A Dataset Showing a Century of Evolution in the Complexity of the United States Legal Code

We leverage OCR and Generative AI techniques to recover and clean printed historical editions of the Code. This enables computational analysis of federal law even in periods before web-based digital access. The processing pipeline includes:📄 Contents of U.S. Code: Word counts, unique word counts, entropy, scaling exponents, etc.🌲 Hierarchical Structure: Subtitle → Part → Chapter → Section → Subsection...🔗 Cross-Reference Relationships: Title-to-title citation relationshipsFor the small sample of our data, please check out our github repository https://github.com/Dawoon-Jeong0523/uscode-complexity🔍 A sample OCR text page (ocr_processing_gemini) for demonstration🌐 Web-based U.S. Code text from 1994 for structural parsing (Data Set 2)