A central question for programs that involve constituents in the coproduction of government services, is what motivates constituents to participate. This study compares two perspectives on this question: the traditional public-as-citizen model treats participation as a function of a general civic disposition that extends to many forms of civic and political participation (e.g., volunteering, voting); and we introduce the public-as-partner model, which argues that a given program might rely upon any of the diverse array of human motivations, depending on its specific nature of participation required. We compare these using 311 systems, which provide a hotline and online tools for requesting non-emergency government services (e.g., graffiti removal), evaluating whether using 311 to contribute to neighborhood maintenance reflects a civic disposition or a capacity for territoriality (i.e., identifying with and claiming responsibility for spaces), per the public-as-partner model. The study links at the individual level three forms of information on a sample of 311 users from Boston, MA (n = 722): objective reporting activity, derived from the 311 archive; a user survey including self-reports of civic activities and territorial motives; and voter registration records. Controlling for demographics and the contextual effects of home neighborhood, higher territorial motives predicted a greater likelihood of a person reporting any issues of public concern, and reporting more issues over a broader geographical range in one’s home neighborhood (where >80% of reports are made). Civic activities and voting predicted a greater likelihood of reporting in non-home neighborhoods (e.g., work). This dichotomy highlights the distinction between the two models in conceptualizing the motivations for participation in coproduction. The paper explores how to extend this logic to the assessment of participation, outreach, and disparities in access across programs is discussed.
The distribution of wealth in the United States and countries around the world is highly skewed. How does visible economic inequality affect well-off individuals’ support for redistribution? Using a placebo-controlled field experiment, I randomize the presence of poverty-stricken people in public spaces frequented by the affluent. Passersby were asked to sign a petition calling for greater redistribution through a “millionaire’s tax.” Results from 2,591 solicitations show that in a real-world-setting exposure to inequality decreases affluent individuals’ willingness to redistribute. The finding that exposure to inequality begets inequality has fundamental implications for policymakers and informs our understanding of the effects of poverty, inequality, and economic segregation. Confederate race and socioeconomic status, both of which were randomized, are shown to interact such that treatment effects vary according to the race, as well as gender, of the subject.
Co-partisan legislators, and governors in control of state government, often direct public funds for projects and programs toward localities where their party attains high levels of electoral support. While we typically equate distributive goods with concrete projects, state-level financing formulae may also be subject to partisan manipulation. School finance reform, which often arises in response to court cases heard in a state’s supreme court, may provide just such an opportunity for manipulation. Using panel regression methods, this study shows that in the wake of judicial interventions that occurred in many U.S. states since the 1970s, transfers from states to local areas for the purposes of education were geographically targeted to co-partisan localities when one party controlled state government, in the period immediately following reform. The findings have important consequences for our understanding of how distributive politics occurs, and what types of goods it may target.
How does local demographic context shape political behavior? We investigate the effect of segregation, operationalized as white isolation, on racial voting in South Africa. Using a variety of new datasets, which include high resolution census data from before the end of Apartheid, we estimate effects by leveraging plausibly exogenous variation in the extent to which local segregation persisted after the end of Apartheid. Racial isolation is found to increase white racial voting, measured as the probability of whites voting against the African National Congress (ANC) or other non-white parties. Using geo-referenced survey data for over 39,000 people we then present individual level evidence consistent with our findings, and discuss potential mechanisms.
The effect of political violence on policy and attitudes has recently come back into scholarly and popular attention. Whether voters will punitively react to riots and other violence is a question of policy relevance and speaks to a long literature on intergroup bias. The Los Angeles Riots lasted from April 29 to May 4, 1992, and served as a focal point for race relations in the US. The riots strongly shifted political discourse prior to a statewide election on June 2. We argue that the riots served as an exogenous shock to the salience of racial issues, but a shock which affected Los Angeles voters differently depending on their race and spatial proximity to the riots. To causally identify the effect of the riots on behavior, we use the change in the difference between voter support for public education and higher education as proxy for attitude shifts in the wake of the riots. Using official election returns and survey data, we find that among white voters, the riot increased support for racial-minority targeted public goods, relative to other public goods. However, white voters increased support at lower rates than racial minorities and, among white voters, proximity to the epicenter of the riots is related to diminished support for spending on minority-targeted goods.
I introduce a new type of data that is increasingly available to social science researchers: geo-located real-time pedestrian traffic counts. Data on foot traffic, singular in its precision and temporal coverage, comes from a private company that uses a network of live video camera feeds and computer vision technology to calculate traffic levels in real time. After discussing the data structure and limitations, I present several social science applications that describe the relationship between space and ‘civic-ness’ in a highly walkable urban setting. First, I show how foot traffic counts can be used to study large events and gatherings by examining pedestrian flows during a recent political protest. Second, I use spatial kriging to interpolate hourly foot traffic in Manhattan, which is then overlaid with geo-located New York City 311 reports, a proxy for citizen engagement with local government. I explore how certain non-emergency issues are more likely to be reported under varying conditions. Next, I bring data on incidents of major crime and show that the most highly trafficked blocks are also the most dangerous. Finally, I conclude with ideas for the future use of the data.
How do citizens respond to unanticipated domestic crises and threats to public safety? Using a series of novel datasets, this study examines the political behavior of residents of Boston after the 2013 Boston Marathon Bombing and the manhunt that followed. The ten hour 'lockdown', or 'shelter in place', ordered by city officials during the manhunt directly affected nearly one million people. The lockdown changed behavior en masse, with most residents of Boston and certain nearby communities staying indoors until the order was lifted. This study sheds light on how these experiences altered citizens' expectations of local government performance, and how this impact varies over time and space. Voter-file data, data from Boston's Citizen Relationship Management (CRM) system, and census data, are used to explore these effects in a range of research designs. Finally, data from a survey experiment conducted days after the bombing is used to complement the observational findings.
Faculty and students planning research involving human subjects are required by their universities to pass formal certification tests and then submit research plans for prior approval. Those who diligently take the tests may better understand certain important legal requirements but, at the same time, are likely misled into thinking they can apply these rules to their own work which, in fact, they are not permitted to do. They will likely also be missing many other legal requirements not mentioned in the required training but which govern their behaviors. Finally, they are likely to completely misunderstand the essentially political situation they find themselves in. The resulting risks to their universities, collaborators, and careers may be catastrophic, in addition to contributing to the more common ordinary frustrations of researchers with the system. To avoid these problems, faculty and students conducting research about and for the public need to understand that they are public figures, to whom different rules apply, ones that political scientists have long studied. University administrators (and faculty in their part-time roles as administrators) need to reorient their perspectives as well. University research compliance bureaucracies have grown, in well-meaning but sometimes unproductive ways -- not required by federal laws or guidelines. We offer advice to faculty and students for how to deal with the system as it exists now, and suggestions for changes in university research compliance bureaucracies, that should benefit faculty, students, staff, university budgets, and our research subjects.
The relationship between residential stability and non-voting participation has been largely ignored in the study of context. Using individual-level reports on every 311 call for city services and a panel of individual-level, geocoded and personally identified, census data from a mid-sized northeastern U.S. city, we explore the relationship between the residential stability of neighborhoods and civic participation. We use individual census records to construct annual measures of residential churn, and its ethnic composition, at various levels of spatial aggregation. We then examine the correlation between churn and 311 calls in neighborhoods over time, as well as the causal effect of churn on a panel of individual 311 users observed over several years. We find that the composition of residential churn, rather than the quantity of new residents, has implications for local citizen engagement via 311.