Performing legitimate choice narratives in physics: possibilities for under-represented physics students
Bibliographic record
Abstract
Abstract Higher education physics has long been a field with a disproportionately skewed representation in terms of gender, class, and ethnicity. Responding to this challenge, this study explores the trajectories of “unexpected” (i.e., demographically under-represented) students into higher education physics. Based on timeline-guided life-history interviews with 21 students enrolled in university physics programs across Sweden, the students’ accounts of their trajectories into physics are analyzed aschoice narratives. The analysis explores what ingredients are used to tell a legitimate story of physics participation, in relation to dominant discourses in physics culture, and wider social and political discourses. Results indicate that students narrate their choice as based on motivations of physics being a prestigious and challenging subject, of a deep interest in and a natural ability for physics, as well as a wish to use physics for contributing to the world. While most of these affiliations to physics has been documented in earlier research, the study shows how they are negotiated in relation to social locations such as gender, class and migration history, and used to perform an authentic and legitimate choice narrative in the interview situation. Furthermore, the study reports and discusses the possibility of conceiving the role of physics in students’ lives as something beyond a “pure”, intellectually challenging, and “prestigious” subject. In contrast, and with implications for widening participation, the stories of “unexpected” physics students indicate that physics can be reconceived as socially and altruistically oriented.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".