Keeping College Options Open: A Field Experiment to Help all High School Seniors Through the College Application Process
Bibliographic record
Abstract
Abstract Recent research suggests that the college application process itself prevents access. This paper reports results from a school‐based experiment in which application assistance is incorporated into the high school curriculum for all graduating seniors at low‐transition schools. Over three workshops, students were guided to pick programs of interest that they were eligible for, apply for real, and complete the financial aid application. The goal was to create a real college option for exiting students to make the transition easier and more salient. Among all graduating seniors, the program increased application rates by 15 percentage points, and college going rates by 5 percentage points. Among those not taking advanced‐level courses, college enrollment increased by 9 percentage points. The program generated significant effects for a wide range of heterogeneous groups, including both males and females, those from urban and rural schools, and those with above and below average grades. While more intensive than other tested approaches, in‐class application assistance may provide a more effective approach for bridging the gap towards higher education.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".