README.md

metadata

license: mit
task_categories:
  - text-classification
language:
  - en
tags:
  - legal
pretty_name: US 117th Congress Bills
size_categories:
  - 10K<n<100K

Dataset Card for Dataset US 117th Congress Bills

Dataset Description

• Homepage: https://hunterheidenreich.com/posts/us-117th-congress-data-exploration/
• Repository:
• Paper:
• Leaderboard:
• Point of Contact: Hunter Heidenreich

Dataset Summary

The US 117th Congress Bills dataset is a collection of all of the House Resolutions, House Joint Resolutions, Senate Resolutions, and Senate Joint Resolutions introduced during the 117th Congress (2021-2022). The task is to classify each bill into one of thirty-three major policy areas. There are 11,389 bills in the training split and 3,797 bills in the testing split.

Supported Tasks and Leaderboards

• text-classification: The goal is to classify each bill into one of thirty-three major policy areas. The dataset contains both a text label (policy_areas) and a class integer (y).

These classes correspond to:

• 0: Agriculture and Food
• 1: Animals
• 2: Armed Forces and National Security
• 3: Arts, Culture, Religion
• 4: Civil Rights and Liberties, Minority Issues
• 5: Commerce
• 6: Congress
• 7: Crime and Law Enforcement
• 8: Economics and Public Finance
• 9: Education
• 10: Emergency Management
• 11: Energy
• 12: Environmental Protection
• 13: Families
• 14: Finance and Financial Sector
• 15: Foreign Trade and International Finance
• 16: Government Operations and Politics
• 17: Health
• 18: Housing and Community Development
• 19: Immigration
• 20: International Affairs
• 21: Labor and Employment
• 22: Law
• 23: Native Americans
• 24: Private Legislation
• 25: Public Lands and Natural Resources
• 26: Science, Technology, Communications
• 27: Social Sciences and History
• 28: Social Welfare
• 29: Sports and Recreation
• 30: Taxation
• 31: Transportation and Public Works
• 32: Water Resources Development

There is no leaderboard currently.

Languages

English

Dataset Structure

Data Instances

index                                                          11047
id                                                          H.R.4536
policy_areas                                          Social Welfare
cur_summary        Welfare for Needs not Weed Act\nThis bill proh...
cur_text           To prohibit assistance provided under the prog...
title                                 Welfare for Needs not Weed Act
titles_official    To prohibit assistance provided under the prog...
titles_short                          Welfare for Needs not Weed Act
sponsor_name                                          Rep. Rice, Tom
sponsor_party                                                      R
sponsor_state                                                     SC
Name: 0, dtype: object

Data Fields

• index: A numeric index
• id: The unique bill ID as a string
• policy_areas: The key policy area as a string. This is the classification label.
• cur_summary: The latest summary of the bill as a string.
• cur_text: The latest text of the bill as a string.
• title: The core title of the bill, as labeled on Congress.gov, as a string.
• titles_official: All official titles of the bill (or nested legislation) as a string.
• titles_short: All short titles of the bill (or nested legislation) as a string.
• sponsor_name: The name of the primary representative sponsoring the legislation as a string.
• sponsor_party: The party of the primary sponsor as a string.
• sponsor_state: The home state of the primary sponsor as a string.

Data Splits

The dataset was split into a training and testing split using a stratefied sampling, due to the class imbalance in the dataset.

Using scikit-learn, a quarter of the data (by class) is reserved for testing:

train_ix, test_ix = train_test_split(ixs, test_size=0.25, stratify=df['y'], random_state=1234567)

Dataset Creation

Curation Rationale

This dataset was created to provide a new dataset at the intersection of NLP and legislation. Using this data for a simple major topic classification seemed like a practical first step.

Source Data

Initial Data Collection and Normalization

Data was collected from congress.gov with minimal pre-processing. Additional information about this datasets collection is discussed here.

Who are the source language producers?

Either Congressional Research Service or other congressional staffers.

Annotations

Who are the annotators?

Congressional Staff

Personal and Sensitive Information

None, this is publicly available text through congress.gov.

Additional Information

Licensing Information

MIT License