THE EDUCATIONAL TRAJECTORY OF HIGH SCHOOL STUDENTS TO ENGINEERING PROGRAMS AT A COMPREHENSIVE CANADIAN UNIVERSITY
Bibliographic record
Abstract
This paper reports an analysis of an integrated data set that longitudinally tracked over 14,000 students from Canada’s largest school board (the Toronto District School Board [TDSB]) into Canada’s largest university (the University of Toronto [UofT]). Our analysis showed that when controlling for high school academic records and other student demographics, immigrant students from TDSB were more likely to pursue engineering than other fields of study; math ability was a strong predictor for the TDSB-UofT Engineering pathway; and while engineering students had better academic outcomes than other students, they had lower CGPAs than would be predicted by their academic performance in high school. These findings reveal three characteristics of UofT Engineering: its selectivity and rigor, transnational character of its student population, and complex student diversity. The study also suggests UofT Engineering look into its grading practices.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".