JOURNAL ARTICLE

The "Silent" Removal of Bibliometric Information of Three SSRN Preprints Related to Peer Review, and then their Full Reinstatement.

  • Published In: Preservation, Digital Technology & Culture, 2023, v. 52, n. 3. P. 85 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Teixeira da Silva, Jaime A. 3 of 3

Abstract

For data information scientists, librarians and academics alike, it is a worrisome sign when information or a file opaquely disappears from the body of scientific literature, even more so when it carries a digital object identifier (DOI). This is because the DOI typically offers a published paper a form of digital permanence. Preprints are being increasingly fused into the publication stream, serving as a prelude to submission to a peer-reviewed journal. One of the main preprint servers is Elsevier's SSRN. This paper, a rare case study, describes three preprints by the same authors related to peer review that were withdrawn (i.e., retracted). Apart from a short notice with identical text ("This paper has been removed from SSRN at the request of the author, SSRN, or the rights holder"), no date of the withdrawals and no explanation were publicly provided. Following queries to the authors and SSRN, the three preprints were reinstated around February 2023. Finally, the original title of two of the preprints was manipulated in the reinstated preprints. This historical case study not only highlights the risks of opaque preprint withdrawals, but also the ease with which information on preprint servers (in this case SSRN) can be modified and/or manipulated. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Preservation, Digital Technology & Culture. 2023/10, Vol. 52, Issue 3, p85
  • Document Type:Article
  • Subject Area:Computer Science
  • Publication Date:2023
  • ISSN:2195-2957
  • DOI:10.1515/pdtc-2023-0021
  • Accession Number:173035465
  • Copyright Statement:Copyright of Preservation, Digital Technology & Culture 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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