I recently attended the Maryland Municipal League’s annual conference in Ocean City, MD. This conference brings together elected and appointed officials from many of Maryland’s 157 towns and cities. During the four-day conference we explored topics including consensus building, running effective meetings, budgeting and the upcoming 2020 census and many more.

It was clear from these sessions that social science and sociology can inform and provide valuable tools for local elected officials. For example, census participation is directly tied to resources for municipalities, states, and counties. Because census results require enumeration and don’t allow for any statistical inference based on nonresponse, complete participation is all the more important. As sociologists, we are equipped to understand the methodological consequences of methodological decisions and census outreach and apply them to our own strategies and interpretation of information. It is estimated that only about 75% of Prince George’s County residents were counted in 2010. We can safely assume that low-income communities and racial minorities are more likely to be undercounted, leading to further discrepancies in resources in marginalized communities. Funding tied to the census is estimated to be roughly $1,800 per person per year. Young children are particularly likely to be uncounted, leading to a lack of resources for their local schools. Recent attempts to add a citizenship question to the 2020 census have underscored these concerns. However, understanding the factors leading to non-response can help us as elected officials to approach the upcoming census strategically so that we can help to achieve accurate accounting for our community.

This starts with building trust in our community and educating residents. We have broader efforts to ensure that our community fully includes Spanish-speaking households, low-income families, and those who do not own their homes. We need to be aware of the importance of complete census participation, as well as the patterns in non-response that help us to predict and address inequalities in representation.