JOURNAL ARTICLE

The Discovery of D'Ewes's Long Parliament Diary.

  • Published In: Parliamentary History, 2024, v. 43, n. 2. P. 166 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Mendle, Michael 3 of 3

Abstract

2023 marked the centenary of Wallace Notestein's edition of part of Sir Simonds D'Ewes's journal of the Long Parliament. This essay treats the diary's pre‐Notestein emergence as a prime source for the history of the Long Parliament. Thomas Carlyle was first to publicise the diary. He could not read it but paid for a 'transcript' of major passages. Though only indirectly useful to Carlyle's project of editing Oliver Cromwell's letters and speeches, the so‐called transcript prompted Carlyle to experiment at the boundary of history and fiction. Carlyle passed the transcript to the antiquary John Bruce and to John Forster. Both praised the diary, touted their paleographical skills, and also relied on the 'transcript'. Whatever their paleographical limitations, their enthusiasm canonised the text. When Samuel Rawson Gardiner turned to the Long Parliament, D'Ewes's diary joined the Thomason tracts and the State Papers as foundational sources. Though he owed his source‐agenda to Carlyle, Bruce, Forster and J. L. Sanford, Gardiner was determined to supersede them, in large part by correcting their use of D'Ewes's diary. In Forster's case, Gardiner verged on the patricidal. This was a moment in the bifurcation of 'history' from 'letters', and in the creation of the historical 'profession'. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Parliamentary History. 2024/06, Vol. 43, Issue 2, p166
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2024
  • ISSN:0264-2824
  • DOI:10.1111/1750-0206.12747
  • Accession Number:177678395
  • Copyright Statement:Copyright of Parliamentary History is the property of Wiley-Blackwell 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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