Gender differences in STEM enrolment and graduation: What are the roles of academic performance and preparation?
Bibliographic record
Abstract
Despite women outnumbering men in postsecondary institutions, women are considerably less likely to select the higher paying STEM fields, which could be a factor in the gender wage gap. While many studies have examined the persistent underrepresentation of women in STEM programs among postsecondary graduates, the goal of this study is to advance the Canadian evidence in three ways. First, the study distinguishes between two types of gender differences in the probability of selecting STEM-related fields in a bachelor’s degree program: those that are conditional on enrolment in a bachelor’s degree program and those that are unconditional on doing so. Second, the study highlights gender differences in specific STEM programs. Third, the study addresses the substantial sample attrition affecting longitudinal household surveys that have been used to study the issue in several previous studies. To do so, the study uses an administrative dataset that provides detailed academic performance information on students from kindergarten to Grade 12 in Canada’s third-most populous province, British Columbia.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".