MétaCan
Menu
Back to cohort
Record W3085762324 · doi:10.1177/1078087420958074

Do “Non-Partisan” Municipal Politicians Match the Partisanship of Their Constituents?

2020· article· en· W3085762324 on OpenAlexafffundabout
Jack Lucas

Bibliographic record

VenueUrban Affairs Review · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIdeologyRepresentation (politics)PoliticsPolitical sciencePolitical economyPublic administrationUrban politicsElectoral politicsCharacter (mathematics)LawSociologyDemocracy

Abstract

fetched live from OpenAlex

Recent research in the United States has found that municipal governments are responsive to the ideological complexion of their cities even in the absence of partisan elections. In this paper, I test for the presence of party match—a match between the partisan character of a district and the partisanship of its municipal representative—in Canada, where municipal elections are distinctively non-partisan. Using new data on district-level party support and the partisanship of Canadian municipal politicians, I find clear evidence for party match. This match is equally likely in at-large and ward elections, partisan and non-partisan elections, and large and small cities. I thus argue that partisan and ideological representation is an important and widespread feature of Canadian municipal politics. I discuss the implications of these findings for theories of municipal representation and the role of ideology in municipal politics.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.272

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.090
GPT teacher head0.349
Teacher spread0.259 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations30
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueUrban Affairs ReviewSame topicElectoral Systems and Political ParticipationFrench-language works237,207