metadata
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: lsat
dtype: float32
- name: gpa
dtype: float32
- name: race
dtype:
class_label:
names:
'0': Asian
'1': Black
'2': Hispanic
'3': White
- name: resident
dtype:
class_label:
names:
'0': out-of-state
'1': in-state
- name: college
dtype:
class_label:
names:
'0': Akron
'1': Arizona
'2': Arizona State
'3': Baltimore
'4': Buffalo
'5': Cincinnati
'6': Cleveland State
'7': George Mason
'8': Hawaii
'9': Houston
'10': Idaho
'11': Louisiana State
'12': Michigan
'13': Minnesota
'14': Missouri at Columbia
'15': Missouri at Kansas City
'16': Nevada Las Vegas
'17': North Carolina
'18': Northern Illinois
'19': Ohio State
'20': Virginia
'21': Washington
'22': West Virginia
'23': William and Mary
'24': Wyoming
- name: year
dtype:
class_label:
names:
'0': '2005'
'1': '2006'
'2': '2007'
'3': '2008'
'4': 200x
- name: gender
dtype:
class_label:
names:
'0': female
'1': male
- name: admit
dtype:
class_label:
names:
'0': denied
'1': admitted
- name: black
dtype:
class_label:
names:
'0': 0
'1': 1
- name: hispanic
dtype:
class_label:
names:
'0': 0
'1': 1
- name: asian
dtype:
class_label:
names:
'0': 0
'1': 1
- name: white
dtype:
class_label:
names:
'0': 0
'1': 1
- name: missingrace
dtype:
class_label:
names:
'0': 0
'1': 1
- name: urm
dtype:
class_label:
names:
'0': 0
'1': Black OR Hispanic
- name: enroll
dtype:
class_label:
names:
'0': not enrolled
'1': enrolled
splits:
- name: train
num_bytes: 14090514
num_examples: 124557
download_size: 1062910
dataset_size: 14090514
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}
}