The Development of the Urban-Rural Cleavage in Anglo-American Democracies
Why this work is in the frame
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Bibliographic record
Abstract
We provide a mixed-methods, comparative analysis of the development of the urban-rural electoral cleavage in Canada, Great Britain, and the United States from the early 20th century to the present. Using aggregate election results, electoral district boundary files, and electoral district population measures, we construct a new comparable dataset of district election results and urbanity for the lower house of the legislature in each country. We use this dataset to measure the importance of the urban-rural divide for election outcomes across countries and time. We find that the cleavage has widened over time in each country, each arrived at its current urban-rural divide via a distinct developmental trajectory, which we interpret with reference to secondary literature. We conclude by discussing the significance of our findings for theories of both the causes and consequences of urban-rural divides and discuss the implications of our work for the comparative study of urban-rural cleavages.
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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 | 0.002 |
| 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