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Record W3208385285 · doi:10.1017/s0008423921000792

The Urban-Rural Divide in Canadian Federal Elections, 1896–2019

2021· article· en· W3208385285 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Political Science · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversity of CalgaryWestern University
Fundersnot available
KeywordsUrbanityPoliticsPolitical scienceFederal electionCleavage (geology)Rural areaEconomic growthGeographyEconomyEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract Using a new measure of urbanity for every federal electoral district in Canada from 1896 to the present, this article describes the long-term development of the urban-rural divide in Canadian federal elections. We focus on three questions: (1) when the urban-rural divide has existed in Canada, identifying three main periods—the 1920s, the 1960s and 1993–present—in which the urban-rural cleavage has been especially important in federal elections; (2) where the urban-rural divide has existed, finding that in the postwar period the urban-rural cleavage is a pan-Canadian phenomenon; and (3) how well urbanity predicts district-level election outcomes. We argue that the urban-rural divide is important for understanding election outcomes during several periods of Canadian political development, and never more so than in recent decades. We conclude by discussing the implications of our findings for research on urban-rural cleavages, Canadian electoral politics and Canadian political development.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.331
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it