Overcoming “Bikelash”: Successful Implementation of an Urban Bicycle Highway in Montréal
Bibliographic record
Abstract
Among the leading factors that frustrate bike lane development is the phenomenon known as “bikelash,” which is the organised opposition to bike lane development, usually categorised by \nheated emotion. The presence of bikelash can make bike lane developments politically toxic in the public discourse, often leading to the failure to build the bike lane. The Saint-Denis Réseau \nExpress Vélo (REV) is one artery of the “bike highway” of Montréal that managed to be built despite the presence of bikelash from merchants, politicians and select members of the public. This thesis uses the Saint-Denis REV as a case study to understand why bikelash did not overwhelm this bike lane, despite the intense opposition to this development. Using political communication strategies and merchant subsidy programs, the municipal administration of Montréal was able to overcome bikelash and see the bike lane successfully installed. This thesis will examine the history of this bike lane, the bikelash in response to the development, and how this project managed to survive.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".