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Record W4247240454 · doi:10.4324/9781003089858-4

Economic and fiscal policy coordination after the crisis: is the European Semester promoting more or less state intervention?

2021· book-chapter· en· W4247240454 on OpenAlexafffund
Jörg Haas, Valerie J. D’Erman, Daniel F. Schulz, Amy Verdun

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsUniversity of Victoria
FundersErasmus+Social Sciences and Humanities Research Council of CanadaUniversiteit LeidenUniversitetet i AgderEuropean Commission
KeywordsIntervention (counseling)State (computer science)Fiscal policyEconomic policyEconomicsCrisis interventionMacroeconomicsPsychologySocial psychologyComputer science

Abstract

fetched live from OpenAlex

The European Union (EU)and its Economic and Monetary Union (EMU) in particularis often criticized as a predominantly marketoriented project.We analyse to what extent such claims can be substantiated by focusing on one key aspect of the EU's post-crisis framework for economic governance: the country-specific recommendations (CSRs) that the EU has been issuing annually since 2011.Based on an original dataset, we analyse more than 1300 CSRs, which show that the EU does not push uniformly for less state intervention.Rather, the CSRs tend to suggest fiscal restraint and less protection for labour market insiders, while simultaneously promoting measures that benefit vulnerable groups in society.During the second decade of EMU, CSRs have gradually become more permissive of higher public spending and more in favour of worker protection, while the share of recommendations advocating more social protection has stagnated at a high level.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0010.001
Scholarly communication0.0080.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.002

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 head0.033
GPT teacher head0.317
Teacher spread0.284 · 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 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

Citations36
Published2021
Admission routes2
Has abstractyes

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