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Record W4386391559 · doi:10.1108/heswbl-05-2023-0115

Disparities in work-integrated learning experiences for students who present as women: an international study of biases, barriers, and challenges

2023· article· en· W4386391559 on OpenAlexaffabout
Tracey Bowen, Maureen Drysdale, Sarah Callaghan, Sally Smith, Kristina Johansson, Colin Smith, Barbara Walsh, Tessa Berg

Bibliographic record

VenueHigher Education Skills and Work-based Learning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsSt. Jerome's UniversityUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsOriginalityThematic analysisAutonomyFocus groupValue (mathematics)PerceptionIdentity (music)Presentation (obstetrics)PsychologyWork (physics)Social psychologySociologyQualitative researchGender studiesPedagogyPolitical scienceSocial scienceMedicine

Abstract

fetched live from OpenAlex

Purpose This study identifies gendered disparities among women students participating in work-integrated learning and explores the effects of the disparities on their perceptions on perceived opportunities, competencies, sense of belonging, and professional identity. Design/methodology/approach A series of semi-structured focus groups were run with 59 participants at six higher education institutions in four countries (Australia, Canada, Sweden, United Kingdom). All focus groups were designed with the same questions and formatting. Findings Thematic analysis of the transcripts revealed two overarching themes, namely perceptions of self and interactions with others in work placements. Theme categories included awareness of self-presentation, sense of autonomy, perceived Allies, emotional labour, barriers to opportunity, sense of belonging, intersections of identity, and validation value. Originality/value This study fills an important gap in the international literature about gendered experiences in WIL and highlights inequalities that women experience while on work placements.

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)0.008
metaresearch head score (Gemma)0.014
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 score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0050.004
Scholarly communication0.0040.003
Open science0.0010.007
Research integrity0.0010.001
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 head0.039
GPT teacher head0.367
Teacher spread0.328 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueHigher Education Skills and Work-based LearningSame topicWork-Family Balance ChallengesFrench-language works237,207