Bonus or Burden? Care Work, Inequality, and Job Satisfaction in Eighteen European Countries
Bibliographic record
Abstract
Abstract While existing research highlights the feminized and devalued nature of care work, the relationship between care work and job satisfaction has not yet been tested cross-nationally. England (2005) outlines two theoretical frameworks that guide our thinking about this potential relationship: the Prisoner of Love framework suggests that, notwithstanding the explicit and implicit costs of care work, the intrinsic benefits of caring provide ‘psychic income’ and lead to greater job satisfaction; while the Commodification of Emotion framework suggests, instead, that care work generates additional stress and/or alienation for the worker, thereby resulting in lower job satisfaction. This article empirically tests this relationship in 18 countries using European Social Survey data and incorporating national-level factors. The results provide support for the Prisoner of Love framework, with variation based on the degree of professionalization. Although we find broad evidence of a care work-job satisfaction bonus, non-professional care workers experience a substantively larger bonus than their paraprofessional and professional counterparts. However, national-level economic inequality is also found to play a role in this relationship, with higher inequality amplifying the care work bonus at all levels of professionalization.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| 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) | 0.001 | 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".