100% of first-gen college graduates receive aid
Bibliographic record
Abstract
With more than 60 first-generation college graduates currently earning their J.D. at the School of Law, we are pleased to share that 100% of them are receiving aid. This cohort is currently supported by more than 20 scholarship funds, including the First-Start Scholars Program established by 1982 alumna Kathelen V. Amos and the Daniel P. Amos Family Foundation. This initiative has grown from first-generation students in the 2019 J.D. entering class receiving a scholarship to every first-gen J.D. student getting aid for the third year in a row. The School of Law is redefining what it means to be a great national public law school by offering a world-class, hands-on, purpose-driven educational experience with a pioneering commitment to accessibility and affordability, according to Dean Peter B. "Bo" Rutledge. Some recent statistics supporting this statement include: #1 Best Value Law School for four of the last six years (National Jurist, 2018-23). Top-20 Law School (U.S. News & World Report, 2023-24). Nearly 99% Ultimate Bar Passage rate (Class of 2020). Almost 95% employment rate for full-time, long-term, bar pass required jobs within 10 months of graduation (Class of 2022). 18 clinics and externships, with 94% participation (Class of 2023). More than 50% reduction in aggregate annual student borrowing compared to 2013. Extremely competitive tuition and fees (the lowest among the Top-20 law schools ranked by U.S. News & World Report).
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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.093 | 0.031 |
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".