A Professor Like Me: The Influence of Instructor Gender on College Achievement
Bibliographic record
Abstract
Many wonder whether teacher gender plays an important role in higher education by influencing student achievement and subject interest.The data used in this paper helps identify average effects from male and female college students assigned to male or female teachers.In contrast to previous work at the primary and secondary school level, our focus on large first-year undergraduate classes isolates gender interaction effects due to students reacting to instructors rather than instructors reacting to students.In addition, by focusing on college, we examine the extent to which gender interactions may exist at later ages.We find that assignment to a same-sex instructor boosts relative grade performance and the likelihood of completing a course, but the magnitudes of these effects are small.A same-sex instructor increases average grade performance by at most 5 percent of its standard deviation and decreases the likelihood of dropping a course by 1.2 percentage points.The effects are similar when conditioning on initial ability (high school achievement), and ethnic background (mother tongue not English), but smaller when conditioning on mathematics and science courses.The effects of same-sex instructors on upper-year course selection are insignificant.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".