Gender, Class and the Cost of Unpaid Care: An Analysis of 25 Countries
Bibliographic record
Abstract
This article examines the relationship between gender, class and unpaid care for children and elderly household members across twenty-five countries. Using the microdata files of the 2015–2017 Luxembourg Income Study, we demonstrate that household income quintile shapes the relationship between resident caregiving and a) women’s diminished share of household income and b) the associated “wage penalty” women experience in paid employment, examining dual-headed heterosexual households and grouping countries at varying levels of GDP per capita. Our analyses demonstrate that both eldercare and childcare have a negative impact on women’s economic outcomes, yet the effects of both types of unpaid care vary across class. Overall, childcare has a larger impact for women in lower income households, while eldercare has a larger impact for women in higher income households. However, the wage penalties experienced by wealthier women due to either type of potential care responsibilities are considerably less than those experienced by women in poorer households. Together, these data suggest that unpaid resident caregiving has effects that are both highly gendered and highly classed, leading to intersectional disadvantages for women performing unpaid care within poorer households across countries, and with effects that, in some cases, are further amplified within low-GDP countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".