The Transforming Educational Gradient in Marital Disruption in Northern Europe: A Comparative Study Based on GGS Data
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".