James Mahoney

Professor Turner’s reply to my article focuses on the ways in which set-theoretic analysis can be used to help solve problems of causal heterogeneity in social science research. By contrast, I discuss the ways in which set-theoretic analysis can be used to help solve problems of conceptual heterogeneity. I identify conceptual heterogeneity as a ubiquitous problem that is disguised by psychological essentialism. The seriousness of this problem must be recognized for scholars to appreciate the advantages of constructivist set-theoretic analysis for the social sciences.

Psychological essentialism is a cognitive bias through which human beings conceive the entities around them as having inner essences and basic natures. Social scientists routinely generate flawed inferences because their methods require the truth of psychological essentialism. This article develops set-theoretic analysis as a scientific-constructivist approach that overcomes the bias of psychological essentialism. With this approach, the “sets” of set-theoretic analysis are mental phenomena that establish boundaries and identify similarities and differences among entities whose natural kind composition is not known. The approach is illustrated through a consideration of research on intelligence, race, and poverty in the United States.

Research Ethics, Volume 18, Issue 3, Page 226-240, July 2022. The ubiquitous use of social platforms across the globe makes them attractive options for investigating social phenomena including migration. However, the use of social media data raises several crucial ethical issues around the areas of informed consent, anonymity and profiling of individuals, which are particularly sensitive when looking at a population such as migrants, which is often considered as ‘vulnerable’. In this paper, we discuss how the opportunities and challenges related to social media research in the context of migration impact on the development of large-scale scientific projects. Building on the EU-funded research project PERCEPTIONS, we explore the concrete challenges experienced in such projects regarding profiling, informed consent, bias, data sharing and ethical approval procedures, as well as the strategies used to mitigate them. We draw from lessons learned in this project to discuss implications and recommendations to researchers, funders and university ethics review panels. This paper contributes to the growing discussion on the ethical challenges associated with big social data research projects on migration by highlighting concrete aspects stakeholders should be looking for and questioning when involved in such large-scale scientific projects where collaboration, data sharing and transformation and practicalities are of importance.