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Record W4206555879 · doi:10.1016/j.jointm.2021.12.002

Female representation in intensive care medicine: Challenges and perspectives from China

2022· article· en· W4206555879 on OpenAlexaff
Xuelian Liao, Yi Yang, Francesca Rubulotta, Yan Kang, Jordi Rello

Bibliographic record

VenueJournal of Intensive Medicine · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsMcGill University
Fundersnot available
KeywordsIntensive careWorkforceIntensive care unitChinaMedicineRepresentation (politics)Work (physics)NursingPerspective (graphical)Family medicineIntensive care medicinePolitical science

Abstract

fetched live from OpenAlex

The gender gap in the practice of intensive care medicine has increasingly been recognized as a problem in recent years. Despite limited information, the available data suggest that representation of women in the physician workforce, academic positions, and leadership roles in intensive care is inadequate globally. In this article, we describe the situation of female intensive care unit (ICU) physicians from the perspective of Chinese intensivists. The proportion of female ICU physicians in China has been increasing in recent years. The biggest challenges faced by female ICU physicians include balance of work and life, difficulties in career planning, and lack of academic influence. More attention and policy support should be provided to help them play a better role in intensive care medicine.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.065
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.078
GPT teacher head0.344
Teacher spread0.265 · 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 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

Citations6
Published2022
Admission routes1
Has abstractyes

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