Impacts of sustainable transport interventions: changes in perception over time and spatially towards a new bus rapid transit (BRT) infrastructure in Montréal, Canada
Bibliographic record
Abstract
Bus rapid transit systems (BRT) research has focused on suitability for implementation and operational factors while disregarding publics’ perceptions and acceptability. This research addresses this gap by investigating changes in perception towards the Pie-IX BRT, a new line in Montréal, Quebec, Canada, over time and across space. We examine attitudinal statements and open-ended survey questions from before and after its opening. At both times, respondents were divided into two groups, those living within one km of the BRT and those who did not. We analyze four attitudinal statements finding statistically significant changes in perception over time, especially among those residing close to the BRT. For the open-ended questions, we apply thematic analyses. Themes concerning the everyday impacts on the neighborhood and the BRT operations were more prevalent among those living close to the project indicating impacts on livability. Those living farther from the BRT focused on city-wide impacts, such as the financial aspects. Our analyses show that to increase acceptance of BRT, different policy directions are needed for the citywide population compared to those residing nearby. The findings can be of interest to practitioners and policymakers as they shed light on public needs and concerns towards new BRT infrastructure.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".