Underrepresented Students and the Transition to Postsecondary Education: Comparing Two Toronto Cohorts
Bibliographic record
Abstract
Using data from two cohorts of Grade 12 students in Toronto, we examined whether the transition to post-secondary education changed between 2006 and 2011, particularly for under-represented groups. We used multilevel, multinomial logistic regressions to examine how the intersections of race and sex affect post-secondary transitions in the two cohorts. Our findings revealed that Black, Latino, and Southeast Asian students were less prepared for post-secondary education than White students. Students in these groups had lower than average GPAs, higher identification of special education needs, or lower likelihoods of taking academic-stream courses. These differences remained fairly stable between 2006 and 2011. We did, however, find that Black students were more likely than White students to confirm a place in university in 2011—a significant difference. In contrast, Southeast Asian students experienced a decline in university transition but an increase in college confirmation. We also found that race and sex were important intersections for university confirmations in the case of Blacks and for college confirmations in the case of Southeast Asians. We contextualize our findings within the policy climate of Ontario in the years spanning our two cohorts.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".