Participation of Women in the Labor Market in Europe and Informal Care Hours
Bibliographic record
Abstract
An analysis was made of the effect of providing informal care, in terms of the weekly work hours, on middle-aged women in Europe aged between 30 and 59 years, using as reference subjects women aged between 20 and 29 years. The data come from the eight European Community Household Panel surveys (ECHP). We compared the group of women caregivers and noncaregivers using a zero-inflated negative binomial (ZINB) regression model. The results show that caring for dependents reduces weekly work hours, especially in southern European countries. eir becoming entrepreneurs. Five plots are identified: the women who positioned themselves as the creators of their businesses; those who define themselves as artists, those who assumed a position of co-author; those who described themselves as a ‘responsible wife’; those who defined themselves as belonging to the second generation. In fact becoming a woman entrepreneur implies a process of learning and enacting behaviors, discourses and competent participation in a local community. The narratives of becoming a woman entrepreneur are analyzed in relation to two dimensions: temporality and accountability.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".