UK Data Service Dissertation Award winners

Jen Buckley

Jen Buckley introduces the winners of the UK Data Service Dissertation Award, exploring the work the undergraduate researchers have undertaken and what they hope to do next. 




This summer we have had the pleasure of judging entries to the UK Data Service Dissertation Award. Open to undergraduates from social science disciplines at UK universities, the award celebrates students who are writing excellent dissertations using secondary data.

This year’s entries

By the deadline in early June, we received 29 entries from students using varied data sources and addressing a wide range of research questions. Dissertations based on survey data were most common among the entries and it was exciting to see students using the major longitudinal studies. It was also wonderful to see students apply for special licence data and link waves of longitudinal studies within the timeframe of a dissertation project. Other entries included analysis of archived secondary qualitative data and data deposited in ReShare, the UK Data Service’s online data repository for researchers to archive, publish and share research data.

Disciplines represented among the entries include sociology, economics, criminology, psychology, international relations and politics.

The winning entries

Following both internal shortlisting and an anonymous review of the full shortlisted dissertations by the expert judging panel, we are delighted to announce this year’s three winning entries.

The Impact of EU Migration on UK productivity

Valeria Pasco Garfias, BSc (Hons) in Economics, University of Manchester

Valeria’s project examined the link between immigration from European Union (EU) counties and productivity in the UK. Since a significant fraction of immigration into the UK has comes from EU countries; understanding the impact of EU migration on economic outcomes has important implications for policy design. This includes the newly proposed points-based immigration system.

Valeria’s research exploited differences in exposure to EU migration across industry groupings between 2000-2016, a period which includes the 2004 EU enlargement. Valeria used the Labour Force Survey (LFS) to compute industry level figures including the share of EU and non-EU born migrants. This new data was then combined with ONS statistics on Multi-Factor Productivity (MFP), to model the relationship between EU immigration and productivity.

Valeria found that EU immigration into specific industry groupings after 2004 had a positive impact on UK productivity, especially in industries more dependent on EU migrant labour. These finding suggest that the end of free movement of labour, which has characterized EU migration into the UK for more than 25 years, could generate pressures in sectors that are heavily dependent on it.

Common Ground: A Study of Urban Public Space and Wellbeing across London

William Holy-Hasted, Human, Social and Political Sciences, University of Cambridge

William’s project examined the effect of urban public space on well-being in London, including differences in the impact of green space (i.e. parks) compared to hard-surface space (i.e. civic squares and children’s playgrounds).

The project used data from Wave 6 of Understanding Society combined with public space data from Greenspace Information for Greater London. Using Special License data, William could access ward of residence and link individuals to information about their geographical location.

William’s findings confirmed previous studies in showing positive associations between green space and well-being. William also found that hard space has a positive effect on well-being in neighbourhoods where feelings of safety are generally higher; in contrast, for areas where feelings of safety are lower, hard-space becomes negatively associated with well-being. The impact of feelings of safety on the connection between hard-space and well-being was greater for social renters. This result suggests that for social renters hard public space might offer some of the greatest benefits but also the greatest dangers.

William’s findings suggest the need to theoretically distinguish between different types of public space in future literature. It also implies that urban planning policy cannot focus on space alone. Instead, policy must also tackle the factors contributing to low neighbourhood safety in order to ensure hard public space’s positive effects.

How does class influence individual perceptions of the environmental crisis and the undertaking of pro-environmental behaviours?

Elizabeth Livesey, BA Social Science (Sociology & Philosophy), University of Manchester.

Elizabeth’s project examined the claim that some socio-economic groups are excluded from environmentalism. Using data from Understanding Society, Wave 4, 2012-14, she was able to examine the relationships between social class, perceptions of the environmental crisis and environmental behaviours.

Controlling for other individual factors including education and political affiliation, Elizabeth found that environmental perspectives and behaviours do vary across social classes. In relation to everyday environmental activities those in routine occupations are less likely to report activity, but social class differences are modest in size. However, social class matters more in relation to environmental perspectives and consumptions choices, with those in routine occupations more likely to indicate that the ‘environmental crisis’ has been exaggerated and more likely to purchase pro-environmental options. The findings suggest that socio-economic class, although not forcing total exclusion, has a significant effect on resources and agency to adopt environmental attitudes and behaviours.


The three winning students each deserve congratulations alongside their £300 award. On winning, Valeria explained that

“Knowing that I was one of the Award winners is very gratifying and makes me feel honoured and proud of all the effort I put into producing my dissertation”.

William commented on how it feels very satisfying to know that someone else has appreciated your work, but that overcoming the moments of frustration involved in data analysis may have been the real achievement.

In addition to our final three winners, we would also like to pass on congratulations to the other 26 entries; both the shortlisting and final judging process were difficult due to the number of excellent entries we received.

Secondary data analysis for dissertations

This year’s entries confirm what students can achieve within a dissertation project using secondary data. Indeed, the judge’s feedback talked about excellent topical dissertations, publishable work and outstanding use of data.

The winning students are also enthusiastic about opportunities to access and use high quality data. Based on her experience, Valeria says

“I would encourage more students to use secondary data from the UK Data Service … Secondary data allows for the study of so many different subjects. When writing an original piece of research, you use your own approach to exploit the available data and that can be very enriching for the academic community and society as a whole”.

Next steps

Looking to the future, Valeria and William are looking to develop their skills further by taking postgraduate courses this autumn involving more quantitative data analysis. William also spent lockdown developing computer programming skills and hopes to combine computer science with social science in future research.

For us at the UK Data Service, we are more excited than ever to launch the Dissertation Award for the forthcoming academic year this Autumn.

Behind the scenes, we are also working on more support for undergraduate dissertation students. This includes a second edition of our Using survey data guide, which is designed to support students doing dissertations and research projects. We are also writing case studies of dissertation projects with tips and trick from the students themselves. Students can also participate in online events for dissertation students in the Autumn and Spring.


About the author

Dr Jennifer Buckley is a Research Associate at the University of Manchester and part of User Support and Training for the UK Data Service. She develops training to support researchers and teachers with a special interest in learning resources that support the use of data in undergraduate social science teaching.

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