• Corpus ID: 53056110

Who Calls for Help ? Statistical evidence of disparities in citizen-government interactions using geospatial survey and 311 data from Kansas City

@inproceedings{Kontokosta2018WhoCF,
  title={Who Calls for Help ? Statistical evidence of disparities in citizen-government interactions using geospatial survey and 311 data from Kansas City},
  author={Constantine E. Kontokosta},
  year={2018}
}

• Constantine E. Kontokosta
• Published 2018
• Political Science

Local governments are increasingly turning to ’311’ citizen complaints and service reports to provide a real-time condition assessment of the city. When combined with machine learning and predictive analytics, these data can be mined to gain new insight into city service needs and potential problems, including quality-of-life issues like rodent infestations, illegally converted buildings, and heat and hot water outages. However, we know that people do not complain at the same rate, and the willingness to interact with local government varies with socioeconomic, demographic, and cultural traits, as well as individual exposures to negative conditions. The goal of this preliminary work with the Kansas City Office of Performance Management (OPM) is to understand the disparities in the use of 311 and to identify the individual characteristics that impact citizen-government engagement and interaction. To do so, we use results from a citizen satisfaction survey administered by OPM that consists of 21,046 individual responses from 2014 to 2017. We combine these data with more than 500,000 311 reports and approximately 200,000 code enforcement violations to develop a statistical model to predict the likelihood of 311 reporting about neighborhood and property issues (code enforcement) based on household demographic and socioeconomic characteristics, as well as measures of community engagement and political participation. Furthermore, we explore the relationship between 311 usage and citizen satisfaction with city government, testing the hypothesis that there is a positive relationship between citizen participation in government processes (co-production) and overall citizen satisfaction. The insights of our preliminary work form the basis of acknowledging and accounting for the data bias problem of the citizen self-reported data, and contribute to the more equitable allocation and delivery of city services.