Ethno-linguistic patterns of degree completion in BC universities: How important are high-school academic achievement and institution of entry?
Bibliographic record
Abstract
We examine bachelor's degree completion in the British Columbia post-secondary system, which is noted for its multiple pathways to graduation and ethnically diverse student population. Employing an administrative longitudinal dataset, we compare how the probability of degree completion by students enrolled at research-intensive, teaching-intensive, and college-technical institutions differs by ethno-linguistic background and high school grades. Estimates from multi-level logistic regression modelsdemonstrate that Korean, Tagalog, and Vietnamese speakers have lower probabilities of degree completion than English-speaking students. The type of institution a student initially enters is, however, an important correlate of degree completion for all ethno-linguistic groups. Students with lower high school grades who initially enter a research-intensive institution are more likely to graduate compared with higher-achieving students who enter a teaching-intensive or college-technical institution. To improve completion by institutional type and among ethno-linguistic groups, our study highlights the need for research on why degree completion is lower at certain institutions for all ethno-linguistic groups and consistently lower among Korean, Tagalog, and Vietnamese speakers regardless of their level of academic achievement in high school or the type of post-secondary institution they initially entered.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".