Can We Retrofit Suburban Arterials?
Bibliographic record
Abstract
The multilane arterial roadway is a central feature of post–World War II (WWII) suburbs that challenges efforts to create more transit-oriented regions. Retrofitting suburbs is an important planning goal, but research examining the urban form of arterials and their potential for transformation has been scarce. We analyzed four suburban corridors in the Toronto (Canada) region developed during different periods of suburbanization. We found that the walkability of corridors declined as modernist planning ideas were more fully implemented, and then walkability increased as new urbanist ideas began to influence planning in the 1990s. Over time, however, the retrofit potential declined across all corridors studied, with patterns of lots and development becoming ever more static. Understanding these patterns is important to developing successful strategies for retrofitting suburban arterials. Arterial roadway corridors present potential to bring transit-oriented, walkable urban places near large areas of automobile-dependent suburbs and should be a primary focus for retrofitting research and practice. We present here a set of metrics that rely on readily available data, are not complex to carry out, and produce mapping and visualization that is legible and allows comparison across corridors. We suggest that local governments should be routinely studying and evaluating the potential for retrofit and intensification of all such corridors within their jurisdiction. Planners should seek to develop approaches to managing future corridor development to permit greater adaptability in response to future economic, transportation, and climate changes and vulnerabilities.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".