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Record W4412962239 · doi:10.1111/gwao.70018

Opportunities and Constraints: Gendered Family‐Life and Career Trajectories of Academics in Iceland and Canada

2025· article· en· W4412962239 on OpenAlexaffabout
Andrea Hjálmsdóttir, Laura Landertinger, Helga Kristín Hallgrímsdóttir, Þorgerður Einarsdóttir

Bibliographic record

VenueGender Work and Organization · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversity of VictoriaMinistry of Health and Long Term CareMinistry of the Environment, Conservation and Parks
Fundersnot available
KeywordsNeoliberalism (international relations)WelfareSociologyPower (physics)Gender studiesHigher educationWork–life balanceFamily lifeWelfare stateWork (physics)InequalityPolitical scienceEconomic growthSocial scienceEconomicsPoliticsLaw

Abstract

fetched live from OpenAlex

ABSTRACT Academic institutions reproduce the dynamics of gendered power relations and maintain gendered inequalities, a process exacerbated by neoliberalism in higher education. In this article, we study how the interplay between conditions within academia and welfare issues affects academics' decision‐making regarding their careers and family life trajectories in different welfare regimes. We draw on open‐ended interviews with 26 men and women working in higher education institutions in Iceland and British Columbia, Canada. The findings reveal how these academics live their lives in different, yet strikingly similar, ways. The study contributes to the dialog on the relative impact of welfare regimes and gender relations on struggles of academics around work–life balance; competing work responsibilities and family commitments; and gendered patterns in care, and housework. Our findings contribute to clarifying how higher education institutions and different welfare state policies are eclipsed by gendered power dynamic at the couple level in both countries.

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 score0.168
Threshold uncertainty score0.937

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 head0.100
GPT teacher head0.248
Teacher spread0.148 · 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
Published2025
Admission routes2
Has abstractyes

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