The gender gap in university participation: What role do skills and parents play?
Bibliographic record
Abstract
University participation among women has been increasing over the last 3 decades such that now in Canada more than half of all new degrees are awarded to women. Recent research has suggested that boys are also falling behind in their grades and educational as- pirations during high school. Both grades and aspirations re ect many different individual characteristics and socio-economic circumstances. To uncover the deeper determinants of the gender gap in university participation, I use the Youth in Transition Survey to estimate a factor model based on a framework developed by Foley, Gallipoli, and Green (2014). I use that model to identify and quantify the impact of three factors: cognitive skills, non- cognitive skills and parental valuations of education (PVE). I find that all three factors play an important role in explaining both the level and the gap in university participation. The factor structure as a whole accounts for 88 percent of the gender gap, and of that the PVE factor accounts for 28 percent. This result suggests that parents play a larger role than what is implied by decompositions employing only observed determinants.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".