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Record W4327587972 · doi:10.1080/03075079.2023.2187771

Gender and leadership in public higher education in South Asia: examining the individual, socio-cultural and organizational barriers to female inclusion

2023· article· en· W4327587972 on OpenAlexaff
Md Asadul Islam, Dieu Hack‐Polay, Mahfuzur Rahman, Amer Hamzah Jantan, Francesca Dal Mas, Maria Kordowicz

Bibliographic record

VenueStudies in Higher Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsCrandall University
FundersUniversiti Putra Malaysia
KeywordsInclusion (mineral)Higher educationFocus groupOrganizational cultureSociologyPublic relationsPolitical sciencePsychologyGender studies

Abstract

fetched live from OpenAlex

The study examines the personal, social, and organizational barriers facing women in university leadership positions in South Asia, building on the cases of Malaysia and Bangladesh. We discussed the topic through the lens of interactionist feminist theory. Semi-structured interviews with 20 female deans from 12 public universities in Malaysia and Bangladesh were conducted, followed by two focus group discussions with eight female deans. The results reveal that personal barriers such as family duties, lack of technological knowledge, interest in taking leadership positions, spousal support and poor time management, and lack of spousal support represented the major barriers for female deans in Bangladesh. Lack of interest in deanship was found to compound the underrepresentation of women in dean roles. The participants identified fewer socio-cultural barriers faced by Malaysian female deans, while Bangladeshi participants met major issues. The organizational barriers for female deans in public universities were reported. The findings hold significant organizational and policy implications.

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)0.001
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 score0.028
Threshold uncertainty score0.744

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.574
GPT teacher head0.402
Teacher spread0.172 · 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

Citations51
Published2023
Admission routes1
Has abstractyes

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