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Limits and Paradoxes of Accelerating Research. A Retrospective on the Attempts to Accelerate Medical Research on COVID-19.

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Title: Limits and Paradoxes of Accelerating Research. A Retrospective on the Attempts to Accelerate Medical Research on COVID-19.
Authors: Grieser, Christopher1 (AUTHOR) christopher.grieser@tu-berlin.de
Source: Minerva: A Review of Science, Learning & Policy. Mar2026, Vol. 64 Issue 1, p133-159. 27p.
Subject Terms: COVID-19, Medical research, Research integrity, University research, Information overload, Scientific method
Abstract: The COVID-19 pandemic led to a historically unprecedented effort to accelerate medical research on the novel coronavirus. At the same time, researchers have raised concerns that the attempts to expedite research had negative side effects, such as information overload or adverse impacts on research quality. This paper thus explores the question whether attempts to increase the pace of research do more harm than good and to what extent the acceleration of scientific knowledge production is even possible. To address these questions, this article proposes a multi-level perspective on research speed consisting of four interrelated dimensions: the speed of individual research activities, the number of concurrent research activities, the speed of knowledge circulation, and the usefulness of knowledge contributions for peers. A closer examination of medical research on COVID-19 reveals that attempts to accelerate research were inherently precarious: On the one hand, there are hard limits to the speed of research, while on the other, several measures intended to expedite research have side effects that can actually decelerate research. This ambiguous character of research acceleration creates difficult trade-offs that require careful consideration in science policy. [ABSTRACT FROM AUTHOR]
Copyright of Minerva: A Review of Science, Learning & Policy is the property of Springer Nature 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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  Data: Limits and Paradoxes of Accelerating Research. A Retrospective on the Attempts to Accelerate Medical Research on COVID-19.
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  Data: The COVID-19 pandemic led to a historically unprecedented effort to accelerate medical research on the novel coronavirus. At the same time, researchers have raised concerns that the attempts to expedite research had negative side effects, such as information overload or adverse impacts on research quality. This paper thus explores the question whether attempts to increase the pace of research do more harm than good and to what extent the acceleration of scientific knowledge production is even possible. To address these questions, this article proposes a multi-level perspective on research speed consisting of four interrelated dimensions: the speed of individual research activities, the number of concurrent research activities, the speed of knowledge circulation, and the usefulness of knowledge contributions for peers. A closer examination of medical research on COVID-19 reveals that attempts to accelerate research were inherently precarious: On the one hand, there are hard limits to the speed of research, while on the other, several measures intended to expedite research have side effects that can actually decelerate research. This ambiguous character of research acceleration creates difficult trade-offs that require careful consideration in science policy. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Minerva: A Review of Science, Learning & Policy is the property of Springer Nature 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.</i> (Copyright applies to all Abstracts.)
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