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Record W1999371489 · doi:10.1017/s000842391400016x

Party, Ideology, and Deficits: Provincial Fiscal Policy and the Cameron Thesis, 1966–2009

2014· article· en· W1999371489 on OpenAlexaboutno aff
Christopher A. Simon, Raymond Tatalovich

Bibliographic record

VenueCanadian Journal of Political Science · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsnot available
FundersAustralian GovernmentWashington State University
KeywordsIdeologyLeft-wing politicsPoliticsPolitical sciencePolitical economyEconomicsPeriod (music)Public spendingFiscal policyDemographic economicsDevelopment economicsKeynesian economicsLaw

Abstract

fetched live from OpenAlex

Abstract In a 1985 publication David Cameron reported that historically leftist governments had governed with smaller deficits than rightist governments. The party ideology variable was incorporated into a large body of subsequent research, mainly by economists, to study the growth of public spending and indebtedness. Most agreed with Cameron; some did not. Virtually all studies focused on western European nations (but not subnational governments). This study analyzes provincial deficits or surpluses over the period 1966 to 2009 and determines that rightist parties, despite controls for economic and other political variables, have lower budgetary deficits, a finding which contradicts Cameron but is consistent with five previous studies of provincial spending in Canada.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.991
Threshold uncertainty score0.953

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.013
GPT teacher head0.215
Teacher spread0.202 · 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

Citations10
Published2014
Admission routes1
Has abstractyes

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