JOURNAL ARTICLE

The House Freedom Caucus, Kevin McCarthy's Race for Speaker, and the Fate of Rules Reform in the 118th Congress.

  • Published In: Forum (2194-6183), 2023, v. 21, n. 2. P. 163 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Baer, Emily 3 of 3

Abstract

For the first time in one hundred years, the 118th Congress began with a prolonged Speaker's race that required fifteen ballots to elect a Speaker. The contentious Republican debate displayed a level of personal animosity between a faction – the House Freedom Caucus (HFC) – and the majority party's chosen leader – Rep. Kevin McCarthy (R-CA) – but it also revealed a series of significant divisions within the majority party over policy, and legislative norms and practices. How do different strategies shape the capacity of factions to spur formal changes to legislative institutions? How do party leaders respond to the demands of factions that raise issues threatening to party unity and their own leadership position? In this article, I analyze the composition of defectors in the Speaker's race, the status of their rule and procedural reform agenda, and the response by McCarthy, including to committee assignments and early use of restrictive rules in the 118th Congress. I conclude with a discussion of the consequences of the HFC strategy for the contemporary U.S. House, and an emerging need to expand theories of institutional change to better integrate the behavior of both party leaders and factions. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Forum (2194-6183). 2023/07, Vol. 21, Issue 2, p163
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2023
  • ISSN:2194-6183
  • DOI:10.1515/for-2023-2013
  • Accession Number:169953025
  • Copyright Statement:Copyright of Forum (2194-6183) is the property of De Gruyter and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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