The Causes of City-Suburban Political Polarization? A Canadian Case Study
Why this work is in the frame
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Bibliographic record
Abstract
Recent research conducted in both the United States and Canada has found that residents of inner cities and suburbs are diverging in their voting behavior and political attitudes. The mechanisms producing such a divergence, however, have remained unclear. After identifying a set of distinct hypotheses for why one might expect residents of inner cities and suburbs to differ in their political views, this article draws on a survey undertaken by the author in one electoral district in the Toronto region to empirically test the relative contribution of each of the hypothesized mechanisms in explaining the geography of party preferences. This study suggests there is no single explanation for the city-suburban cleavage, and that the mechanisms producing it are complex. Spatial segregation (based on individual attributes such as race, ethnicity, and class) is clearly important; however neighborhood self-selection, local experience, and, to a lesser extent, mode of consumption all have significant independent effects. Particularly important is the self-selection of supporters of political parties on the left into the inner city, stemming either from a search for a “sense of community” or the desire to link their lifestyle choices to their political convictions, whereas supporters of parties farther to the right are more likely to choose postwar suburban neighborhoods out of a preference for private space. In contrast, there is little evidence that housing tenure or the sharing of political information between neighbors are factors independently producing city-suburban political differences within the study district.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it