoption rates are slow. This is especially true in Atlantic Canada, where cities are consistently ranked unsustainable and receive the highest annual precipitation. For more sustainable cities in the future, adoption of LID must increase. Often responsible for stormwater management decisions, planners and engineers from Atlantic Canadian municipalities were interviewed to identify barriers to and perceptions of LID. The interviews yielded six predominant trends representing recurring themes in the interview dialogue. These trends suggest stormwater management is a significant component of projects, yet there is unfamiliarity with LID. No single definitive barrier is inhibiting the adoption of LID in Atlantic Canadian municipalities but developer reluctance was identified as substantial. Overall, municipalities are receptive to LID but require further education and evidence of local effectiveness.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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 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".