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Record W4324386706 · doi:10.1177/10384162221141350

Breaking through the glass ceiling, but at what cost? From transitions between hierarchical levels to the diversity of ascending, lateral, or descending career paths of women executives

2023· article· en· W4324386706 on OpenAlexaff
Émilie Giguère, Mariève Pelletier, Karine Bilodeau, Louise St-Arnaud

Bibliographic record

VenueAustralian Journal of Career Development · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversité de MontréalUniversité Laval
Fundersnot available
KeywordsGlass ceilingNarrativeDiversity (politics)Experiential learningDistancingSociologyPublic relationsCareer developmentMeaning (existential)Qualitative researchGender diversityPerspective (graphical)PsychologySocial psychologyManagementPolitical sciencePedagogyComputer scienceSocial scienceCoronavirus disease 2019 (COVID-19)LawEconomics

Abstract

fetched live from OpenAlex

The present article proposes to broaden the understanding of the life courses of women executives to include an experiential perspective of meaning built around their different life projects. Our study is based on a qualitative approach employing narrative research methodology to analyze interviews with a sample of 51 women executives. Our findings reveal key experiences and events and a diversity of transitions between hierarchical levels that characterize their career development. They also show a number of possible configurations of rapprochement, integration, distancing, or separation between the different spheres of life and their influence on executive careers through ascending, lateral, or descending career paths. These findings contribute to a deeper insight into the complex career paths of women executives and underscore the value of including these different dimensions when considering guidance support strategies for this clientele.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.264
GPT teacher head0.340
Teacher spread0.076 · 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 designQualitative
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

Citations10
Published2023
Admission routes1
Has abstractyes

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