This site uses cookies

Some of these cookies are essential, while others help us to improve your experience by providing insights into how the site is being used.

For more detailed information please check our Cookie notice


Necessary cookies

Necessary cookies enable core functionality. This website cannot function properly without these cookies.


Cookies that measure website use

If you provide permission, we will use Google Analytics to measure how you use the website so we can improve it based on our understanding of user needs. Google Analytics sets cookies that store anonymised information about how you got to the site, the pages you visit, how long you spend on each page and what you click on while you’re visiting the site.

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

Author: William Holy-Hasted
Institution: University of Cambridge
Type of case study: Research

About the research

William researched Human, Social and Political Sciences at the University of Cambridge.

William’s project investigated the association between London residents’ wellbeing and the amount of public space in their neighborhood. He explored whether different forms of public space have different effects on wellbeing, comparing the effects of green space (i.e parks) and hard-surface spaces (i.e. civic squares and children’s playgrounds). In order to look at differences over the socioeconomic spectrum, he also explored the impact for residents living in different housing tenures (homeowners and private and social renters).

Data

William used data from Wave 6 of Understanding Society (a multi-topic longitudinal study) to look at resident’s subjective wellbeing. He also matched Understanding society’s special license geographical data with public data from Greenspace Information for Greater London, in order to calculate the amount of public space in different areas.

“[This data was] chosen due to its fine-area geographic data, which other wellbeing surveys, such as the Annual Population Survey and European Quality of Life Survey, do not record”

Methodology

William used regression models to investigate the research questions, including individual models for each housing tenure. He also used interaction terms to examine whether the association between public space and well-being depends on neighbourhood safety.

Findings

The main findings from William’s project were that:

  • Green space was positively associated with wellbeing
  • In wards where feelings of safety are generally high, hard space was positively associated with wellbeing, but in wards with low safety, the inverse was true.
  • The impact of feelings of safety on the connection between hard-space and well-being was greater for social renters.
  • Greenspace’s positive association with wellbeing was consistent across all housing tenures.

“The interaction effect of hard space and safety, however, was especially pronounced for social renters. This suggests that hard public space can offer the greatest benefits, but also the greatest dangers, for social renters”.

 

Top Tips

William’s top tip for students about to start a project or dissertation with secondary data is to start exploring datasets early:

“By playing around with various datasets at an early stage, one has the time to familiarize themselves with the differences between datasets, and understand their potential limitations and strengths”.

“By adding various datasets to my project, I was able to compare their attributes and choose what dataset most closely aligned with my research aims.”

 

Future plans

On competing his degree, William took part in online training in Python programming and was accepted on to a master’s degree in Economics and Quantitative Social Science.