“Women’s Work”: Welfare State Spending and the Gendered and Classed Dimensions of Unpaid Care
Bibliographic record
Abstract
This study is the first to explicitly assess the connections between welfare state spending and the gendered and classed dimensions of unpaid care work across 29 European nations. Our research uses multi-level model analysis of European Quality of Life Survey data, examining childcare and housework burdens for people living with at least one child under the age of 18. Two key findings emerge: First, by disaggregating different types of unpaid care work, we find that childcare provision is more gendered than classed—reflecting trends toward “intensive mothering”. Housework and cooking, on the contrary, demonstrate both gender and class effects, likely because they are more readily outsourced by wealthier individuals to the paid care sector. Second, while overall social expenditure has no effect on hours spent on childcare and housework, results suggest that family policy may shape the relationship between gender, income, and housework (but not childcare). Specifically, family policy expenditure is associated with a considerably smaller gender gap vis-à-vis the time dedicated to housework: This effect is present across the income spectrum, but is particularly substantial in the case of lower income women.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".