Canadian Low Impact Development Retrofit Approaches: A 21 <sup>st</sup> -Century Stormwater Management Paradigm
Bibliographic record
Abstract
Southern Ontario and, more generally, urban areas throughout Canada, have seen the implementation and successful operation of a number of pilot scale low impact development (LID) projects. Despite demonstrated success and a proclivity to outperform design expectations, adoption of LID practices—particularly on predeveloped private property—has not occurred. This is true even in the face of ongoing urban flooding and water quality impairment issues. While several factors have been identified as barriers hindering broad scale LID implementation, market research conducted in the Greater Toronto Area (GTA) indicates that the high up-front costs and long or non-existent payback period are the largest barriers inhibiting LID adoption. To address this, a mix of innovative policy and market-based tools, incentives, and approaches are needed. The Drainage Act, a 183 year old piece of legislation unique to the Province of Ontario, has been intensely scrutinized and found suitable as a vehicle to facilitate cost-optimized, community-based retrofit implementation. However, to incentivize the use of the Drainage Act process, a paradigm shift in how municipalities approach stormwater management is required to address the up-front costs and long payback periods associated with LID retrofits. Recognizing the offsite benefits provided by private property adoption and rewarding appropriately will promote an approach to managing stormwater that is not only cost effective and affordable, but linked and integrated at a watershed scale in a way that meets water quality targets in the face of increasing urbanization and climate change.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".