Scaffolding decision spaces in decision support systems: Using plagiarism screening software in editorial offices
This paper explores the dynamics of algorithmic governance, decision support systems and human involvement in the context of plagiarism screening in academic publishing. While automated plagiarism screening is widespread in editorial work, critical investigations about these decision support systems...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2024-12-01
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| Series: | Big Data & Society |
| Online Access: | https://doi.org/10.1177/20539517241306371 |
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| Summary: | This paper explores the dynamics of algorithmic governance, decision support systems and human involvement in the context of plagiarism screening in academic publishing. While automated plagiarism screening is widespread in editorial work, critical investigations about these decision support systems remain scarce. Focusing on the issue of human autonomy and discretion in algorithmic governance, the paper investigates the complexities of the human-in-the-loop within these screening tools. Revisiting Wanda Orlikowski's conceptual metaphor of ‘scaffolding’, the study empirically analyses interactions between editors and plagiarism screening software. It traces how these tools act as scaffolds, defining plagiarism as a manageable problem while allowing editors considerable flexibility in decision-making. The software, which is both non-deterministic and powerful, transforms issues into potential decisions, shaping the decision space for human editors. Based on this investigation of screening software as scaffolding, the paper argues that the question of human involvement in systems for automated decision-making is somewhat beside the point, and that analytical attention should shift towards understanding how algorithmic systems configure decision spaces by establishing issues as decidable problems. The implications of this shift are discussed, emphasizing the need for advancing our understanding of power dynamics inherent in algorithm–human interactions within automated decision-making systems. |
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| ISSN: | 2053-9517 |