Regimes of justification in the datafied workplace: the case of hiring

Dencik, Lina and Stevens, Sanne. 2023. Regimes of justification in the datafied workplace: the case of hiring. New Media and Society, 25(12), pp. 3657-3675. ISSN 1461-4448 [Article]

[img]
Preview
Text
14614448211052893.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (180kB) | Preview

Abstract or Description

The uptake of data-driven hiring systems has introduced important questions about how decisions about who is eligible for jobs, and why, are changing. To explore this, the article draws on interviews with prominent providers of data-driven hiring systems and analyses the way they situate the provision of tools in relation to existing hiring processes, what problems they claim to solve, and the nature of the solutions they provide. While the ideological grounds of datafication have been well-established, privileging data-driven knowledge production as less biased, more objective, and with superior insights than other forms of information-gathering, in hiring, we find legitimisation frames extend to ways in which work and workers should be organised and assessed. Drawing on the notion of 'regimes of justification', we argue that such legitimisation frames in turn invoke certain normative expectations about what is just and unjust organised around a vision of the common good.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.1177/14614448211052893

Additional Information:

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research of Lina Dencik was supported by the ERC Starting Grant DATAJUSTICE (grant no. 759903) under the Horizon 2020 research and innovation program.

Keywords:

Automation, datafication, hiring, regimes of justification, work

Departments, Centres and Research Units:

Media, Communications and Cultural Studies

Dates:

DateEvent
24 September 2021Accepted
28 October 2021Published Online
December 2023Published

Item ID:

37251

Date Deposited:

12 Jul 2024 15:29

Last Modified:

16 Jul 2024 08:41

Peer Reviewed:

Yes, this version has been peer-reviewed.

URI:

https://research.gold.ac.uk/id/eprint/37251

View statistics for this item...

Edit Record Edit Record (login required)