UGA School of Law enrolls accomplished and majority-female first-year class
Bibliographic record
Abstract
Tuesday, August 19, 2008 Writer: Heidi Murphy, 706/542-5172, hmurphy@uga.edu Contact: Paul B. Rollins, 706/542-7060, rollins@uga.edu UGA School of Law enrolls accomplished and majority-female first-year class Athens, Ga. - Today, one of the most academically talented classes in the University of Georgia School of Law's history begins the three-year pursuit of a law degree. The entering class is composed of 229 students, which represent a median undergraduate grade point average of 3.67 and a median Law School Admission Test score of 163, placing them among the top 12 percent of test takers nationwide. Both of these statistics tie existing school records. Furthermore, the top quarter of the class achieved an LSAT score of 164 or higher and an undergraduate GPA of at least 3.82. "We are very pleased with the caliber of this year's entering class," School of Law Director of Admissions Paul B. Rollins said. "Members of the admissions committee reviewed nearly 2,300 applications with the goal of identifying those who would excel in the study of law. One of the primary missions of the School of Law is to produce future leaders for our state, region and beyond. We are confident that this class continues our proud tradition." For the second time in School of Law history, the majority of the first-year class is composed of females. This year's class includes 115 females and 114 males. The only other time there was a majority female class was in 2004. The entering Class of 2008 also represents a diverse and accomplished group of students. Although the majority (76 percent) of the members of the class are state residents, the students come to the school from 22 different states. Approximately 22 percent self-identified as members of a minority group, including 28 students who called themselves African-Americans. Members of this class studied at 72 different undergraduate institutions. Among the most popular feeder schools for this class are: the University of Georgia (83), Emory University (17), Georgia State University (7), the University of Florida (7), the University of Virginia (7), the University of North Carolina at Chapel Hill (7), Furman University (6) and the Georgia Institute of Technology (5). The most popular undergraduate degrees are political science, business, English and history. The School of Law is routinely ranked among the top public law schools in the nation. ##
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.297 | 0.241 |
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".