Our COP26 events

Articulating and Categorising Ethnic Identity: Reflections on Politics of Recognition and (Mis)representation in ‘Big Data’ Using the EVENS Survey

Articulating and Categorising Ethnic Identity: Reflections on Politics of Recognition and (Mis)representation in ‘Big Data’ Using the EVENS Survey

Sociology; College of Social Sciences Hub
Date: Friday 23 February 2024
Time: 11:30 - 13:00
Venue: University of Glasgow, Main Building, Humanity Lecture Theatre (Room 255), University Avenue, Glasgow G12 8QQ
Category: Public lectures, Academic events, Student events, Staff workshops and seminars
Speaker: Professor Nissa Finney, University of St Andrews
Website: www.eventbrite.co.uk/e/articulating-and-categorising-ethnic-identity-tickets-753094113767

In a world awash with data how do we untangle ethnic identifications and their meanings, and how well do ‘big data’ capture ethnic identities? In this talk, Nissa considers how people articulate their ethnic identity, how this is – and isn’t - captured by statistical categorisations used as standard in Britian, and the implications of this for how we conduct research and the creation of knowledge on experiences of minoritized people. The presentation draws on a new, exciting national social survey that was led by Nissa – the Evidence for Equality National Survey (EVENS) – published in 2023 by the Centre on the Dynamics of Ethnicity (CoDE). EVENS documents the experiences of over 14,000 people and provides unrivalled data on the lives of ethnic and religious minorities in Britain.

​Using EVENS, Nissa draws out concepts that underpin articulations of ethnic identity and argues that new formulations of ethnic group categories are needed to reflect these, and to more fully represent the twenty percent of ethnic minorities whose identities are not well captured by current approaches. Focusing on two groups who are not routinely identified in official ethnicity data collection – Jewish and White Eastern European – Nissa discusses the power of recognition afforded (or not) through the creation (or not) of statistical categories, and the implications for whose experiences are silenced. 

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