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Record W4400317004 · doi:10.1007/s44217-024-00186-8

Barriers to women’s participation in higher engineering education: a qualitative assessment of the role of social networks of students in a Ghanaian university

2024· article· en· W4400317004 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDiscover Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsMisinformationEngineering educationPsychologyPerceptionMedical educationEngineeringPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Abstract Engineering is critical for socio-economic development, however only a few women participate in engineering education and careers. This study aimed to identify the types of negative information propagated by the social networks of engineering students that could create barriers to students, and particularly women’s retention in engineering education and careers, and assess whether they influence men and women differently. The study was exploratory hence six focus group discussions were conducted with undergraduate engineering students in their second, third, and fourth years of study in a Ghanaian university. An interview guide was used to, among others, examine the perceptions and misconceptions of students’ social networks about engineering and the negative information that circulates within the networks. Demotivating information from students’ social networks were mainly misconceptions such as (1) engineering is too difficult and strenuous for women, and only meant for strong and well-built people, (2) engineering negatively affects women’s beauty and body image, (3) engineering makes women unfashionable and unattractive, and (4) engineering is a threat to marital and family lives. Both female and male students were negatively affected by misinformation about engineering being difficult and having limited job prospects as well as societal preferences for other programmes such as medicine. The misinformation could serve as a barrier, especially for students lacking ‘faith and the spirit of perseverance’ to pursue and graduate from engineering programmes. While efforts are being made to bridge the gender gap in engineering education and careers, there are misconceptions and misinformation that can hinder progress toward achieving the desired gender parity. Educational policies must integrate gender-responsive strategies including addressing the socio-cultural and stereotypical factors and public misconceptions. There is a need to provide strategic counselling services to engineering students to be able to cope with the effects of negative information from their social networks especially during the early years of their studies in the universities.

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.

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)0.000
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 score0.255
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.015
GPT teacher head0.368
Teacher spread0.353 · 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