cestwc/law-school-admissions

Law School Admission Dataset

Dataset Overview

The Law School Admission Dataset provides detailed application and admission records from 25 law schools for the 2005, 2006, and, in some cases, 2007 and 2008 admission cycles. The dataset includes over 100,000 individual applications and contains variables related to academic performance, demographics, residency, and admission decisions.

Dataset Structure

• Number of examples: 124,557
• Number of features: 14
• Dataset size: 13.98 MB (compressed)
• Download size: 1.08 MB

Features

Feature Name	Type	Description
lsat	float32	LSAT score (scaled from 120 to 180). Some schools used a different scale, which has been recoded.
gpa	float32	Undergraduate GPA on a 4-point scale.
race	categorical	Self-reported race: Asian, Black, Hispanic, White, or missing.
resident	categorical	Residency status: in-state (1) or out-of-state (0).
college	categorical	Undergraduate institution (aggregated to 25 unique institutions).
year	categorical	Intended enrollment year: 2005, 2006, 2007, 2008, or suppressed as 200x.
gender	categorical	Male (1) or Female (0).
admit	categorical	Admission decision: admitted (1) or denied (0).
black	binary	Indicator variable for Black applicants (1 = Black, 0 = not Black).
hispanic	binary	Indicator variable for Hispanic applicants (1 = Hispanic, 0 = not Hispanic).
asian	binary	Indicator variable for Asian applicants (1 = Asian, 0 = not Asian).
white	binary	Indicator variable for White applicants (1 = White, 0 = not White).
missingrace	binary	Indicator for missing race information.
urm	binary	Underrepresented minority (URM): 1 if Black OR Hispanic, 0 otherwise.
enroll	categorical	Enrollment decision conditional on admission: 1 = enrolled, 0 = not enrolled or deferred.

Data Collection & Processing

• Source: Law school application records for 25 institutions.
• Privacy Measures: To minimize re-identification risks:
  • Small cell sizes (<5 individuals) were aggregated.
  • Black and Hispanic applicants were grouped as URM in some cases.
  • Gender and year variables were suppressed where necessary to maintain anonymity.
• Data Cleaning:
  • LSAT scores recoded for schools that used non-standard scales.
  • Outliers removed (erroneous data entries).

Dataset Splits

• Train split: 124,557 records
• Configs: Single configuration (default)
• Data Files: Stored in the data/train-* format.

Intended Uses & Applications

This dataset is useful for:

• Law school admission modeling
• Fairness and bias analysis in admissions decisions
• Predictive analytics for law school acceptance
• Educational policy research

Limitations & Considerations

• Aggregated and suppressed categories may limit granular subgroup analysis.
• Only includes applicants from 25 schools, not representative of all U.S. law schools.
• Admission decisions do not capture subjective evaluation factors (e.g., essays, recommendations).

Citation

If you use this dataset, please consider cite the following works (these might be inaccurate, but note that the publication by Linda F. Wightman (especially the 1990s version) appears to be something else):

@article{smyth2004ethnic,
  title={Ethnic and Gender Differences in Science Graduation at Selective Colleges with Implications for Admission Policy and College Choice},
  author={Smyth, Frederick L. and McArdle, John J.},
  journal={Research in Higher Education},
  volume={45},
  number={4},
  pages={353--381},
  year={2004},
  publisher={Springer}
}

@article{arcidiacono2007representation,
  title={Representation versus Assimilation: How do Preferences in College Admissions Affect Social Interactions?},
  author={Arcidiacono, Peter and Khan, Shakeeb and Vigdor, Jacob L.},
  journal={Working Paper},
  year={2007},
  institution={Duke University}
}