Bibliographic record
Abstract
At least a quarter of college students in the United States graduate with more than one undergraduate major. This paper investigates how students decide on the composition of their paired majors - in other words, whether the majors chosen are substitutes or complements. Since students use both their preferences and their expectations about major-specific outcomes when choosing their majors, I collect innovative data on subjective expectations, drawn from a sample of Northwestern University sophomores. Despite showing substantial heterogeneity in beliefs, the students seem aware of differences across majors and have sensible beliefs about the outcomes. Students believe that their parents are more likely to approve majors associated with high social status and high returns in the labor market. I incorporate the subjective data in a choice model of double majors that also captures the notion of specialization. I find that enjoying the coursework and gaining approval of parents are the most important determinants in the choice of majors. The model estimates reject the hypothesis that students major in one field to pursue their own interests and in another for parents' approval. Instead, I find that gaining parents' approval and enjoying a field of study both academically and professionally are outcomes that students feel are important for both majors. However, I do find that students act strategically in their choice of majors by choosing ones that differ in their chances of completion and difficulty and in finding a job upon graduation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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 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".