Bibliographic record
Abstract
This paper examines a natural experiment in which students at a large state university were randomly assigned roommates through a lottery system. We find that on average, males assigned to roommates who reported drinking in the year prior to entering college had one quarter-point lower GPA than those assigned to non-drinking roommates. The 10th percentile of their college GPA is half a point lower than among males assigned non-drinking roommates. For males who themselves drank frequently prior to college, assignment to a roommate who drank frequently prior to college reduces GPA by two-thirds of a point. Since students who drink frequently are particularly influenced by frequent-drinking roommates, substance-free housing programs could potentially lower average GPA by segregating drinkers. The effect of initial assignment to a drinking roommate persists and possibly even grows over time. In contrast, students' college GPA is not influenced by roommates' high school grades, admission test scores, or family background. Females' GPAs are not affected by roommates' drinking prior to college. Overall, these findings are more consistent with models in which peers change preferences than models in which they change endowments.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".