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Record W2588554407 · doi:10.3138/jcfs.47.1.87

The Transforming Educational Gradient in Marital Disruption in Northern Europe: A Comparative Study Based on GGS Data

2016· article· en· W2588554407 on OpenAlexvenueno aff
Allan Puur, Leen Rahnu, Aušra Maslauskaitė, Vlada Stankūnienė

Bibliographic record

VenueJournal of Comparative Family Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsnot available
Fundersnot available
KeywordsEducational attainmentAutonomyDemographic economicsGeographyDemographyPolitical scienceSocioeconomicsEconomic growthSociologyEconomics

Abstract

fetched live from OpenAlex

A substantial body of research has accumulated on the socio-economic correlates of marital instability. Previous studies have shown considerable variation in the association between women’s educational attainment and marital disruption. This article complements existing research by investigating the pattern of this relationship across countries and its change over time. The main geographical focus is on Northern Europe but evidence is also presented from countries in other regions of the continent. The data come from the Generations and Gender Surveys conducted from 2004 to 2010. The estimates from Cox proportional hazards models reveal considerable variation in the educational gradient of disruption risks. We find that among the Northern European countries, Norway and East Germany exhibit a negative relationship between women’s education and marital disruption. In contrast, Lithuania features a positive association, while Estonia and West Germany show a neutral relationship. The observed pattern seems to follow the advancement of family deinstitutionalisation and women’s increased economic autonomy. With regard to temporal change, our study lends support to the view that the relationship between women’s educational attainment and marital disruption is not static but evolves from positive to neutral and further to negative. Due to the contextual features discussed in the article, Northern Europe can be regarded as a forerunner in this development among the regions of Europe.

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)0.002
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 score0.062
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.199
GPT teacher head0.426
Teacher spread0.227 · 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

Citations11
Published2016
Admission routes1
Has abstractyes

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