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Record W2063965181 · doi:10.1080/09540250042000300402

The participation of women faculty in Chinese universities: paradoxes of globalization

2004· article· en· W2063965181 on OpenAlexaff
Jane Gaskell, Margrit Eichler, Julia Pan, Jieying Xu, Xiaoming Zhang

Bibliographic record

VenueGender and Education · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsUniversity of British Columbia Hospital
Fundersnot available
KeywordsGlobalizationChinaDisadvantageContext (archaeology)ConsciousnessPolitical scienceHigher educationSociologyPublic relationsEconomic growthPedagogyGender studiesPsychologyGeography

Abstract

fetched live from OpenAlex

This paper contributes to a discussion of how globalization is affecting women faculty in different countries around the world. It reports on a collaborative, international research project designed to understand the participation of women faculty members in Chinese universities, sketching the historical context necessary for understanding women's place in universities in China, describing the process of surveying university faculty on gender issues and reporting the findings of the survey for universities that prepare secondary school teachers. The paper concludes that in China, ‘gender consciousness’ is a major barrier preventing women's full participation as faculty. As a result, women are likely to increase their disadvantage in the next few years as Chinese universities expand, diversify, emphasize research and broaden their links with the rest of the world.

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)0.012
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0140.015
Scholarly communication0.0060.005
Open science0.0010.008
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.349
Teacher spread0.329 · 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 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

Citations41
Published2004
Admission routes1
Has abstractyes

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