Beyond perception: Spatial analysis of detached ADU potential on residential lots in Windsor, Ontario
Bibliographic record
Abstract
Abstract This paper analyzes the spatial potential of detached additional dwelling units (ADUs) in Windsor, Ontario. A new GIS model, which integrates various geoprocessing commands in ArcGIS 10.8.1, is developed to calculate whether the minimum allowable size of a detached ADU can fit within the total buildable area of a residential property, based on the setbacks, the lot coverage requirements, and other factors (such as parking and flood plain areas). The model uses publicly sourced data that were obtained from the City of Windsor's Open Data Portal. More specifically, individual residential parcels and associated building footprints along with street centerlines are used as inputs to the model. The outputs are then categorized into three types (suitable, potentially suitable, and not suitable) to demonstrate where detached ADUs can be built in compliance with the local zoning bylaws, on both an individual lot basis and at an aggregate level. The conducted analysis reveals the potential of existing residential neighbourhoods in a mid‐size city, and has many implications for homeowners, policymakers, and researchers with respect to increasing housing supply within current Canadian municipalities.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".