Unpacking the Countercyclicality of Post-Secondary Enrollment in the United States
Bibliographic record
Abstract
Using data from the Current Population Survey’s Education Supplement, we examine the countercyclicality of post-secondary education (PSE) enrollment in the U.S. between 1977 and 2023. The unemployment–enrollment relationship is weak prior to 2000 and when Covid-19 years are included, but it is much stronger in 2000-2019. Focusing on these two decades, we show that higher unemployment increases enrollment at both 2- and 4-year colleges. We also show that persistence (continued enrollment among prior PSE participants) accounts for a larger share of the countercyclicality than matriculation (new enrollments). As for matriculation, eighteen-year-olds experience a particularly pronounced increase in the probability of starting a 2-year college degree when unemployment is high. We also find that men in their 20s are more likely to start a 4-year college degree when economic conditions deteriorate.
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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 | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.006 |
| 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".