JOURNAL ARTICLE

A corpus-assisted critical metaphor analysis of movement metaphors in university presidents' responses to anti-black violence.

  • Published In: Metaphor & the Social World, 2026, v. 16, n. 1. P. 1 1 of 3

  • Database: Communication Source 2 of 3

  • Authored By: Adedayo, Victor 3 of 3

Abstract

This study employs corpus-assisted critical metaphor analysis (CMA) to examine movement metaphors in university presidents' responses to anti-black violence. With data retrieved from official responses of 25 R1 universities (i.e., universities with high research activity) following the 2020 murder of George Floyd, the study utilized Charteris-Black's critical metaphor analysis alongside keyword analysis to examine inherent ideological biases that frame institutional responses to systemic racism. The findings revealed that university presidents employ movement metaphors to construct positive self-representation through positionality and allyship, while simultaneously downplaying racist experiences, reinforcing colorblind ideologies, and perpetuating negative stereotypes. This suggests that university presidents prioritize institutional image over meaningful change, highlighting the performative nature of these statements in light of the current anti-DEI development. The study contributes to the scholarship on racial discourse in higher education by demonstrating how metaphors reinforce or challenge power structures and shape institutional narratives on racial justice. Ultimately, it calls for higher education leaders to move beyond symbolic gestures toward substantive commitments to racial equity. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Metaphor & the Social World. 2026/01, Vol. 16, Issue 1, p1
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2026
  • ISSN:2210-4070
  • DOI:10.1075/msw.24017.ade
  • Accession Number:193171420
  • Copyright Statement:Copyright of Metaphor & the Social World is the property of John Benjamins Publishing Co. 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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