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Record W2981081104

The Gender Gap in Physics: A Study of Educator Perspectives

2019· article· en· W2981081104 on OpenAlexaboutno aff
Jacqueline Wightman

Bibliographic record

VenueTSpace (University of Toronto) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsnot available
Fundersnot available
KeywordsGender gapMathematics educationPedagogySociologyPsychologyPhysics
DOInot available

Abstract

fetched live from OpenAlex

The gender gap in science and mathematics remains an issue in Canada today, with far-reaching socioeconomic implications (Dionne-Simart et al., 2016). The gender gap is wider in physics than in most other science disciplines (Xu et al., 2015). In this qualitative study, I examine educator perspectives on the low retention rate of young women in physics. The experience and perceptions of female students and educators in physics can inform best practices for physics education in order to retain women in physics. I interviewed two female physics educators: a high school physics teacher, and a graduate physics Teaching Assistant. From these interviews, four themes emerge. The first is that participants believe that the gender gap is caused by differing interests, which may be shaped by societal norms and stereotypes. The second is that participants feel that having strong STEM programming and positive female role models in schools would do the most to reduce the gap. The third theme is that group-based learning should be used to promote inclusivity of young women in physics classrooms. Finally, both participants feel that institutional initiatives geared specifically towards young women sometimes reinforce gender stereotypes, and that promotional initiatives should be designed to foster gender inclusivity, rather than emphasize gender differences.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.281
Teacher spread0.247 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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