BACKGROUND Research has shown that the circumstances surrounding birth may influence the timing of death. In the northern hemisphere, children born in spring and summer have a shorter lifespan than those born in fall and winter. OBJECTIVE We describe the effect of month of birth on adult lifespan (50+) in the United States in three ways. First, we estimate it between and within groups of siblings, accounting for unobserved factors at the family level. Second, we estimate the effect of birth month across a period of about 200 years (1700‒1899). Third, we examine geographical variation in the effect of birth month across US census areas. METHODS We estimate descriptive statistics and OLS regression models between and within siblinggroups. RESULTS We find an effect of birth month on lifespan. Individuals born in spring and summer have on average a shorter lifespan than those born in fall and winter. The effect is relatively consistent across cohorts, geographical census areas, and between and within families.We test different possible explanations for this result and find residual evidence that in utero debilitation may account for this result.

High-quality preschool programs are heralded as effective policy solutions to promote low-income children's development and lifelong wellbeing. Yet evaluations of recent preschool programs produce puzzling findings, including negative impacts, and divergent, weaker results than demonstration programs implemented in the 1960s and 70s. We provide potential explanations for why modern preschool programs have become less effective, focusing on changes in instructional practices and counterfactual conditions. We also address popular theories that likely do not explain weakening program effectiveness, such as lower preschool quality and low-quality subsequent environments. The field must take seriously the smaller positive, null, and negative impacts from modern programs and strive to understand why effects differ and how to improve program effectiveness through rigorous, longitudinal research.

The 1870 election in Maine resulted in a Re- publican sweep of statewide offices, of the five seats in the US House of Representatives that Maine then enjoyed, and of control of both houses of the Legislature.The issues in the elec- tion were similar to what the Republicans and Democrats had contested before, during and af- ter the Civil War: race, citizenship, and the reg- ulation of alcohol. What makes the 1870 elec- tion worthy of closer study is the availability of the 1870 Census in machine-readable format. The census that year asked respondents a pair of questions about their eligibility to vote and their being denied the right to vote. Cross-tab- ulating the answers from the census with town- level voting returns results in new views on the state of democracy in Maine. This article pres-ents information about the size of the Voting Eligible Population (VEP), variable turnout of voters, and the partisan orientation of Maine’s counties and towns.

Historically, Hispanic adults that answer health surveys in Spanish report worse health than those who answer in English. This paper documents a growing English-Spanish gap in self-reported health (SRH) among Hispanic adults in the United States between 1997 and 2018. Data are from the 1997–2018 National Health Interview Survey (NHIS). The analytic sample consisted of 189,024 Hispanic adults older than 18 with valid information for the variables considered in the study. Descriptive analyses indicate that Hispanic adults who answer the NHIS in Spanish report worse health than English respondents do across the period of analysis. Multivariable logistic regression analysis was used to study the English-Spanish gap in SRH and to track its evolution over the last 22 years. At baseline, Spanish respondents exhibited significantly worse levels of SRH than those who answered in English and this gap persisted across time and older cohorts. The gap was still present when demographic/socioeconomic characteristics and assimilation are considered. In the majority of the cases, there is a significant interaction between language of interview, and period and cohort indicators. The English-Spanish gap in self-reported health is not explained by demographic/socioeconomic characteristics or assimilation. It may be possible that there are differences in how Hispanic adults understand health categories items across different languages with differences observed depending on how self-reported health is operationalized.

Black queer geographies matter. Intersectionality is at the core of living and existing in this world as fully realized persons in a social landscape that would ask us to cast aside aspects of the self or hide them from view (Collins 2002, 2019; Collins and Bilge 2020; Crenshaw 1991). While these affirmative statements may ring true, even apparent, they tend not to guide many in practice and scholarship. Black queer geographies are often ignored, subsumed in a vacuum of details on or about Black people writ-large, or LGBTQ people writ-large (Cohen 1999, 2004; Cohen and Hunter 2007; Lorde 2012). In turn, our relative ignorance generates presentism on the development and articulation of racialized and queer urban geographies. Such maps of urban life are believed to be relatively new, lacking a true historical genealogy.

In my dissertation, I explore the connection between economic history and political economy in three ways. Chapter 1, studies the effects of a postal program in the U.S. at the turn of the 20th century and its role in increasing access to higher education. Chapter 2, co-authored with Alexey Makaring and Ricardo Pique, focuses on a historical episode of foreign annexation and its political ´ consequences. Chapter 3, co-authored with Matteo Magnaricotte, studies the effect of U.S. movies on electoral choices in Italy during the Cold War period. All chapters of my dissertation were written before I joined the Bank of Italy and, as such, views and opinions expressed in this paper do not represent in any way those of the Bank of Italy.

OUTLINE: •Introduction to IPUMS •Data Availability •Complete Count Data 1790-1950 •Linked census data 1850-1940 •Questions [a full guide and introduction to IPUMS and effective utilization]

We conduct the first quantitative assessment of federal college subsidies during the 1930s. Overlapping generation households invest in children’s education to maximize multigenerational utility, and the government subsidizes college to maximize enrollment subject to a budget constraint and recipients satisfying ability and income qualifications. A modelling innovation assigns children educational ability through a random regression to the population mean correlated with father’s presumed ability ranking via his percentile in fathers’ earnings distribution. Simulating the theoretical model, the equilibrium that replicates actual education distributions estimates federal college subsidies increased graduation rates of the cohort of White Americans reaching college age during the 1930s by 22.12% for men and 19.16% for women; the mean ability of subsidy recipients exceeded non-subsidized students’ mean .4 s.d. The program favored middle income groups. Most benefits accrued to high ability students with fathers in the 4th through 6th deciles of fathers’ earnings distribution. The subsidies had no effect on the graduation rates of high ability students in the bottom two deciles of fathers’ earnings. A more universal government policy that maximized stipends subject only to the budget and income criteria would have increased annual stipends by about 50 thousand while only decreasing college students’ mean ability .13 s.d. Gender biases favoring higher male graduation rates remain a puzzle.

Past researchers have used various categorizations of sleep duration to analyze how sleep duration is associated with mortality. Here we analyze eleven categorizations of sleep duration to analyze the best model fit in relation to mortality for the U.S. population and by gender. Data from the 2004–2018 National Health Interview Survey (n = 420,037) was linked to the National Death Index through 2019 (36,574 deaths). We fit Cox Proportional Hazard models with and without covariates and used Bayesian Information Criterion (BIC) to determine the optimal model for self-reported sleep duration. Different categorizations produced vastly different substantive results. Categorizations A (≤ 4, 5, 6, 7 [ref], 8, 9, or ≥10 h) and E (≤ 5, 6, 7 [ref], 8, 9, or ≥10 h) provided the best model fit. Both of these categorizations were “J-shaped” and there was no difference between 6 and 7 h, but other reported durations were associated with higher hazards of mortality. Overall, we document how different specifications of sleep duration within the same sample may lead to different conclusions regarding the risk of mortality and that the most optimal specification tends to include more hours of sleep and have a “J-shape.” The findings of this study can help researchers, clinicians, and policymakers better understand the relationship be- tween sleep and mortality and clarify the optimal sleep duration(s).

Problem, research strategy, and findings U.S. housing advocates have called for a fundamental rethinking of the nation’s federal housing policies. In this study, I examined the geographic and household-level consequences of a plan that redistributes federal income tax expenditures from homeowners to very-low-income households. I propose, defend, and illustrate the effects of the SHELTER plan, a redistributive policy that a) is revenue neutral, b) is tenure neutral, c) is progressive, d) prioritizes local redistribution, and e) targets excess revenues to affordable housing production subsidies in communities where an increase in cash-based housing assistance is most likely to inflate housing rents. I demonstrate that the savings from the elimination of four homeownership tax expenditures would provide more than enough revenue to fund a universal housing allowance for all very-low-income households. Ignoring housing market adjustments, the plan would reduce housing cost burdens for the nation’s very-low-income renters by 36% and reduce very-low-income homeowners’ cost burdens by 28%. Takeaway for practice The SHELTER plan would provide a new foundation for local affordable housing and community development practice. Very-low-income households would receive a guaranteed housing allowance with no strings attached and local planners would have new roles in the design and implementation of localized solutions to the affordable housing crisis.

We generate the first cross-city panel dataset of land-use reforms that increase or decrease allowed housing density and estimate their association with changes in housing supply and rents. To generate reform data, we use machine-learning algorithms to search US newspaper articles between 2000 and 2019, then manually code them to increase accuracy. We merge these data with US Postal Service information on per-city counts of addresses and Census data on demographics, rents, and units affordable to households of different incomes. We then estimate a fixed-effects model with city specific time trends to examine the relationships between land-use reforms and the supply and price of rental housing. We find that reforms that loosen restrictions are associated with a statistically significant 0.8% increase in housing supply within three to nine years of reform passage, accounting for new and existing stock. This increase occurs predominantly for units at the higher end of the rent price distribution; we find no statistically significant evidence that additional lower-cost units became available or moderated in cost in the years following reforms. However, impacts are positive across the affordability spectrum and we cannot rule out that impacts are equivalent across different income segments. Conversely, reforms that increase land-use restrictions and lower allowed densities are associated with increased median rents and a reduction in units affordable to middle-income renters.

High older voter turnout rates, an aging population, and organizations that serve the interests of older adults have historically contributed to the importance of older adults for elections. Since 2010, older voters have tended to vote Republican, with White older adults typically preferring Republican candidates, and Black and Hispanic older voters typically preferring Democratic candidates. In the 2020 election, 65+ voters showed a slow downward trend in favor of the Republican candidate compared to past elections. Grounded in a demographic, economic, and generational context, and considering theory and research from gerontology, political science, psychology, and sociology, this chapter will explore older voter turnout and candidate choice in the 2020 presidential election. The focus will be on considering past trends and public polling data to examine three key issues in relation to the behavior of older voters in 2020: the COVID-19 pandemic, presidential candidate platforms regarding aging-related policy, and the role of media and misinformation.

Introduction Middle Neighborhoods (MNs) are generally recognized for their safety, stability and affordability for residents. They also provide an important opportunity to give lower-income populations access to affordable housing and an overall higher quality of life, but the number of MNs is declining throughout the U.S. Recognizing these opportunities and challenges regarding MNs, the research team set out to fill in the existing knowledge gaps about which public policies and programmatic activities are effective at 1) stabilizing MNs and 2) providing equitable access for lower-income and marginalized populations to join and stay in MNs. A literature review revealed that there are not clear, consistent characteristics used to describe MNs and that they are not a nationally defined neighborhood type. A common way to define a Middle Neighborhood is by median household income, but this is only one dimension to consider. This report includes additional factors describing wealth, occupation, race, ethnicity, culture, and others. A strong class of middle-income households accompanied by low- and highincome groups is a quintessential feature of a healthy middle neighborhood. The neighborhood typology developed in this research study was intended to identify middle neighborhoods as a distinct neighborhood type. The factor analysis did not reveal any standalone middle neighborhood type. Because middle neighborhoods did not emerge directly from the typology, it became apparent that middle neighborhoods are more complex and complicated than researchers initially thought. This makes identifying them even more important if practitioners and policymakers intend to address the potential of these neighborhoods. This research furthers the work in identifying and defining middle neighborhoods by: 1) incorporating people- and place-based dimensions of neighborhoods beyond middle income and 2) expanding the geographical focus on middle neighborhoods outside of the traditional northeast and legacy city places. However, the creation of the typology was an exploratory effort, and further analysis and research that examines neighborhood change over time and incorporates regional and local dynamics should be conducted. Six regional case studies examined in this report help to illustrate the diverse forms middle neighborhoods can take, common challenges and concerns they face, and the efforts being made to preserve and develop them. The six cities selected were Cleveland, Ohio; Chicago, Illinois; South Milwaukee, Wisconsin; Charlotte, North Carolina; Plano, Texas; and Lakewood, Colorado. These case studies provide important information related to: 1) validation of the geographic delineation of using a census tract to categorize a neighborhood; 2) identification of essential information on the policy process in these areas; and 3) discovery of the best practices of each MN. 5 Trends  Inflation in real estate and tightening rental markets are national trends since the start of the pandemic. These are mirrored in most of the case studies.  While some neighborhoods that had very low housing acquisition costs before the pandemic rose but remain relatively affordable, other neighborhoods have seen homes in middle neighborhoods (or previously middle) skyrocket in price and become unattainable for many.  Most of the case study middle neighborhoods are experiencing population growth, but many are struggling to keep the cost of living affordable.  However, there are exceptions, with some neighborhoods—particularly those in the Midwest—staving off decline. Targeted policy is needed to maintain these areas. There are many policy options to strengthen these neighborhoods, many of which have proven effective in various neighborhoods around the country. While financial capital is necessary, the importance of social capital for preserving middle neighborhoods must also be included. Ultimately, the best policy solutions are as diverse as middle neighborhoods themselves.

The US social safety net includes a range of programs to help families with lower incomes obtain additional cash income, additional resources for food, and help with housing, child care expenses, and energy costs. However, many of the people who are eligible for these programs do not receive help. One barrier is that some programs, including housing assistance, are not funded at a level that would serve all eligible households. Previously, we estimated that full funding and participation in six benefit programs (not including housing assistance) would reduce the poverty rate as measured by the Supplemental Poverty Measure (SPM) from 14.7 percent to 12.1 percent. If all households eligible for housing assistance were then provided with a housing voucher and found a rental unit that would accept it, the poverty rate would fall further to 10.1 percent (Giannarelli et al. 2023). Here, we estimate the antipoverty effect of full funding and provision of housing assistance separately, without the assumption of full funding and participation in other government programs. We estimate the effect of full funding and full use of housing vouchers using projected 2022 data from the Analysis of Transfers, Taxes, and Income Security (ATTIS) microsimulation model. We show results in terms of aggregate benefit dollars and reductions in poverty as measured by the SPM, both nationally and at the state level. We also examine results by age group and by race and ethnicity. Key findings include the following:  Households currently receiving housing assistance represent 25 percent of households that would receive assistance with full funding and use of housing vouchers.  With full funding and use of housing vouchers, total housing subsidies would increase by over three times, from about $50 billion to $168 billion per year.  Full funding and use of housing vouchers would reduce the share of people with resources below the SPM poverty level from 14.7 to 12.8 percent, a reduction of 13 percent.  The child poverty rate would fall by 23 percent, poverty among adults ages 18 to 64 would fall by 12 percent, and poverty among adults 65 and older would fall by 7 percent.  Hispanic people would have the largest reduction in poverty (19 percent), followed by Black, non-Hispanic people (15 percent), Asian and Pacific Islander people who are not Hispanic (13 percent), and white, non-Hispanic people (9 percent).  Poverty would fall by 13 percent for citizens and 14 percent for noncitizens.  Poverty would fall across states, with the reduction ranging from 4 percent in Kentucky and West Virginia to 24 percent in Hawaii and 25 percent in California. Child poverty would fall by between 8 percent in Idaho and West Virginia and 51 percent in Hawaii.

Previous research on job devaluation typically evaluates the potential wage declines associated with a significant inflow of women into an occupation, while results have been mixed. Few studies, however, examine the cultural mechanism central to the thesis, where an occupation’s prestige changes in response to the dynamics of its cultural association with women. This paper proposes a new semantic approach to trace the devaluation process in American culture, where occupation titles appear in scholarly and public discourses with varied semantic proximity to gender- and prestige-signaling phrases over time. Decade-specific occupation embedding (1900- 2019) from 127 billion words of American English across genres and a novel decom- position of fixed-effects estimation show a latent cultural bias against women’s work, such that an occupation’s prestige declines when it becomes increasingly stereotyped as a female job. Penalties appear throughout the period, with the largest effects found in lower-income occupations; most high-income occupations, despite experiencing large increases in female share in recent years, are persistently stereotyped as male professions without a significant prestige loss. In total, the cultural mechanism of devaluation accounts for 18.2–21.1% of the observed negative link between the changes of an occupation’s actual female share and prestige.

Introduction. Many children in low-income and middle-income countries fail to receive any routine vaccinations. There is little evidence on how to effectively and efficiently identify and target such ‘zero-dose’ (ZD) children. Methods. We examined how well predictive algorithms can characterise a child’s risk of being ZD based on predictor variables that are available in routine administrative data. We applied supervised learning algorithms with three increasingly rich sets of predictors and multiple years of data from India, Mali and Nigeria. We assessed performance based on specificity, sensitivity and the F1 Score and investigated feature importance. We also examined how performance decays when the model is trained on older data. For data from India in 2015, we further compared the inclusion and exclusion errors of the algorithmic approach with a simple geographical targeting approach based on district full-immunisation coverage. Results. Cost-sensitive Ridge classification correctly classifies most ZD children as being at high risk in most country-years (high specificity). Performance did not meaningfully increase when predictors were added beyond an initial sparse set of seven variables. Region and measures of contact with the health system (antenatal care and birth in a facility) had the highest feature importance. Model performance decreased in the time between the data on which the model was trained and the data to which it was applied (test data). The exclusion error of the algorithmic approach was about 9.1% lower than the exclusion error of the geographical approach. Furthermore, the algorithmic approach was able to detect ZD children across 176 more areas as compared with the geographical rule, for the same number of children targeted. Interpretation. Predictive algorithms applied to existing data can effectively identify ZD children and could be deployed at low cost to target interventions to reduce ZD prevalence and inequities in vaccination coverage.

Objectives: The prevalence of long working hours has been accompanied by a corresponding rise in sleep disorders. Sedative-hypnotic agents (SHAs), have been reported as the second most commonly misused drug class in the U.S. The key objective of this study was to examine the relationship between working hours on the use of sleep aids and medications with sedative properties. Methods: The 2010-2019 Medical Expenditure Panel Survey data was utilized. SHAs and medications with sedative related properties (MSRPs) were identified. Furthermore, we employed different regression models ranging from multivariable linear regression, Tobit regression, Heckman regression, and multivariable logistic regression, to ensure consistency, robustness, and reliability of associations. Results: Overall, a sample of 81,518 observations of full-time workers was analyzed. Working 56hours or more per week was significantly associated (p < 0.05) with an increased odds of using SHAs and MSRPs by 13% (Adjusted Odds Ratio, aOR =1.13, 95% Confidence Interval, CI=1.01:1.26) and 9% (aOR=1.09, 95% CI=1.03:1.16), respectively more than that among those who worked fewer hours. Females in our study had a higher likelihood (aOR=1.11, 95% CI=1.05:1.19) of using SHAs when compared to males. Also, professional services had the highest likelihood (aOR=1.31, 95% CI=1.14:1.50) of using SHAs. Conclusion: We found that long working hours were significantly associated with an elevated use of SHAs and MSRPs among U.S. workers. Specifically, female workers and individuals working in professional services had the highest likelihood of using sleep medications.

In this technical report, we introduce the CenSoc WWII Army Enlistment Dataset. This harmonized file was constructed from the most informative parts of World War II era army enlistment records that were digitized and published by the National Archives and Records Administration and the U.S. Census Bureau. The CenSoc WWII Army Enlistment Dataset contains information on 24 variables for over 9 million records of enlistees circa 1938-1947. This report details the composition of these records, and describes steps taken to clean the raw data file to produce this harmonized data set. We also describe datasets constructed by linking the CenSoc WWII Army Enlistment Dataset to U.S. mortality records and census records.

This dissertation includes three papers that examine part-time work and work hour preferences. The involuntary part-time employment rate is defined as the share of employed workers who work part-time but would prefer to work full-time. The first paper investigates the determinants of the involuntary part-time employment rate by accounting for both labor supply and labor demand, while the second paper compares the patterns and determinants of involuntary part-time employment during the Great Recession and the COVID-19 recession. The third paper shifts attention to a particular industry with a high prevalence of part-time workers, the food retail sector, and examines workers’ experience during the early stages of the COVID-19 pandemic. Paper 1, titled “The Labor Demand Side of Involuntary Part-time Employment,” investigates the determinants of the involuntary part-time employment rate (i.e., the proportion of involuntary part- time workers in all employment) by accounting for both labor supply (unemployment) and labor demand (job vacancies). We use big data on the near universe of online job vacancies collected by Burning Glass Technologies and the Current Population Survey from 2003 to 2021. We find that, within a commuting zone by 6-digit SOC occupation cell, a 10% increase in the unemployment rate increases the involuntary part-time rate by 0.19 percentage points, while a 10% increase in job vacancies decreases the involuntary part-time rate by 0.07 percentage points. We also provide suggestive evidence that higher labor market concentration, which is indicative of greater employer power in the labor market, may raise involuntary part-time employment. Overall, we conclude that higher labor supply and lower labor demand increase involuntary part-time employment. How did the COVID-19 recession affect part-time workers who wanted full-time jobs? The second paper, titled "Involuntary Part-time Employment in Two Recent Economic Downturns: Lessons from the Great Recession and the COVID-19 Recession," compares the impact of the Great Re- cession and the COVID-19 recession on involuntary part-time employment. Using data from the Current Population Survey from January 1994 to December 2022, we examine the patterns and determinants of involuntary part-time work. Based on the experience of the Great Recession, one would have expected a large increase in involuntary part-time work during the COVID-19 Recession, when unemployment surged to more than 15%. Relative to these expectations, the growth of invol- untary part-time employment in 2020 was subdued. This can be explained by unique factors, such as workers transitioning to unemployment due to business closures and changes in consumer behavior. Contact-based industries, like leisure and hospitality, experienced higher unemployment rates and lower shares of involuntary part-time workers. In the most adversely affected industries, employers were not able to adjust with hours reduction – which would have increased involuntary part-time work – but instead resorted to laying off workers. The labor market recovery in 2020 was remark- ably swifter than the recovery after 2009, with substantial decreases in both involuntary part-time employment and unemployment within a few months. This paper highlights how the COVID-19 recession reshape the labor market through unemployment rather than underemployment, and how favorable conditions facilitate a surprisingly rapid recovery. Lastly, paper 3, entitled “Work Attendance Anxiety, Precarious Work Schedules, and Job Satisfac- tion of Essential Retail Workers during early COVID-19”, turns attention to food retail part-time workers. Building upon the Job Demands-Resources model (JD-R), the study examines the rela- tionships among precarious work schedules, work attendance anxiety: anxiety over going to work, and employer supports during the early pandemic among essential retail workers who were required to continue working on-site. Data were collected through an online survey on the Amazon Me- chanical Turk platform. Between July and August 2020, we secured a sample of U.S. part-time workers in “food and beverage retail stores” (N=179). Using Ordinary Least Squares (OLS) regres- sion analyses, the findings indicate that attendance anxiety, lack of control over work hours, and non-standard working hours are negatively associated with job satisfaction. In terms of employer support, personal protective equipment reduces the level of attendance anxiety and alleviates the impact of attendance anxiety on job satisfaction. The findings from this study provide insights for employers and managers to improve the job satisfaction of essential workers in the food retail sector.

"Because immigration is such a recurring-and divisive-topic in the United States, it is easy to assume that we understand what it means for an immigrant to live under the specter of surveillance and punishment. It is easy to assume, as many scholars and journalists do, that undocumented immigrants live on the run from the authorities, constantly fleeing to the margins of daily life, staying in the shadows beneath the eyes of the law. And yet, while it is certainly true that immigrants are constantly faced with mechanisms of surveillance that function as tools of societal exclusion, this only tells part of the story. As Asad L. Asad shows, many people with a sanctionable status cannot-and, in some cases, do not want to-evade surveilling institutions or the formal records they generate: evading the institutions that keep formal records is a luxury that most immigrants (especially those with children) cannot afford. In Engage and Evade, Asad uses a wealth of interviews and ethnographic observations collected in Dallas County, Texas, bolstered and contextualized by original analyses of national survey data, to explore whether, how, and why immigrants engage with surveilling institutions. Presenting the stories of immigrants living in mixed-status families in which at least two members of the household have different legal statuses, and focusing especially on the experiences of immigrant parents, Asad argues that engagement with such institutions stems as much from hope for societal inclusion as it does from fear of exclusion. By paying attention to the ways in which immigrants make sense of, pursue, and use the records that result from these engagements, Asad reveals a variety of ways these individuals reinforce or resist their sanctionable status through the state's own surveillance"-- "How everyday forms of surveillance threaten undocumented immigrants-but also offer them the hope of societal inclusionSome eleven million undocumented immigrants reside in the United States, carving out lives amid a growing web of surveillance that threatens their and their families' societal presence. Engage and Evade examines how undocumented immigrants navigate complex dynamics of surveillance and punishment, providing an extraordinary portrait of fear and hope on the margins.Asad L. Asad brings together a wealth of research, from intimate interviews and detailed surveys with Latino immigrants and their families to up-close observations of immigration officials, to offer rare perspective on the surveillance that undocumented immigrants encounter daily. He describes how and why these immigrants engage with various institutions-for example, by registering with the IRS or enrolling their kids in public health insurance programs-that the government can use to monitor them. This institutional surveillance feels both necessary and coercive, with undocumented immigrants worrying that evasion will give the government cause to deport them. Even so, they hope their record of engagement will one day help them prove to immigration officials that they deserve societal membership. Asad uncovers how these efforts do not always meet immigration officials' high expectations, and how surveillance is as much about the threat of exclusion as the promise of inclusion.Calling attention to the fraught lives of undocumented immigrants and their families, this superbly written and compassionately argued book proposes wide-ranging, actionable reforms to achieve societal inclusion for all"