City Research Online

Abstract

This paper presents findings on the correspondence of levels of digital systems and media use with a range of socio-economic and demographic measures in the U.K. Most research on inequalities in regard to digital systems and media has focused on access and skills. Building on prior work (Yates and Lockley, 2018; Yates, et al., 2015) we argue that inequalities in regard to digital systems and media are better understood around types of user and their correspondence to other key social variables — rather than solely individual skills and access. The analysis presented here covers a range of key demographic variables, especially those that are markers of distinct social disadvantage. We find that those not using the Internet have distinct characteristics — predominantly around age, education and deprivation levels. We also find that those undertaking limited uses (overall limited use or a very narrow range of uses) are all predominantly from lower socio-economic status backgrounds with variations due to age and education. The data used for the analysis is the recent U.K. Ofcom 2018–19 (n = 1,882) media literacy survey. The paper uses latent class analysis methods to inductively define user types. Multinomial and binary logistic regression are used to explore the correspondence of latent class group membership to key demographic variables. These insights have direct U.K. and international policy relevance as they are key to the development of strategies to tackle ongoing digital inequalities in U.K. society.

Publication Type:	Article
Additional Information:	This paper is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Authors retain copyright to their work published in First Monday.
Subjects:	H Social Sciences > HN Social history and conditions. Social problems. Social reform H Social Sciences > HT Communities. Classes. Races
Departments:	School of Policy & Global Affairs > Sociology & Criminology
SWORD Depositor:	Symplectic Administrator

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