Gender Parity and Program Choice: Which Engineering Programs Women Students Prefer to Enter
Bibliographic record
Abstract
Many engineering programs have historically struggled to attract and retain women students. At UBC, two new engineering programs—Biomedical Engineering (BME) and Environmental Engineering (ENV)—have a high percentage of women students compared to other disciplines. However, anecdotal evidence consistent with research on US schools suggested that BME and ENV might have drawn women away from more traditional engineering programs, such as mechanical or civil. This creates a challenge for improving gender parity across all engineering disciplines, and means women are over-represented in disciplines that comprise a small proportion of industry jobs. In this paper, we examine 11 years of student data ranking preferences for second-year programs out of a common first-year at UBC. We found evidence that the addition of BME is associated with a drop in the fraction of women selecting electrical engineering. We also found patterns in the combinations of top-ranked disciplines for men and women students. And we examined the impact of UBC’s pre-BME program on ranking BME as a first choice for women and men.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".