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This paper looks closely at how data analytic providers leverage rankings as a part of their strategies to further extract rent and assets from the university beyond their traditional roles as publishers and citation data providers. Multinational publishers such as Elsevier, with over 2,500 journals in its portfolio, has transitioned to become a data analytic firm. Rankings expand their abilities to monetize further their existing journal holdings, as there is a strong association between publication in high-impact journals and improvement in rankings. The global academic publishing industry has become highly oligopolistic, and a small handful of legacy multinational firms are now publishing the majority of the world’s research output (See Larivière et. al. 2015; Fyfe et. al. 2017; Posada & Chen, 2018). It is therefore crucial that their roles and enormous market power in influencing university rankings be more closely scrutinized. We suggest that due to a combination of a lack of transparency regarding, for example, Elsevier’s data services and products and their self-positioning as a key intermediary in the commercial rankings business, they have managed to evade the social responsibilities and scrutiny that come with occupying such a critical public function in university evaluation. As the quest for ever-higher rankings often works in conflict with universities’ public missions, it is critical to raise questions about the governance of such private digital platforms and the compatibility between their private interests and the maintenance of universities’ public values.
university rankings, surveillance capitalism, algorithmic governance, data analytics, platform society, Knowledge infrastructure
university rankings, surveillance capitalism, algorithmic governance, data analytics, platform society, Knowledge infrastructure
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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| downloads | 62 |

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