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High-density housing, low density turnout

Municipal electorates across America are vocal, unrepresentative networks. With lower turnout rates than state and national elections, the local electoral process disproportionately elects white, older, home-owning officials. Voting and elected bodies align demographically, thus leading to a policy that disproportionately reflects the interests of white, older, home-owning voters (Levine Einstein, Ornstein, & Palmer, 2019). This cycle is problematic because it halts the passage of policy that reflects the interest of historically underrepresented voters: young people and people of color. I argue that, for local races, campaign methods disproportionately mobilize the social networks that white, older, home-owning voters belong to. Members of these groups disproportionately occupy low-density housing-building types that can be accessed and mobilized by all campaigns. I suggest a relationship exists between housing density and turnout, with voters residing in low-density housing
participating at higher rates in local elections. Therefore, local races have smaller budgets and fewer reserves to invest in mobilizing voters residing in high-density housing. To assess this relationship, I compare housing density - whether a voter
lives in low density or high-density housing - and individual voting records from 2017 to 2021 across four municipalities in Massachusetts: Cambridge, Boston, Somerville, and Worcester. I expect to find that compared to voters living in low-density housing, those residing in high-density housing - disproportionately young voters and voters of color - are turning out at lower rates in local elections than in the 2018 Midterm and 2020 Presidential Elections. To change this cycle, scholars must pay more attention to the role housing density plays in inhibiting local mobilization efforts, and campaigns must collaborate to mobilize voting members of all social networks, especially those residing in high-density housing.

Identiferoai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/45184
Date25 September 2022
CreatorsRichards, Sophie Marie
ContributorsPalmer, Maxwell
Source SetsBoston University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

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