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Record W4400829187 · doi:10.33138/2957-0506.2024.8.444

Work from Home and Perceptions of Career Prospects of Employees with Children

2024· article· en· W4400829187 on OpenAlexaboutno aff
Agnieszka Kasperska, Anna Kurowska

Bibliographic record

VenueWorking Papers. · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionPsychologyWork (physics)Medical educationMedicineEngineering

Abstract

fetched live from OpenAlex

this study explores how various work and family-related contexts moderated the link between work-from-home (WFH) and self-perceived changes to the career prospects among employees with children after over a year of the COVID-19 pandemic. We argue that the link between WFH and the perception of changes to one’s career prospects is likely to differ depending on gender, occupation, whether the employee has worked from home before the pandemic, how much time their children spent at home due to pandemic restrictions and the cohabiting status of the parent. We conducted fixed effects multinomial regression models using a unique multicountry dataset, including representative samples of parents with dependent children from Canada, Germany, Italy, Poland, Sweden, and the US. Employees with children who had prior experience with WFH before the pandemic were more likely to report improved career prospects than those who worked solely in the office. The positive effect of WFH for newcomers to the world of remote work was less unequivocal and varied based on occupation and gender. We also find that the presence of children at home and the cohabitation status substantially moderate the link between WFH and perceived changes to one’s career prospects, with different implications based on the employee's gender. We fill the research gap by showing how fluid workers' perceptions of career prospects depend on varying professional (prior experience with WFH and occupation) and personal (increased family demands) situations. This study also indicates the need for context-sensitive career management in organisations.

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)0.000
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 score0.109
Threshold uncertainty score0.191

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.015
GPT teacher head0.265
Teacher spread0.250 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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