Who Goes into STEM Disciplines? Evidence from the Youth in Transition Survey
Bibliographic record
Abstract
This article presents an empirical analysis of access to post-secondary education (PSE) as it pertains to students in science, technology, engineering, and mathematics (STEM) programs, who are vital to the nation’s economic performance, especially with respect to its information and communication technology (ICT) sector. The analysis is based on the rich Youth in Transition Survey, Cohort A (YITS–A), which follows a representative sample of Canadian youth age 15 in 1999 through to the normal point at which PSE decisions are made. The main findings include that female students go into STEM disciplines at a much lower rate than male students, even after controlling for a broad set of control variables, including high school grades in math and science. Conversely, visible minorities, especially those who are first-generation immigrants, and particularly those from a specific set of regions, participate at much higher rates than others. These results have implications for the ICT talent pool of the future.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".