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Record W1542468874

Women Returning to Employment, Education and Training in Ireland: An Analysis of Transitions*

2004· article· en· W1542468874 on OpenAlexaboutno aff
Helen Russell, Philip J. O’Connell

Bibliographic record

VenueTrinity's Access to Research Output (TARA) (Trinity College Dublin) · 2004
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
FundersU.S. Department of Justice
KeywordsIrishLabour supplyLabour economicsWork (physics)Quarter (Canadian coin)Stock (firearms)Demographic economicsTransition (genetics)EconomicsSupply and demandGeographyEngineering
DOInot available

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.009
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.233
GPT teacher head0.510
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2004
Admission routes1
Has abstractyes

Explore more

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