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Public Spending, Public Deficits and Government Coalitions

2010· article· en· W1836838334 on OpenAlexaff
André Blais, Jiyoon Kim, Martial Foucault

Bibliographic record

VenuePolitical Studies · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsVetoStatus quoArgument (complex analysis)Context (archaeology)Status quo biasGovernment (linguistics)EconomicsGovernment spendingPublic economicsCoalition governmentPower (physics)Public spendingPolitical sciencePoliticsMarket economyLawWelfare

Abstract

fetched live from OpenAlex

This study examines the relationship between types of government and level of public spending. There are two competing perspectives about the consequences of coalition governments for the size of public expenditures. The most common argument is that government spending increases under coalition governments, compared with one-party governments. Another line of thought contends that coalition governments are often stalled in the status quo due to the veto power of each member. Our analysis of public spending in 33 parliamentary democracies between 1972 and 2000 confirms the latter argument that coalition governments have a status quo bias. We find, particularly, that single-party governments are apt to modify the budget according to the current fiscal condition, which enables them to increase or decrease spending more flexibly. By contrast, coalition governments find it difficult not only to decrease spending under difficult fiscal conditions but also to increase it even under a more favorable context, because each member of the coalition has a veto power.

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)0.002
metaresearch head score (Gemma)0.016
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 score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.163
GPT teacher head0.277
Teacher spread0.114 · 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

Citations31
Published2010
Admission routes1
Has abstractyes

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