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Record W2753378583

Bulgarian GDP structures: convergence with the EU [paper]

2015· article· en· W2753378583 on OpenAlexaboutno aff
Statty Stattev, Stela Raleva

Bibliographic record

VenueSEEJE · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsnot available
Fundersnot available
KeywordsConvergence (economics)BulgarianEconometricsDivergence (linguistics)Quarter (Canadian coin)EconomicsCzechMathematicsMacroeconomicsGeography
DOInot available

Abstract

fetched live from OpenAlex

The paper studies the convergence of the GDP expenditure and production structures of Bulgaria and the Czech Republic with the EU. It is structured as follows: first, we analyse convergence of the dynamics of the respective GDP components in the two structural cross-sections. To this end, the behaviour of respective components is characterized and an econometric evaluation of the existing convergence between them is conducted. After that, the convergence of any of the two structures of GDP is examined and trends in its changes over time are interpreted. Convergence in the dynamics of components is measured by using the β-convergence approach and panel modelling. Regarding GDP structural convergence, it is calculated through the divergence index. All data used are on a quarterly basis and refer to the period starting from the first quarter (for structural convergence – from the second quarter) of 1997 till the first quarter of 2005 inclusive.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.195
Teacher spread0.158 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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