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Record W2084422964 · doi:10.1353/cpp.2012.0025

Effective Tool or Effectively Hollow?: Balanced Budget Legislation in Western Canada

2012· article· en· W2084422964 on OpenAlexaffvenueabout
Wayne Simpson, Jared J. Wesley

Bibliographic record

VenueCanadian Public Policy · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Two decades have passed since the first wave of balanced budget legislation (BBL) in Canada. This passage of time and the recent economic downturn afford researchers the opportunity to evaluate the success of these regulations in encouraging fiscal responsibility. This paper provides both a quantitative analysis of the impact of BBL on expenditure growth and a qualitative assessment of BBL in Western Canada as these four western provinces confronted the Great Recession of 2008–09. On both accounts, our analysis suggests that BBL did not fare particularly well in terms of its original objectives. Our empirical analysis shows that BBL had no discernible effect in restraining expenditure growth relative to revenue growth in most provinces, leaving them in a vulnerable fiscal position to avert deficits during economic recession. We illustrate this vulnerability among Western Canadian governments when confronted with the Great Recession. In other words, BBL was neither strong enough to limit expenditure growth during the good times nor adequate to prevent governments from choosing to run deficits during the bad times. Our analysis suggests that, like any piece of legislation, BBL is only as effective as the political will and public support surrounding it.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.223
Teacher spread0.205 · 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.

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

Citations12
Published2012
Admission routes3
Has abstractyes

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