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Winners of the UK Data Service Dissertation Award 2023

The UK Data Service is delighted to announce the winners of this year’s UK Data Service Dissertation Award.

The award celebrates undergraduate dissertations based on the use of archived data available through the UK Data Service. This year, Paula Surridge, Professor of Political Sociology at the University of Bristol and Dr Alita Nandi, Associate Director (Outreach) for Understanding Society, joined Dr Jen Buckley from the UK Data Service User Support and Training team as judges.

The judging panel reviewed the full dissertations of shortlisted entries before deciding on the three winning entries. Congratulations to the winners, who have all been awarded a prize of £300.

The winners

Aiste Timukaite, BA (Hons) Criminology, University of Manchester

Title: A quantitative analysis of victim’s rational decision to report violent crime: does trust in the police matter?

This dissertation aimed to better understand the factors that contribute to the under-reporting of violent crime. The focus was on how a victim’s attitudes towards the police may influence their perceptions of the costs and benefits associated with crime reporting.

Using data from the Crime Survey for England and Wales for 2017-2020, the dissertation examined how the reporting of crime to the police is associated with attitudes towards the police as well as demographic and situational characteristics. Through a series of binary logistic regression models, the analysis found no evidence that the decision to report victimisation is influenced by a victim’s trust in police effectiveness. However, factors such as the presence of a weapon and injury to the victim are important predictors of violent crime reporting, as well as sex and age.

Drawing on the results, Aiste proposed the need for further efforts to promote reporting amongst male and younger victims. The dissertation also stressed that while the analysis identified victim and situational characteristics associated with reporting crime to the police, they only accounted for a small fraction of the variation in violent crime reporting. Therefore, further research is needed to explore broader contexts that impact victims’ cost-benefit considerations of violent crime reporting.


Caitlin Lin, Population Health Sciences (Data Science), University College London (UCL)

Title: A quantitative study into the control of diabetes in older age: who goes on to have eye problems?

Caitlin’s dissertation focused on the relationship between diabetes and related eye problems in England. Using data from the English Longitudinal Study of Ageing’s large representative sample of older people, the dissertation was able to explore how diabetes is associated with the development of glaucoma, diabetic eye disease, macular degeneration and cataracts amongst older adults over time. The dissertation also examined how age, sex, physical activity and the medical management of diabetes are associated with the development of different eye conditions.

The results of a series of multilevel logistic regression models identified how diabetes is associated with diabetic eye disease, glaucoma and cataracts. The results also showed that engaging in physical activity more than once per week is negatively associated with developing diabetic eye disease.

A key recommendation from the dissertation was that the treatment and prevention of eye problems amongst patients with diabetes should include the promotion of physical activity in middle-age and older adult populations to promote healthy aging, as well as enhanced screening for eye conditions.


Finlay Yates, Economics (BA), Durham University

Title: The impact of the minimum wage on employment: An assessment of the effect of employer concentration

Finlay’s dissertation examined the impact of the introduction of the National Living Wage (NLW) on employment and assessed whether regional employer concentration mediated any of this impact.

The project used the Labour Force Survey Five-Quarter Longitudinal Datasets (April 2015 – June 2016 to January 2021 – March 2022). By tracking individuals over time, the data made it possible to examine changes in employment retention and hours worked prior to and after each minimum wage increase. The project used a standard difference-in-differences design to compare the employment outcomes of employees directly impacted by the minimum wage policy (the treatment group) to a comparison group of similar employees not affected by the policy. Supplementary data from the Inter-Departmental Business Register was integrated to examine the impact of regional employer concentration.

The analysis indicated that the effect of increases in the National Living Wage on employment retention were insignificant (except during the rather exceptional pandemic period of 2020). For weekly working hours, the analysis indicated a significant negative effect of the large increase in the National Living Wage in 2016 on weekly hours, with a decrease in working hours of around two hours per week, but no significant effect in later years (except for a positive effect for 2021 during the height of the post-lockdown opening of the economy). The results did not identify any impact of employer concentration on either employment outcomes. Considering the results, the policy recommendation was for gradual and cautious increases in minimum wages.