Leaving and Losing a Job After Childbearing in Italy: A Comparison Between 2005 and 2012
Bibliographic record
Abstract
This article builds on microdata from the Birth Sample Survey (BSS) carried out by Istat in 2005 and 2012 in order to analyse changes in the occupational status of mothers of young children. We aim in particular to broaden the understanding of the individual and contextual characteristics that can affect the probability of women who were employed during pregnancy of not returning to work in the two years following the child’s birth. The study contributes to existing literature on mothers’ employment in two main ways. First, we take into consideration the different nature - voluntary or involuntary – of the motivations for not returning to work. Second, we attempt to evaluate whether the likelihood of Italian mothers to leave or lose their jobs and the factors affecting these probabilities changed between 2005 and 2012. Our results confirm human capital investments and job characteristics to be among the main determinants of women’s employment continuity after childbearing. The probability of losing a job increased significantly for mothers in 2012 compared to 2005, probably as a result of the deterioration of labour market conditions during the recession years. Conversely, the probability of leaving a job was not statistically significantly related to the year; family characteristics - the presence of a couple and features of the partner’s job - were key factors in women’s deciding not to return to work after childbearing.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".