Dan Heaton
“The algorithm will screw you”: Blame, social actors and the 2020 A Level results algorithm on Twitter
Heaton, Dan; Nichele, Elena; Clos, Jeremie; Fischer, Joel E.
Authors
Elena Nichele
Mr Jeremie Clos JEREMIE.CLOS@NOTTINGHAM.AC.UK
ASSISTANT PROFESSOR
Professor JOEL FISCHER Joel.Fischer@nottingham.ac.uk
PROFESSOR OF HUMAN-COMPUTER INTERACTION
Contributors
Michal Ptaszynski
Editor
Abstract
In August 2020, the UK government and regulation body Ofqual replaced school examinations with automatically computed A Level grades in England and Wales. This algorithm factored in school attainment in each subject over the previous three years. Government officials initially stated that the algorithm was used to combat grade inflation. After public outcry, teacher assessment grades used instead. Views concerning who was to blame for this scandal were expressed on the social media website Twitter. While previous work used NLP-based opinion mining computational linguistic tools to analyse this discourse, shortcomings included accuracy issues, difficulties in interpretation and limited conclusions on who authors blamed. Thus, we chose to complement this research by analysing 18,239 tweets relating to the A Level algorithm using Corpus Linguistics (CL) and Critical Discourse Analysis (CDA), underpinned by social actor representation. We examined how blame was attributed to different entities who were presented as social actors or having social agency. Through analysing transitivity in this discourse, we found the algorithm itself, the UK government and Ofqual were all implicated as potentially responsible as social actors through active agency, agency metaphor possession and instances of passive constructions. According to our results, students were found to have limited blame through the same analysis. We discuss how this builds upon existing research where the algorithm is implicated and how such a wide range of constructions obscure blame. Methodologically, we demonstrated that CL and CDA complement existing NLP-based computational linguistic tools in researching the 2020 A Level algorithm; however, there is further scope for how these approaches can be used in an iterative manner.
Citation
Heaton, D., Nichele, E., Clos, J., & Fischer, J. E. (2023). “The algorithm will screw you”: Blame, social actors and the 2020 A Level results algorithm on Twitter. PLoS ONE, 18(7), Article e0288662. https://doi.org/10.1371/journal.pone.0288662
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 30, 2023 |
Online Publication Date | Jul 26, 2023 |
Publication Date | Jul 26, 2023 |
Deposit Date | Mar 19, 2025 |
Publicly Available Date | Mar 19, 2025 |
Journal | PLoS ONE |
Electronic ISSN | 1932-6203 |
Publisher | Public Library of Science |
Peer Reviewed | Peer Reviewed |
Volume | 18 |
Issue | 7 |
Article Number | e0288662. |
DOI | https://doi.org/10.1371/journal.pone.0288662 |
Keywords | Multidisciplinary |
Public URL | https://nottingham-repository.worktribe.com/output/23488378 |
Publisher URL | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0288662 |
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“The Algorithm Will Screw You”: Blame, Social Actors And The 2020 A Level Results Algorithm On Twitter
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Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
Copyright Statement
Copyright: © 2023 Heaton et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and
reproduction in any medium, provided the original author and source are credited.
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