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Record W7100257657

Searching for Keynes: The Transitory Component in the Evolution of the Public Sector with Application to Canada, 1870-1995

2002· article· en· W7100257657 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsArgument (complex analysis)Business cyclePublic sectorFiscal policyNew Keynesian economicsPublic policyComponent (thermodynamics)Monetary policy
DOInot available

Abstract

fetched live from OpenAlex

This paper has two themes. In the first instance, we are concerned with uncovering the impact of intellectual thought on the practice of economic policy- specifically, the influence of Keynesianism on fiscal policy. Keynes ' idea that national governments can stabilize aggregate economic activity, presented in his General Theory of Employment, Interest and Money (1936), is one of the most important innovations in economic policy thinking of the last century. It is clear that this argument has influenced both macroeconomic theory and popular opinion about what governments can and should do with respect to the business cycle. However, the extent to which Keynesian thinking has actually influenced the course of public policy remains an open question. Since Keynesian stabilization concerns the transitory components of public policy, a “search for Keynes ” requires that policy actions be separated into permanent and transitory components. There is little research on the challenging problem of modelling trend and cycle in the public sector, and this aspect of the paper constitutes a second theme, one that is of interest in its own right. We look for evidence of attempts at Keynesian stabilization in the fiscal policy actions of the

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0020.003
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.026
GPT teacher head0.193
Teacher spread0.167 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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