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Record W2294287345 · doi:10.3138/cpp.2015-026

Budgeting Under Prolonged Constraints: Canadian Provincial Governments Respond to Recession and “Slowth”

2016· article· en· W2294287345 on OpenAlexaffvenueabout
Oleg Kodolov, Geoffrey Hale

Bibliographic record

VenueCanadian Public Policy · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsUniversity of LethbridgeQueen's University
Fundersnot available
KeywordsRecessionEconomicsGlobal recessionIdeologyFiscal policyGreat recessionEconomic policyBalance (ability)Political scienceMacroeconomicsKeynesian economicsPoliticsPsychology

Abstract

fetched live from OpenAlex

This article examines the different responses of Canadian provinces to fiscal pressures and constraints since the recession of 2008/09, most of which suggest that in sharp contrast to provincial deficit reduction measures during the 1990s and in the absence of imminent fiscal crises, most provinces have pursued incrementalist responses during the five years following the end of the recession. With only one province achieving ongoing fiscal balance by 2014/15, (with one more in prospect in 2015/16), there has been no consistent partisan or ideological response across provinces to post-recession budgetary challenges.

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)0.010
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 score0.086
Threshold uncertainty score0.625

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0070.002
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.221
Teacher spread0.199 · 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

Citations6
Published2016
Admission routes3
Has abstractyes

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