Women Returning to Employment, Education and Training in Ireland: An Analysis of Transitions*
Bibliographic record
Abstract
Abstract: Recent improvements in the Irish labour market have led to a substantial increase in the labour force participation rate of women in Ireland. Part of this increase has been fuelled by women moving from the home into paid employment. Much of the existing research on labour market activity among Irish women has focused on cross-sectional analyses of the stock of labour market participants. In this paper we aim to address some of the gaps in the literature by investigating the transition from home to work, and from home to education, training and employment schemes among women in Ireland during the period 1994 to 1999. We adopt a dynamic approach by drawing on the nationally representative longitudinal data in the Living in Ireland Survey. This allows us to provide, for the first time, a representative profile of returners, and to formally model the transition process in terms of supply and demand factors. The analysis also investigates the factors associated with the return to part-versus full-time work. Our analysis reveals that about one-quarter of those engaged full-time in home duties in 1994 had made a transition to paid work within the six-year period 1994-1999. The study identifies a number of key factors that influence the transition from home to work or education, training and employment schemes, including, on the supply side, age, education, previous work experience, time out of the labour force, and the presence of young children in the household, and on the demand side, macro-economic conditions and urban versus rural residence. I
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".