Making College Worth It: A Review of Research on the Returns to Higher Education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent stories of soaring student debt levels and under-placed college graduates have caused some to question whether a college education is still a sound investment. In this paper, we review the literature on the returns to higher education in an attempt to determine who benefits from college. Despite the tremendous heterogeneity across potential college students, we conclude that the investment appears to payoff for both the average and marginal student. During the past three decades in particular, the earnings premium associated with a college education has risen substantially. Beyond the pecuniary benefits of higher education, we suggest that there also may exist non-pecuniary benefits. Given these findings, it is perhaps surprising that among recent cohorts college completion rates have stagnated. We discuss potential explanations for this trend and conclude by succinctly interpreting the evidence on how to make the most out of college.
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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 | 0.029 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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 it