A new urbanity in a suburban region: the perceived (im)possibilities of light rail among residents and stakeholders in Canada’s Waterloo Region
Bibliographic record
Abstract
Recent scholarship on light rail transit (LRT) connects this infrastructure to broader processes of urban transformation, bringing to the forefront its significance beyond transportation functionality. However, much of the transportation literature does not adequately explore light rail’s diverse meanings. In this article, we draw on 65 semi-structured interviews with residents living along the new LRT line in Waterloo Region, Canada, as well as 20 key stakeholders, to identify the infrastructure’s perceived roles with respect to city building, urban identity, and neighbourhood change. We investigate how residents ascribe meaning to the LRT, and the extent to which these meanings align with stakeholders’ growth management objectives. In contrast to this focused planning rationale, the LRT evokes for residents a broader range of (im)possibilities that reflect their class positions and understandings of (sub)urban life in the region. Residents’ perspectives underline light rail’s implication in producing middle-class urbanity beyond its role in supporting an intensified, revitalized urban form. Here, light rail also reinforces existing urban middle-class identities and aspirations, which conflict with both dominant suburban identities and the experiences and fears of lower-income residents living along the route. These findings interrogate who is included in the type of city an LRT helps construct.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".