JOURNAL ARTICLE
Historians and the Impeachment of Andrew Johnson.
Published In: Journal of the Civil War Era, 2025, v. 15, n. 1. P. 81 1 of 3
Database: America: History and Life with Full Text 2 of 3
Authored By: Slap, Andrew L. 3 of 3
Abstract
Historians have analyzed and debated the impeachment of Andrew Johnson since it occurred in 1868. While most historians studying Johnson's impeachment have relied on similar sources and legal framing, their own backgrounds, lived experience, racial attitudes, and views of Reconstruction have led to very different interpretations. In the century and a half of literature, four broad schools of interpretation emerged: traditionalists, hagiographers, revisionists, and conservative revisionists. Traditionalists during the turn of the Twentieth Century and the hagiographers who followed had negative attitudes toward African Americans. Both groups also generally disliked Reconstruction and impeachment, while traditionalists often faulted Johnson the hagiographers lionized him. The revisionists came about during the civil rights movement with the broader revisionist positive interpretation of Reconstruction and support of African American rights. While the revisionists disliked Johnson and gradually became more supportive of impeachment, conservative revisionists arose in opposition to echo many of the positions of the earlier traditionalists and hagiographers. Renewed interest impeachment because of President Donald Trump and upheaval in race relations during the summer of 2020 suggest a new period of reexamining the first impeachment of a US President. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of the Civil War Era. 2025/03, Vol. 15, Issue 1, p81
- Document Type:Article
- Subject Area:History
- Publication Date:2025
- ISSN:2154-4727
- DOI:10.1353/cwe.2025.a952583
- Accession Number:183227667
- Copyright Statement:Copyright of Journal of the Civil War Era is the property of University of North Carolina Press 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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