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Record W2772065840 · doi:10.4337/ejeep.2017.03.02

Editorial to the special issue

2017· article· en· W2772065840 on OpenAlexaffabout
Marc Lavoie, Mario Seccareccia

Bibliographic record

VenueEuropean Journal of Economics and Economic Policies Intervention · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Fiscal policy witnessed a double U-turn, or policy pirouette, because of the global financial crisis. Prior to the 2008 crisis, all Western governments were defending the need to balance public-sector accounts and target budgetary surpluses. The Canadian government, together with the German government, had perhaps been the most vocal and successful in achieving this fiscal objective, while most governments were emulating one another (at least in their official discourse) and metaphorically were tripping over each other to attain budgetary surpluses. However, after November 2008, all the G20 governments began to run significant discretionary budgetary deficits arising from temporary consumption tax cuts and the extension of unemployment insurance benefits, as well as the decision to engage in large public investments According to estimates, these stimulus plans in the G20 countries were in the order of about 2 per cent of GDP on average at the time (Antunes et al. 2010: 5). By June 2010, however, Western governments committed themselves once again to reverse their activist fiscal policy position to achieve budgetary balance. In recent years, a slight rift seems to have appeared in the fiscal policy discourse among Western governments of Europe and North America, with the latter somewhat deviating in their commitments to balanced budgets, especially the Canadian government after 2015.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.025
GPT teacher head0.248
Teacher spread0.222 · 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 designNot applicable
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

Citations1
Published2017
Admission routes2
Has abstractyes

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