Data for good? Data practices and justification in the UK non-profit sector

Aula, Ville (2023) Data for good? Data practices and justification in the UK non-profit sector. PhD thesis, London School of Economics and Political Science.

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Abstract

The thesis analyses the politics and practices of data in the UK non-profit sector. It approaches the topic through scholarship in the Critical Data Studies field, which combines ideas from science and technology studies, sociology, and communications. The thesis focuses on the attempts to introduce new digital and quantitative measurement practices to the UK non-profit sector. The thesis develops a novel conceptual framework to analyse politics and practices of data. The conceptual framework combines John Law’s ideas on methods assemblages with a pragmatic sociology of value drawing upon Luc Boltanski and Laurent Thévenot. The central research question is “How are data practices used to demonstrate value in the UK non-profit sector?” To answer the question, the thesis uses Data for Good initiatives and interviews with non-profit data professionals as its empirical entry-point to non-profit sector data practices. The empirical analysis focuses on interviews with 35 non-profit sector data professionals, which are complemented with participation in Data for Good-themed events and public online information. Data practices are shown to be used to demonstrate value in two ways: demonstrate value by either serving as proof in epistemic disputes or by enacting versions of reality that help to demonstrate value in other situations of dispute. The analysis suggests that the increasing use of data is shaping the way non-profits seek to demonstrate the value of their work. Furthermore, it suggests that use of data can create contradictions that undermine the ideals increased use of data is meant to serve. The interviewees were found to be aware of these contradictions, but they are shown to push for better quantitative and digital data practices rather than for alternative ways of understanding epistemic value. Conceptualising quantitative data practices through my interpretation of the concept of epistemic value allows me to highlight the difference between local data practices, which are always partial and fallible, and the general logic of perceiving quantitative and digital data practices as a way of demonstrating greater epistemic value. The thesis contributes to research debates on non-profit sector data practices by arguing that data practices are linked to multiple different strategies to justify the value of non-profit work, which makes the politics of data relational and contingent. Moreover, the findings suggest that data science has found only limited use in the UK non-profit sector despite attempts to promote it. The thesis contributes to the Critical Data Studies field by developing and operationalising a new conceptual strategy. The approach of the thesis complements earlier literature on the politics of data practices by emphasising the connection between data practices and demonstrations of value and by using an inductive and symmetric approach to politics and normativity.

Item Type:	Thesis (PhD)
Additional Information:	© 2023 Ville Aula
Library of Congress subject classification:	H Social Sciences > H Social Sciences (General) H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HN Social history and conditions. Social problems. Social reform Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Sets:	Departments > Media and Communications
Supervisor:	Mansell, Robin and Powell, Alison
URI:	http://etheses.lse.ac.uk/id/eprint/4873

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