The hegemony of automobility: implementing cycling infrastructure in a politicized space
Bibliographic record
Abstract
The implementation of cycling infrastructure has been argued as a means to increase the overall mode share of cycling in communities. However, the implementation of such infrastructure has been fraught with political contentiousness across North America. In this paper, we interview ten municipal planners and engineers in the Greater Toronto and Hamilton Area, in order to determine how they implement cycling infrastructure in the face of political opposition. We find that there are four principal strategies used to secure the political support and ensure the construction of cycling infrastructure across the region: 1) piggybacking on public works projects, 2) using external grants and funding, 3) pre-emptively re-routing bicycling infrastructure, and 4) using a political champion. Through these strategies, we theorize that the politicization of cycling infrastructure is a result of the dominance of automobility in mobility, and that this politicization may lead to incomplete and less-than ideal cycling networks.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| 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".