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Record W1843958972 · doi:10.1111/jcms.12155

Generational Differences in Values in Central and Eastern <scp>E</scp>urope: The Effects of Politico‐Economic Transition

2014· article· en· W1843958972 on OpenAlexaff
Ekaterina Turkina, Lena Harned

Bibliographic record

VenueJCMS Journal of Common Market Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsDominance (genetics)ResizingConsolidation (business)Convergence (economics)CommunismCohortPolitical sciencePost communistDemographic economicsDevelopment economicsTransition countriesPoliticsEconomicsEconomic growthInternational economicsEuropean unionBiology

Abstract

fetched live from OpenAlex

Abstract This article explores the effects of post‐communist transition and European enlargement on intergenerational politico‐economic values in three groups of countries: Central and Eastern European countries that became European Union members; countries with EU membership prospects; and those that have no membership prospects, at least in the foreseeable future. The analysis indicates considerable differences between these three groups of countries and shows that over time Europeanization served as an intra‐cohort mechanism of social change: it smoothed over intergenerational differences and led to a trend of convergence in values between new Eastern members of the EU and Western Europe. Europeanization also appears to have some harmonizing power on intergenerational differences in countries with EU membership prospects. At the same time, the rough post‐communist transition process and the lack of consolidation mechanisms created considerable intergenerational differences in European countries without EU membership prospects, as revealed by the dominance of cohort replacement mechanism in these countries.

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)0.002
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.023
GPT teacher head0.307
Teacher spread0.283 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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