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Record W4286622161 · doi:10.5465/ambpp.2022.229

Self-employment and Motherhood: Labor Market Outcomes of Self-employment in Early Childhood Years

2022· article· en· W4286622161 on OpenAlexaff
Pomme Theunissen, Annemarie Kuenn, Kate Rybczynski

Bibliographic record

VenueAcademy of Management Proceedings · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEarningsWageChildbirthLabour economicsEconomicsOddsFlexibility (engineering)Parental leaveDemographic economicsPregnancyMedicineWork (physics)Logistic regression

Abstract

fetched live from OpenAlex

Self-employment is a career choice that may offer the flexibility to take care of children whilst remaining active on the labor market, and can therefore be seen by mothers as an alternative to wage employment during early childhood years. Using data from the German Socio-Economic household panel (SOEP) between 1995 and 2018, we investigate the success of this strategy, by studying wage earnings and the labor force status of mothers seven years after childbirth, once the child reaches school age. Taking account of self-selection into self-employment, we find that the consequences of self-employment experience in the early years after childbirth are no different from being inactive in terms of hourly wage for mothers who return to wage employment, while each additional month of wage employment after childbirth increases this wage by 0.4%. However, each additional month of self-employment experience does increase the odds of being active in the labor market by 22%, compared to inactivity. Analogously, for each additional month of wage employment, the odds of being employed increase by 6%. Self-employment in the early years after child birth thereby seems to keep mothers attached to the labor market to a greater degree than does wage-employment.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.240
Teacher spread0.231 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2022
Admission routes1
Has abstractyes

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