Predicting Student STEM Career Expectations by Gender and Parental STEM Employment in Canada
Bibliographic record
Abstract
In Sciences, Technology, Engineering and Mathematics (STEM), there exist gender disparities, but upon closer inspection, those disparities vary by STEM type, specifically, Physical Sciences, Technology, Engineering and Mathematics (PSTEM) versus Biology and Health Sciences (BH). Disparities start at adolescence, when students are making decisions about their future careers. Adolescents look for supports from their environments and people surrounding them, including their parents. This thesis uses the 2022 Programme for International Student Assessment to predict students’ PSTEM and BH expectations by gender and parental employment in PSTEM and BH. It found that STEM expectations vary by STEM type, gender, and parent gender controlling for mathematics performance, STEM self-concept, and mathematics anxiety. This thesis updates the existing research: with more women participating in STEM, particularly in BH fields, it provides insight on women as role models to their children in a male-dominated field.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".