This Article offers an empirical account of felon disenfranchisement and legal financial obligations in the era of mass incarceration. It focuses on a 2018 ballot initiative, known as Amendment 4, which sought to end lifetime disenfranchisement in Florida. At the time, the Republican-controlled state accounted for more than a quarter of the six million citizens disenfranchised across the United States. Marshaling hundreds of public information requests, the Article analyzes the petitions collected to qualify the initiative for the ballot, the ballots cast for its remarkable bipartisan victory, the voter registration records of people whose voting rights were restored, and the outstanding fines and fees that still prevent most people with felony convictions from voting. Part I offers a history of the campaign and the tradeoffs it made to win Republican support, including its decisions to deemphasize race and limit the scope of reform. Part II validates the campaign’s effort to depoliticize disenfranchisement by demonstrating the limited partisan consequences of restoring the right to vote to people with felony convictions. Finally, Part III shows how unpaid fines and fees undermined the campaign’s attempt to dismantle disenfranchisement. Despite Amendment 4, Florida continues to disenfranchise more citizens than any other state.
This article examines an important and thorny problem in interview research: How to assess whether what people say motivated their actions actually did so? We ask three questions: What specific challenges are at play? How have researchers addressed them? And how should those strategies be evaluated? We argue that such research faces at least five challenges—deception, recall error, reasonableness bias, intentionality bias, and single-motive bias—that more than a dozen strategies have been deployed to address them; that the strategies have been external, internal, or interactional in nature; and that each class of strategies demands distinct evaluation criteria. Researchers will likely fail to uncover motivation if they ignore the possibility of each challenge, conflate one challenge with another, or deploy strategies unmatched to the challenge at hand. Our work helps systematize the evaluation of interview-based studies of motivated action and strengthen the scientific foundations of in-depth interview research.
Does public campaign financing improve representation by reducing politicians’ re-liance on wealthy donors as advocates claim, or does it worsen representation by ex-panding the candidate marketplace to give extreme and non-representative candidatesan electoral boost? We conduct a novel analysis of public financing programs in Ari-zona, Connecticut, and Maine to causally identify the effect of a legislator’s fundingstatus on how closely she represents constituent preferences. Using multiple identifica-tion strategies, we show that candidates who exclusively use public campaign financingare more extreme and less representative of their districts than non-publicly financedcandidates. Our findings add new evidence to the electoral reform debate by demon-strating how replacing private campaign donations with public financing can actuallydamage substantive representation. We also advance the scholarship on how institu-tions affect substantive representation and candidate positioning as they respond tonew campaign financing structures.
Insurance is typically viewed as a mechanism for transferring resources from good to bad states. Insurance, however, may also transfer resources from high-liquidity periods to low-liquidity periods. We test for this type of transfer from health insurance by studying the distribution of Social Security checks among Medicare recipients. When Social Security checks are distributed, prescription fills increase by 6–12 percent among recipients who pay small copayments. We find no such pattern among recipients who face no copayments. The results demonstrate that more-complete insurance allows recipients to consume healthcare when they need it rather than only when they have cash.
Using mortality registers and administrative data on income and population, we develop new evidence on the magnitude of life expectancy inequality in Hungary and the scope for health policy in mitigating this. We document considerable inequalities in life expectancy at age 45 across settlement-level income groups, and show that these inequalities have increased between 1991–96 and 2011–16 for both men and women. We show that avoidable deaths play a large role in life expectancy inequality. Income-related inequalities in health behaviours, access to care, and healthcare use are all closely linked to the inequality in life expectancy.
Nine studies investigate when and why people may paradoxically prefer bad news—for example, hoping for an objectively worse injury or a higher-risk diagnosis over explicitly better alternatives. Using a combination of field surveys and randomized experiments, the research demonstrates that people may hope for relatively worse (vs. better) news in an effort to preemptively avoid subjectively difficult decisions (studies 1 and 2). This is because when worse news avoids a choice (study 3A)—for example, by “forcing one’s hand” or creating one dominant option that circumvents a fraught decision (study 3B)—it can relieve the decision-maker’s experience of personal responsibility (study 3C). However, because not all decisions warrant avoidance, not all decisions will elicit a preference for worse news; fewer people hope for worse news when facing subjectively easier (vs. harder) choices (studies 4A and B). Finally, this preference for worse news is not without consequence and may create perverse incentives for decision-makers, such as the tendency to forgo opportunities for improvement (studies 5A and B). The work contributes to the literature on decision avoidance and elucidates another strategy people use to circumvent difficult decisions: a propensity to hope for the worst.
We study the political economy of redistribution over a broad class of decision rules. Since the core is generically non-unique, we suggest a simple and elegant procedure to select a robust equilibrium. Our selected policy depends on the full income profile, and in particular, on the preferences of two decisive voters. The effect of increasing inequality on redistribution depends on the decision rule and the shape of the income distribution; redistribution will increase if both decisive voters are 'relatively poor', and decrease if at least one is sufficiently 'rich'. Additionally, redistribution decreases as the polity adopts increasingly stringent super-majority rules.
Does intensifying immigrationenforcement lead to under-reporting of crime among undocumented immigrants and their communities? We empirically test the claims of activists and legal advocates that the escalation of US Immigration and Customs Enforcement (ICE) activities in 2017 negatively impacted the willingness of undocumented immigrants and Hispanic communities to report crime. We hypothesize that ICE cooperation with local law enforcement, in particular, discourages undocumented immigrants and their Hispanic community members from reporting crime. Using a difference-in-difference approach and FBI Uniform Crime Reporting (UCR) data at the county level, we find that total reported crime fell from 2016 to 2017 in counties with higher shares of Hispanic individuals and in counties where local law enforcement had more cooperation with ICE. Using the National Crime Victimization Survey (NCVS), we show that these declines in the measured crime rate are driven by decreased crime reporting by Hispanic communities rather than by decreased crime commission or victimization. Finally, we replicate these results in a second case study by leveraging the staggered roll-out of the 2008–2014 Secure Communities program across US counties. Taken together, our findings add to a growing body of literature demonstrating how immigration enforcement reduces vulnerable populations’ access to state services, including the criminal justice system.
This paper joins a growing body of research linking measures of the physical environment to population well-being, with a focus on neighborhood toxins. Extending a national database on the social mobility of American children growing up in over 70,000 Census tracts, we explore the association between childhood exposure to two forms of pollutants and three socioeconomic outcomes for African Americans, whites, and Latinos. We find that children who grew up in Census tracts with higher levels of traffic-related air pollution and housing-derived lead risk experienced lower adult incomes on average relative to their parents and higher likelihoods of being incarcerated as an adult or having children as teenagers, after controlling for standard socio-demographic characteristics and metropolitan-level effects. The spatial distribution of these two pollutants is surprisingly different, however, with air pollution varying mostly between regions of the country while lead risk varies dramatically between neighborhoods within the same city. Yet, each pollutant predicts the three aspects of social mobility similarly, and we show important disparities in exposure by race. Differential exposure to environmental toxins in childhood may be a contributor to racial inequality in socioeconomic outcomes among adults.
Administrative records are increasingly used to identify registered voters who may have moved, with potential movers then sent postcards asking them to confirm their address of registration. It is important to understand how often these registrants did not move, and how often such an error is not corrected by the postcard confirmation process, because uncorrected errors make it more difficult for a registrant to subsequently vote. While federal privacy protections generally prevent researchers from observing the data necessary to estimate these quantities, we are able to study this process in Wisconsin because special poll books, available via public records requests, listed those registrants who were identified as potential movers and did not respond to a subsequent postcard. At least 4% of these registrants cast a ballot at their address of registration, with minority registrants twice as likely as white registrants to do so.
Legal disputes over laws that require certain forms of identification (ID) to vote mostly focus on the burden placed on people who do not possess ID. We contend that this singular focus ignores the burden imposed on people who do possess ID, but nonetheless cannot access it when voting. To measure this alternative conception of burden, we focus on Michigan, which allows anyone who lacks access to ID to vote after signing an affidavit. A sample of affidavits filed in the 2016 presidential election from a random set of precincts reveals that about 0.45 percent of voters lacked access to ID. Consistent with our broader conception of the burden of voter ID laws, nearly all voters who filed an affidavit were previously issued a still-active state ID. Importantly, we show minority voters were about five times more likely to lack access to ID than white voters. We also present survey evidence suggesting that people who live in states where voters are asked to show ID, as in Michigan, are more likely to incorrectly believe that access to ID is required to vote than are people who live in states that do not ask voters to show ID.
Urban researchers have long debated the extent to which metropolitan employment is monocentric, polycentric, or diffuse. In this paper I use high-resolution data based on unemployment insurance records to show that employment in US metropolitan areas is not centralized but is spatially concentrated. Unlike residents, who form a continuous surface covering most parts of each metropolitan area, jobs have a bimodal spatial distribution, with most blocks containing no jobs whatsoever and a small number having extremely high employment densities. Across the 100 largest Metropolitan Statistical Areas, about 75% of jobs are located on the 6.5% of built land in Census blocks with at least twice as many jobs as people. These relative proportions are extremely consistent across cities, even though they vary greatly in the physical density at which they are constructed. Motivated by these empirical regularities, I introduce an algorithm to identify contiguous business districts and classify them into four major types. Based solely on the relative densities of employment and population, this algorithm is both simpler to implement and more flexible than current approaches, requiring no metro-specific tuning parameters and no assumptions about urban spatial layout.
Corporations increasingly use personal data to offer individuals different products and prices. I present first-of-its-kind evidence about how U.S. consumers assess the fairness of companies using personal information in this way. Drawing on a nationally representative survey that asks respondents to rate how fair or unfair it is for car insurers and lenders to use various sorts of information—from credit scores to web browser history to residential moves—I find that everyday Americans make strong moral distinctions among types of data, even when they are told data predict consumer behavior (insurance claims and loan defaults, respectively). Open-ended responses show that people adjudicate fairness by drawing on shared understandings of whether data are logically related to the predicted outcome and whether the categories companies use conflate morally distinct individuals. These findings demonstrate how dynamics long studied by economic sociologists manifest in legitimating a new and important mode of market allocation.
Objectives. To examine how physical health symptoms developed and resolved in response to Hurricane Katrina.
Methods. We used data from a 2003 to 2018 study of young, low-income mothers who were living in New Orleans, Louisiana, when Hurricane Katrina struck in 2005 (n = 276). We fit logistic regressions to model the odds of first reporting or “developing” headaches or migraines, back problems, and digestive problems, and of experiencing remission or “recovery” from previously reported symptoms, across surveys.
Results. The prevalence of each symptom increased after Hurricane Katrina, but the odds of developing symptoms shortly before versus after the storm were comparable. The number of traumatic experiences endured during Hurricane Katrina increased the odds of developing back and digestive problems just after the hurricane. Headaches or migraines and back problems that developed shortly after Hurricane Katrina were more likely to resolve than those that developed just before the storm.
Conclusions. While traumatic experiences endured in disasters such as Hurricane Katrina appear to prompt the development of new physical symptoms, disaster-induced symptoms may be less likely to persist or become chronic than those emerging for other reasons.
Meredith Dost, Ryan Enos, and Jennifer Hochschild look at the crucial segment of American voters who have changed their views about Donald Trump since the 2016 presidential election. Using two original surveys, they find that attitudes on race and immigration, populism and authoritarianism, and the nation’s and their own economic well-being are all associated with loyalty to and switching from this divisive president.
How does an individual's criminal record shape interactions with the state and society? This article presents evidence from a nationwide field experiment in the United States, which shows that prospective applicants with criminal records are about 5 percentage points less likely to receive information from college admission offices. However, this bias does not extend to race: there is no difference in response rates to Black and White applicants. The authors further show that bias is all but absent in public bureaucracies, as discrimination against formerly incarcerated applicants is driven by private schools. Examining why bias is stronger for private colleges, the study demonstrates that the private–public difference persists even after accounting for college selectivity, socio-economic composition and school finances. Moving beyond the measurement of bias, an intervention designed to reduce discrimination is evaluated: whether an email from an advocate mitigates bias associated with a criminal record. No evidence is found that advocate endorsements decrease bureaucratic bias.
Segregation across social groups is an enduring feature of nearly all human societies and is associated with numerous social maladies. In many countries, reports of growing geographic political polarization raise concerns about the stability of democratic governance. Here, using advances in spatial data computation, we measure individual partisan segregation by calculating the local residential segregation of every registered voter in the United States, creating a spatially weighted measure for more than 180 million individuals. With these data, we present evidence of extensive partisan segregation in the country. A large proportion of voters live with virtually no exposure to voters from the other party in their residential environment. Such high levels of partisan isolation can be found across a range of places and densities and are distinct from racial and ethnic segregation. Moreover, Democrats and Republicans living in the same city, or even the same neighbourhood, are segregated by party.
Does contact across social groups influence sociopolitical behavior? This question is among the most studied in the social sciences with deep implications for the harmony of diverse societies. Yet, despite a voluminous body of scholarship, evidence around this question is limited to cross-sectional surveys that only measure short-term consequences of contact or to panel surveys with small samples covering short time periods. Using advances in machine learning that enable large-scale linkages across datasets, we examine the long-term determinants of sociopolitical behavior through an unprecedented individual-level analysis linking contemporary political records to the 1940 U.S. Census. These linked data allow us to measure the exact residential context of nearly every person in the United States in 1940 and, for men, connect this with the political behavior of those still alive over 70 years later. We find that, among white Americans, early-life exposure to black neighbors predicts Democratic partisanship over 70 years later.
Each year, U.S. child protection authorities investigate millions of families, disproportionately poor families and families of color. These investigations involve multiple home visits to collect information across numerous personal domains. How does the state gain such widespread entrée into the intimate, domestic lives of marginalized families? Predominant theories of surveillance offer little insight into this process and its implications. Analyzing observations of child maltreatment investigations in Connecticut and interviews with professionals reporting maltreatment, state investigators, and investigated mothers, this article argues that coupling assistance with coercive authority—a hallmark of contemporary poverty governance—generates an expansive surveillance of U.S. families by attracting referrals from adjacent systems. Educational, medical, and other professionals invite investigations of families far beyond those ultimately deemed maltreating, with the hope that child protection authorities’ dual therapeutic and coercive capacities can rehabilitate families, especially marginalized families. Yet even when investigations close, this arrangement, in which service systems channel families to an entity with coercive power, fosters apprehension among families and thwarts their institutional engagement. These findings demonstrate how, in an era of welfare retrenchment, rehabilitative poverty governance renders marginalized populations hyper-visible to the state in ways that may reinforce inequality and marginality.