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Record W2531300269 · doi:10.1111/ecpo.12085

Financing Education in Europe: The Globalization Perspective

2016· article· en· W2531300269 on OpenAlexafffund
Zeynep Özkök

Bibliographic record

VenueEconomics and Politics · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsSt. Francis Xavier University
FundersMount Allison UniversityEuropean CommissionSt. Francis Xavier University
KeywordsGlobalizationPublic expenditurePerspective (graphical)EconomicsPublic educationPanel dataHigher educationPublic spendingInclusion (mineral)Public financeEconomic growthPolitical scienceMacroeconomicsSociologyMarket economySocial sciencePolitics

Abstract

fetched live from OpenAlex

This paper examines the role of globalization on public spending on education in Europe. With the implementation of the Bologna process, the changes taking place in the educational structure in Europe have highlighted the importance of public education expenditures. Taking into account the effects of trade, income, and socio‐demographic factors, we study the impact of globalization on public education expenditure at preprimary, primary, secondary, and tertiary institutions using a panel data model for 25 EU countries for the 1998–2010 period. Our findings with different indices of globalization depict a positive effect on education financing. The use of legal and institutional variables, the inclusion of the crisis and euro dummies, and further control variables do not alter our main findings. The Bologna dummy variable is not found to have a significant effect on public education financing, indicating that the integration goals under this process have not translated into increasing levels of public expenditure for education.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.002
Scholarly communication0.0040.004
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.012
GPT teacher head0.222
Teacher spread0.210 · 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 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

Citations9
Published2016
Admission routes2
Has abstractyes

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