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Record W4390058619 · doi:10.12765/cpos-2023-29

A Quarter Century of Change in Family and Gender-Role Attitudes in Hungary

2023· article· en· W4390058619 on OpenAlexaboutno aff
Zsolt Spéder

Bibliographic record

VenueComparative Population Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHungarian Social, Economic and Educational Studies
Canadian institutionsnot available
FundersPécsi Tudományegyetem
KeywordsQuarter (Canadian coin)PremiseLiberalizationPopulationPeriod (music)Demographic economicsChinaSocial changeCommunismTransition (genetics)Political scienceDemographyPsychologySociologyGeographyPoliticsEconomicsEconomic growthLaw

Abstract

fetched live from OpenAlex

Our study examines how attitudes towards family and gender roles have changed since the ultimate collapse of communism in Hungary. With respect to evaluating the effects of the regime change, it is important to note that Hungary is unique in having pre-transition measures on attitudes from the International Social Survey Program. In analyzing the nature of value shifts, an arithmetic method that decomposes the changes into population turnover and individual (period) components is used. According to the results, period effects fluctuated over the quarter of century, while the population turnover effects point continuously and clearly towards liberalization of family and gender-role attitudes. Since the period effects were usually stronger, they shaped the fluctuating nature of overall change. Namely, there is a clear trend towards re-traditionalization immediately following the regime change and liberalization thereafter, although there are also signs of continued support for traditional values. The series of repeated modules of the ISSP allowed us to examine a key premise of the Second Demographic Transition (SDT) theory in the case of Hungary. We concluded that the detected direction of the attitude change does not support the examined premise of the SDT. * This article belongs to a special issue on “Demographic Developments in Eastern and Western Europe Before and After the Transformation of Socialist 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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.118
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

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

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 head0.485
GPT teacher head0.486
Teacher spread0.000 · 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.

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

Citations8
Published2023
Admission routes1
Has abstractyes

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