LocalLaws/LOCUS-v1

LOCUS v1.0

This repository contains the dataset presented in the paper Freeing the Law with LOCUS: A Local Ordinance Corpus for the United States.

Dataset Summary

LOCUS v1.0 is a chunk-level dataset of U.S. municipal and county law text labeled by legal function. Each eligible chunk is assigned a function, a binary is_substantive label, and all substantive provisions are assigned a topic. The dataset is intended for legal text research, local-law structure analysis, substantive filtering, and downstream taxonomy refinement.

Dataset Structure

The unit of analysis is a text chunk derived from local law documents.

Scale

Approximate scope for v1: 2,211,516 ordinances

Label Schema

Function

Allowed values:

• Context
• Rules
• Process
• Enforcement

Substantive Indicator

The released dataset enforces the following deterministic rule:

• is_substantive = 1 for Rules and Enforcement
• is_substantive = 0 for Context, Process, and Structural

Topic

Used only when is_substantive = 1.

Allowed values:

• Buildings
• Business
• Nuisance
• Zoning
• Other

Recommended Uses

LOCUS v1.0 is appropriate for:

• legal text classification research
• local law structure analysis
• substantive versus non-substantive filtering
• downstream taxonomy refinement
• weakly supervised or human-in-the-loop legal NLP workflows

Out-of-Scope Uses

LOCUS v1.0 should not be treated as:

• legal advice
• a substitute for human legal review
• a complete census of all U.S. local law
• a fully human-validated benchmark without additional auditing

Citation

If you use this dataset, please cite:

@article{peskoff2026freeing,
  title={Freeing the Law with LOCUS: A Local Ordinance Corpus for the United States},
  author={Peskoff, Denis and Barrow, Joe and Vu, Christopher and Davenport, Diag},
  journal={arXiv preprint arXiv:2606.19334},
  year={2026}
}