Neighbourhood environmental problems, such as dog fouling and road repairs, are key issues for citizens and a core part of the business of local authorities. This doctoral research project provides an exciting opportunity for the successful candidate to work with local councils in Scotland, and the Scottish national Improvement Service for local government to understand more about these basic service issues.
As cuts to public services have been rolled-out since 2010, local councils have been forced to move from relying on regular neighbourhood and road inspections to target services such as cleaning or repairs, to relying much more on citizens reporting directly via email, web portals, telephone contact centres and also apps such as FixMyStreet. This means councils delivering the these environmental, waste and repair services hold a lot of administrative data: records of reports of issues by citizens; systems allocating jobs to work teams; audits of environmental quality in neighbourhoods. Some of this data is publicly available already, but is rarely presented at a neighbourhood-level using maps to allow comparisons between neighbourhoods.
The proposed PhD project would be co-produced with local councils, via the Improvement Service and with local authorities. It aims to understand the potential of such data in transforming how councils and citizens understand service delivery in neighbourhoods. It would explore what the barriers are to local councils make such data readily available to allow citizens to understand patterns of service delivery. It would also work with citizens to understand how they would interpret the data and the possible benefits and risks of this. Finally, it would work with partner local authorities and the Improvement Service to understand the benefits of using the data for informing service improvements and performance benchmarking by local councils.
The project would suit a candidate with an interest in local public services and neighbourhood conditions, who has excellent skills in statistical analysis and the ability to work well with partners outside academia, including communities and non-specialist audiences.