Bibliographic record
Abstract
Student loans defer the cost of college until after graduation, allowing many students access to higher lifetime earnings and colleges and universities they otherwise could not afford. Even with student loans, however, the authors find that students psychologically realize the financial costs of a college education long before their loan repayments begin. This early cost realization frames financial decisions between most pairs of colleges as an intertemporal trade-off. Students choose between investments with (1) smaller short-term costs but smaller long-term returns (a lower-cost, lower-return [LC-LR] college) and (2) larger short-term costs but larger long-term returns (a higher-cost, higher-return [HC-HR] college). The authors find that early cost realization increases preferences for LC-LR colleges—preferences that could reduce lifetime earnings—in both simulations and experiments. Preferences for LC-LR colleges are pronounced among financially impatient students and in choice pairs of LC-LR and HC-HR colleges where the equilibrium is set at a low-discount-rate threshold. A return-on-investment strategy, future uncertainty, and debt aversion cannot explain these results. A decision aid synchronizing the psychological realization of costs and benefits reduced preferences for LC-LR colleges, illustrating that the preference is constructed and receptive to interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".