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Record W2326460337 · doi:10.1017/s0008423914001073

Vetoes and Venues: Economic Crisis and the Roads to Recovery in Michigan and Ontario

2014· article· en· W2326460337 on OpenAlexaboutno aff
John Constantelos

Bibliographic record

VenueCanadian Journal of Political Science · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGovernorVetoRecessionDecentralizationState (computer science)Government (linguistics)PoliticsEconomic policyEconomic recoveryPolitical sciencePublic administrationEconomicsMarket economy

Abstract

fetched live from OpenAlex

Abstract This article examines executive responses to economic decline in Ontario and Michigan from 2003 to 2012, when the two governments struggled to adjust to a severe manufacturing crisis which greatly worsened during the Great Recession in 2008–2009. Sharing an international border, these cases offer control over an unusually large number of economic, social and political factors, permitting a focused analysis of the impact of divided government and fiscal decentralization on executive policy making. The research finds that greater fiscal decentralization in Canada and unified government in Ontario allowed the province to develop a more rapid and more robust response to the economic crisis in comparison to the State of Michigan. Budgetary constraints and a partisan veto at the state level forced Michigan's governor to redirect her efforts to the federal venue.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.847

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
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 head0.012
GPT teacher head0.280
Teacher spread0.267 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations11
Published2014
Admission routes1
Has abstractyes

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