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Record W2529568472 · doi:10.5070/p2cjpp8432629

Variation in Structural Home Rule: Evidence from California City Councils

2016· article· en· W2529568472 on OpenAlexaboutno aff
Samuel Stone, Justin A. Tucker

Bibliographic record

VenueCalifornia Journal of Politics and Policy · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsnot available
Fundersnot available
KeywordsCharterHome rulePublic administrationCorporate governancePolitical scienceDemocracyLocal governmentQuarter (Canadian coin)State (computer science)Government (linguistics)GeographyLawPoliticsBusiness

Abstract

fetched live from OpenAlex

Much of the literature on home rule overlooks structural variations in city governance. Because structural features of city governance expand or restrict democratic participation, we take a comprehensive look at the 481 cities in California to identify correlates of home rule status and city council size. Roughly a quarter of the cities in the state have chosen to become charter cities while the rest remain general law cities with essentially identical governing bodies of five member city councils elected in at-large elections. Some cities that have opted to become charter cities have altered their form of government or electoral systems, but many have not. Among all cities in California, both general law and charter, variations in city council size, election method, and mayoral selection are largely unrelated to demographic factors but rather the year of incorporation, selection method of the mayor, and whether the city has adopted a charter.

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)0.005
metaresearch head score (Gemma)0.026
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.571

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.006
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.051
GPT teacher head0.351
Teacher spread0.300 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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