Campus Safety Data Source Reference

Guide to understanding and using campus crime and fire safety data collected under the Clery Act.

CRITICAL: Value Encoding

The Education Data Portal mirrors use integer codes for categorical variables, not string labels:

Variable	Example Code	Meaning
bias	1	Race-based bias
crime_type	14	Intimidation
fips	6	California

See ./references/variable-definitions.md for complete code mappings.

Truth Hierarchy: When interpreting variable values, apply this priority:

1. •Actual data file (what you observe in the parquet/CSV) -- this IS the truth
2. •Live codebook (.xls in mirror) -- authoritative documentation, may lag
3. •This skill documentation -- convenient summary, may drift from codebook

If this documentation contradicts the codebook, trust the codebook. If the codebook contradicts observed data, trust the data and investigate. Use get_codebook_url() from fetch-patterns.md to download codebooks.

What is Campus Safety and Security Data?

The Campus Safety and Security (CSS) data comes from the annual survey required by the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act:

• •Federal mandate: All Title IV institutions must report crime and fire statistics annually
• •Consumer protection: Designed to inform students, parents, and employees about campus safety
• •Primary source: U.S. Department of Education Office of Postsecondary Education
• •Coverage: All postsecondary institutions receiving federal financial aid
• •Reporting period: Calendar year (January 1 - December 31)
• •Available years: 2005-2021 (hate crimes in Portal mirrors)
• •Primary identifier: unitid (IPEDS institution ID, 6-digit integer)
• •Official portal: https://ope.ed.gov/campussafety/
• •Portal mirror coverage: Hate crimes only. For primary offenses, VAWA, arrests, and fire safety, access the Department of Education portal directly.

Reference File Structure

Decision Trees

What type of crime data do I need?

Crime data type?
├─ Violent crimes (murder, assault, robbery, sex offenses)
│   └─ See ./references/crime-categories.md
├─ Property crimes (burglary, motor vehicle theft, arson)
│   └─ See ./references/crime-categories.md
├─ Sex offenses (rape, fondling, incest, statutory rape)
│   └─ See ./references/crime-categories.md
├─ Dating/domestic violence, stalking
│   └─ See ./references/vawa-offenses.md
├─ Hate crimes (bias-motivated)
│   └─ See ./references/hate-crimes.md
├─ Drug/alcohol/weapons violations
│   └─ See ./references/arrests-referrals.md
└─ Fire incidents in residence halls
    └─ See ./references/fire-safety.md

Where did the crime occur?

Understanding crime location?
├─ On-campus (main campus buildings/grounds)
│   └─ See ./references/campus-geography.md
├─ On-campus student housing (subset of on-campus)
│   └─ See ./references/campus-geography.md
├─ Public property (streets, sidewalks adjacent to campus)
│   └─ See ./references/campus-geography.md
├─ Noncampus (off-site but institution-controlled)
│   └─ See ./references/campus-geography.md
└─ Not sure which category
    └─ See ./references/campus-geography.md (definitions section)

Can I compare schools?

Planning institutional comparisons?
├─ Want to rank schools by safety
│   └─ See ./references/limitations.md (CRITICAL: comparability issues)
├─ Comparing similar institution types
│   └─ See ./references/limitations.md (controlling for factors)
├─ Analyzing trends over time
│   └─ See ./references/limitations.md (reporting changes)
└─ Understanding what statistics mean
    └─ See ./references/limitations.md (interpretation guidance)

Quick Reference: Crime Categories

Crime Type Codes (Portal Integer Encoding)

Note: Crime type code 99 (Total) is documented in some references but does NOT appear in the actual Portal mirror data. The data contains individual crime types 1-18 only.

Bias Category Codes (Portal Integer Encoding)

VAWA Offenses (Added 2013)

Hate Crime-Only Offenses

Codes 12-15 are only reported as hate crimes. They are not standalone Clery crimes unless bias-motivated.

Arrests and Disciplinary Referrals

Key Identifiers (Hate Crimes Dataset)

Note: The hate crimes dataset uses inst_name (not instnm). Columns like branch, address, city, zip, state, sector, enrollment are NOT present in the Portal mirror data. Join with IPEDS directory on unitid to obtain institutional characteristics.

Geographic Categories

Fire Safety Data

Fire data is reported only for on-campus student housing facilities:

Missing Data Codes

Empirically verified: The hate crimes dataset in the Portal mirror does NOT use -1, -2, or -3 coded values. All missing data appears as null. This differs from some other Portal datasets (e.g., CCD) that use negative integer codes. Always verify against the actual data.

Data Access

Datasets for Campus Safety are available via the mirror system. See datasets-reference.md for canonical paths, mirrors.yaml for mirror configuration, and fetch-patterns.md for fetch code patterns.

CRITICAL: Limited Data in Portal Mirrors -- Only hate crimes data is available in the Portal mirrors (1 dataset). For other campus safety data (primary offenses, VAWA, arrests/referrals, fire safety), access the Department of Education directly at https://ope.ed.gov/campussafety/. Consult datasets-reference.md for the authoritative list of available mirror datasets.

Codebooks are .xls files co-located with data in all mirrors. Use get_codebook_url() from fetch-patterns.md to construct download URLs:

url = get_codebook_url("csafety/codebook_colleges_csafety_hate_crimes")

Fetching Data

Use the fetch_from_mirrors() pattern from fetch-patterns.md:

import polars as pl

# Fetch hate crimes data (all years, single-file dataset)
df = fetch_from_mirrors("csafety/colleges_csafety_hate_crimes")

# Filter by year
df_2021 = df.filter(pl.col("year") == 2021)

# Filter by bias category (1 = Race)
race_crimes = df.filter(pl.col("bias") == 1)

# Filter by crime type (14 = Intimidation)
intimidation = df.filter(pl.col("crime_type") == 14)

# Filter by institution
institution = df.filter(pl.col("unitid") == 100654)

# Filter by state FIPS code (6 = California)
california = df.filter(pl.col("fips") == 6)

Direct from Department of Education (Non-Mirror Data)

For data NOT available in Portal mirrors (primary offenses, VAWA, arrests, fire safety):

• •Web tool: https://ope.ed.gov/campussafety/
• •Bulk download: Available through Campus Safety website
• •Custom reports: Generate by institution, state, or sector

Common Pitfalls

Reporting Timeline

Related Data Sources

Topic Index