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Record W4404014759 · doi:10.1177/08404704241293947

Gender and healthcare leadership: Addressing critical knowledge gaps by explicitly considering the gendered concept of care

2024· article· en· W4404014759 on OpenAlexafffund
Yvonne James, Billie Jane Hermosura, Ruth Decady, Ivy Lynn Bourgeault

Bibliographic record

VenueHealthcare Management Forum · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsUniversity of Ottawa
FundersStatus of Women Canada
KeywordsHealth carePsychological interventionContext (archaeology)PsychologyLeadership developmentFocus groupPublic relationsNursingSociologyMedicinePolitical science

Abstract

fetched live from OpenAlex

This scoping review of gender and healthcare leadership synthesized the barriers and facilitators at multiple levels employing a framework that integrates a specific focus on the concept of care. The 71 sources identified focus predominantly on barriers to women's leadership at the individual and team level and, to a lesser extent, at the organizational and system level. Facilitators tend to be presented as recommended actions than evaluated interventions. Healthcare leadership tends to ignore the gendered context of care elevating leaders who are least likely to provide such care. Where personal caregiving circumstances are considered, they are individualized, reflecting the literature in general. More critical analysis is needed to focus on women's experiences and how their gender can predetermine their success in achieving and being in leadership positions. Healthcare leadership researchers are encouraged to include gender and care-focused analyses and interventions to address the under-representation of women in healthcare leadership.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.083
metaresearch head score (Gemma)0.170
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.083
Threshold uncertainty score0.440

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0830.170
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0150.010
Science and technology studies0.0040.009
Scholarly communication0.0150.031
Open science0.0040.008
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0030.000

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 head0.165
GPT teacher head0.390
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations5
Published2024
Admission routes2
Has abstractyes

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