README.md

metadata

configs:
  - config_name: default
    data_files:
      - split: '113'
        path: data/usc-113-unified.parquet
      - split: '114'
        path: data/usc-114-unified.parquet
      - split: '115'
        path: data/usc-115-unified.parquet
      - split: '116'
        path: data/usc-116-unified.parquet
      - split: '117'
        path: data/usc-117-unified.parquet
      - split: '118'
        path: data/usc-118-unified.parquet
license: mit
language:
  - en

Dataset Description

This dataset is part of a family of datasets that provide convenient access to congressional data from the US Government Publishing Office via the GovInfo Bulk Data Repository. GovInfo provides bulk data in xml format. The raw xml files were downloaded using the congress repo. Further processing was done using the legisplain legisplain repo.

Hyperdemocracy Datasets

• usc-billstatus (metadata on each bill)
• usc-textversion (different text versions of bills in xml)
• usc-unified (combined metadata and text version xml)

UNIFIED (metadata + text for congresses 113-118)

bill status

• https://www.govinfo.gov/bulkdata/BILLSTATUS
• https://github.com/usgpo/bill-status/blob/main/BILLSTATUS-XML_User_User-Guide.md
• https://github.com/usgpo/bulk-data/blob/main/Bills-XML-User-Guide.md

text versions

• https://www.govinfo.gov/bulkdata/BILLS
• https://xml.house.gov/
• https://github.com/usgpo/bill-dtd?tab=readme-ov-file

Column Descriptions

Column	Description
legis_id	a unique ID for each bill ({congress_num}-{legis_type}-{legis_num})
congress_num	the congress number for the bill
legis_type	one of [hr, hres, hconres, hjres, s, sres, sconres, sjres] (see govinfo - types of legislation)
legis_num	bills in each congress and of each type get an incrementing number as part of their ID
bulk_path	XML file path during bulk download
lastmod	lastmod date during bulk download
bs_xml	contents of billstatus XML file
bs_json	billstatus XML parsed into JSON
tvs	every text version for this bill

Examples

The dataset is broken into splits (one split per congress number).

from datasets import load_dataset

# load each split into a `DatasetDict` keyed on congress number
dsd = load_dataset(path="hyperdemocracy/usc-unified")

# load a single congress number into a `Dataset`
ds = load_dataset(path="hyperdemocracy/usc-unified", split=117)

# load all congress numbers into a single `Dataset`
ds = load_dataset(path="hyperdemocracy/usc-unified", split="all")

Congress Number to Date Mapping

Congress Number	Years	Metadata	Text
118	2023-2024	True	True
117	2021-2022	True	True
116	2019-2020	True	True
115	2017-2018	True	True
114	2015-2016	True	True
113	2013-2014	True	True