The study of historical populations has long supported innovative demographic research, beginning with the work of Graunt in the seventeenth century, increasing rapidly in the 1950s, and continuing to the present. This chapter documents the methods and materials used by explorers of past populations, and the main findings of the field. The section on data and tools shows how researchers make use of information (such as parish registers) originally created for other purposes, in order to undertake demographic analyses, and describes the tools used. Historical demographic research has produced valuable results about family changes over decades and centuries, especially in the timing of marriage and number of children, and has documented unexpected continuities in family life. Researchers have also explored the increase in life expectancy and improvements in quality of life, with the most recent research using sophisticated methods to link life experiences, health, and family formation.

In the twenty-first century, a small percentage of U.S. children have ties to family-based agriculture. Yet with the rise of the modern farming movement that emphasizes local and family-based production, new spaces may exist for involving children and youth in farming. This article focuses on the social value of children to family-based agriculture in the contemporary era. Drawing on a qualitative study of families that farm in the capital region of New York—an epicenter for the modern food movement—we consider why families farm, how they involve children in their farms, and how they understand children’s contributions. Interviews with 76 adult members of 50 families show children to be central to families’ goals; they often rationalize farming as a lifestyle choice undertaken for the benefit of their children. Families also actively involve their own children—and other people’s children—in their farms. By documenting the way families talk about children and farming, we shed light on the logic used to incorporate children into modern productive enterprises. The centrality of children, we argue, helps explain the success of the modern food movement and the persistence of family-based agriculture despite conditions that make it economically difficult to accomplish.

California’s economic picture is unusually bright now. Unemployment is at multiyear lows and the state’s fiscal health is at historically high levels. But history tells us good times will not last forever. Sometime—and according to many forecasters, sometime soon—the nation and the state will go through a recession. This report considers what a recession would mean for certain key programs within California’s social safety net—a vital set of programs that aim to protect the health and wellbeing of the state’s most vulnerable residents. Even in the best of times, millions of Californians depend on these programs. When the economy turns down, the need for assistance rises, sometimes substantially. Past downturns have hit state finances hard, forcing painful spending cuts. How then will California be able to balance its budget, as the state constitution requires, while maintaining support for those who need it? It is helpful to look at the recent past in order to calibrate the difficulties that the state will likely face. California’s most recent downturn was the Great Recession of a decade ago, which came on the heels of the nation’s worst financial crisis since the Great Depression. During the Great Recession, the share of Californians who were poor grew from 12.2 percent to 16.6 percent, putting pressure on the state’s safety net. All told, the three large safety net programs registered $1.9 billion in cuts annually from 2008 to 2012, representing 15 percent of all cuts in state General Fund spending.

From its beginnings, United Statessociety has differentiated groups of people based upon similarities of the people in each group. Such categorization has enabled certain groups to enjoy privilege in American and othersto suffer. For racial groups, such as African Americans, suffering has accompanied their stigmatization in the form of a residential segregation that has systematically deprived them of a basic freedom ,“a deprivation especially onerous when its basis is the unalterable fact of race or ancestry” (McEntire, 1960). Over the course of American history residential segregation has been a central theme in the discussion of the role of housing as it affects quality of life for minorities. Fair housing researchers have applied most of their analytical efforts toward cities and urban settings known to have overt racial tensions, segregation, violence and criminal activity that is most usually associated with minority populations. Such cities include Chicago, New York, Philadelphia, Cleveland and Atlanta, major American urban hubs with large minority populations (Rothstein, 2017b). The Midwest at large, and particularly Iowa, has historically been overlooked in studies addressing social issues impacting minorities and, while that trend generally continuestoday,such research has begun to emerge in placeslike Minneapolis/St. Paul, Seattle, Portland and other locales nationally

This article examines the ability of immigrants to integrate and to become full Americans. Naturalization has long been recognized as a fundamental step in that process and one that contributes to the nation’s strength, cohesion, and well-being. To illustrate the continued salience of citizenship, the article compares selected characteristics of native-born citizens, naturalized citizens, legal noncitizens (most of them lawful permanent residents [LPRs]), and undocumented residents. It finds that the integration, success, and contributions of immigrants increase as they advance toward naturalization, and that naturalized citizens match or exceed the native-born by metrics such as a college education, self-employment, average personal income, and homeownership. It finds that: Naturalized citizens enjoy the same or higher levels of education, employment, work in skilled occupations, personal income, and percentage above the poverty level compared to the native-born population. At least 5.2 million current US citizens — 4.5 million children and 730,000 adults — who are living with at least one undocumented parent1 obtained US citizenship by birth; eliminating birthright citizenship would create a permanent underclass of US-born denizens in the future. Requiring medical insurance would negatively affect immigrants seeking admission and undocumented residents who ultimately qualify for a visa. About 51 percent of US undocumented residents older than age 18 lack health insurance. In 2017, about 1.2 million undocumented residents lived with 1.1 million eligible-to-naturalize relatives. If all the members of the latter group naturalized, they could petition for or expedite the adjustment or immigration (as LPRs) of their undocumented family members, including 890,000 “immediate relatives.” Their naturalization could put 11 percent of the US undocumented population on a path to permanent residency. The article also explores a contradiction: that the administration’s “America first” ideology obscures a set of policies that impede the naturalization process, devalue US citizenship, and prioritize denaturalization. The article documents many of the ways that the Trump administration has sought to revoke legal status, block access to permanent residence and naturalization, and deny the rights, entitlements, and benefits of citizenship to certain groups, particularly US citizen children with undocumented parents. It also offers estimates and profiles of the persons affected by these measures, and it rebuts myths that have buttressed the administration’s policies.

Reducing potential dangers by changing routine behavior to avoid certain people, places, or technologies can be prudent, but reporting avoidance also can be symbolic. This study probed Americans reactions to Ebola from December 2014 to May 2015 with a longitudinal study (final n = 625), plus a representative sample in May: How much did they claim to avoid West Africans, commercial flights, Ebola-associated cities, and four other targets? What factors affected self-reported avoidance? Did people with opportunities to implement avoidance report more (e.g., frequent flyers can change their routine behavior more to avoid commercial flights than can infrequent flyers)? The December 2014 survey found most people never considered avoidance, but substantial minorities claimed acting or intending to avoid each target; substantial majorities of May 2015 respondents reported avoidance intentions if a new Ebola outbreak occurred in Africa or the United States. Perceptions of personal risk, concern about infection, and following Ebola news were primary factors in reported avoidance, with temporal reversals (e.g., news following increased avoidance in December but decreased it in May). Opportunity enhanced reported avoidance in December 2014 by indirect effects through personal risk, concern, and news following, but decreased avoidance intentions in May 2015 through direct effects of opportunity on avoidance. Temporal shifts in avoidance reports and associations seem consistent with objective declines in Ebola cases, perhaps mediated by changes in news coverage. Further consideration of avoidance behavior and the role of opportunity could enhance hazard management.

This study uses path analysis models to evaluate the associations between zoning, development density and the sales prices of new and existing single-family homes at the dwelling-unit level in Portland, Oregon. Development density is associated with the sales prices of single-family homes directly by determining land costs and indirectly by correlating with the size and construction costs of structures. A prominent trend in Portland’s and the nation’s real estate markets is that new single-family homes are getting bigger. Another trend is that single-family homes have been built on smaller lots despite their growing floor areas. Because developers tend to build smaller homes on smaller lots, the decline of lot sizes helps to contain the effect of growing home size on housing prices. However, the counter effect of smaller lot sizes is somewhat weak because home sizes have a stronger association with housing prices than lot sizes. Homebuyers in Portland are willing to pay a premium to live in neighbourhoods with higher densities, which further limits the potential of higher density development as a tool to reduce single-family home costs. In addition to its indirect associations with home prices via the determination of lot and home sizes, zoning exhibits a significant and direct association with the prices of existing single-family homes, but not with the sales prices of new single-family homes. Existing single-family homes in higher density zones tend to sell at lower prices, ceteris paribus, suggesting that the concern of future neighbourhood change prevails over the opportunity for redevelopment.

Purpose To examine the association of muscle-strengthening activities (MSA) and cancer mortality. Methods We pooled data from the 1998 to 2009 National Health Interview Survey (NHIS), which were linked to records in the National Death Index. Mortality follow-up was through 31 December 2011. Based on U.S. federal guidelines for physical activity, we dichotomized MSA and compared those who performed MSA twice a week or more to others with lower MSA. We also examined dose–response relationship of MSA frequency with cancer mortality. Hazard ratios (HR) from Cox regression were computed to estimate the association of MSA with the risk of cancer mortality. Mean follow-up was 7.9 years and the analysis sample size was 310,282. Results Covariate-adjusted results showed that meeting the MSA guideline was associated with a 19% lower risk of cancer mortality (HR 0.81, 95% CI 0.73, 0.90). We found no evidence of a dose–response relationship between the frequency of performing MSA and cancer mortality. Conclusion Adhering to the U.S. federal guideline for MSA is associated with lower cancer mortality. Public health programs and policy for cancer prevention and control should promote MSA to further reduce cancer mortality.

The lack of spatial access to job opportunities is considered one major barrier that explains low employment rates and long commutes of racial/ethnic minorities, particularly in the U.S. But it is unclear whether the job accessibility effects vary by race/ethnicity. This research fills this gap. Results based on the Los Angeles region reveal complicated relationships: job accessibility has similarly insignificant effects on the employment probability of white and black job seekers, while the effects on Hispanics and Asians are plausible and significant in low- and medium-education groups. High job accessibility by transit mode reduces commute distance for all racial/ethnic groups, but job accessibility by automobile does not. Therefore, policies that aim to improve economic prospects or to reduce commutes and related externalities need to be both place-sensitive, e.g., improving transit services to employment clusters, and race/ethnicity-sensitive, e.g., considering transportation needs of low- and medium-education Hispanic and Asian workers.

This paper studies the impact of The Great Recession period and the time period prior on the Indiana labor force. Specifically, it aims to show the impact across a variety of demographic, categorical variables (e.g. sex, age, and race).

BACKGROUND Demographic Research: Volume 41, Article 8 Research Article The health of biracial children in two-parent families in the United States Kate H. Choi1 Nancy E. Reichman2 Over the past few decades, the United States has experienced a dramatic rise in the number of multiracial individuals. The health of this population is vastly understudied because most population-based health surveys do not adequately identify multiracial individuals. OBJECTIVE We compare the health of black/white biracial children with that of single-race white and black children and assess the extent to which differences in characteristics of parents who select into the distinct unions and children’s socioeconomic backgrounds explain the observed differences. METHODS Using information about the race of coresident mothers and fathers, we classify children into four racial groups – single-race whites (WW), biracial children with white mothers and black fathers (WB), biracial children with black mothers and white fathers (BW), and single-race blacks (BB). We estimate logistic regression models to document variations in rates of poor overall health and disability by children’s racial background. RESULTS WW children are less likely than BB children to have poor overall health, but more likely to be diagnosed with a disability. WB children are less likely than BB children, but more likely than WW children, to have poorer health. The disability rates of WB children are similar to those of BB children. Selection and socioeconomic differences explain some of the differences in poor overall health, but suppress differences in disability, between WB and WW children.

Twitter has increasingly been used to study various research topics such as election predictions, disease spread, etc. However, social media platforms do not saturate the entire population in a study area, especially in emerging nations, only representing more affluent subpopulations. The U.S. Army Engineer Research and Development Center, Construction Engineering Research Laboratory (ERDC-CERL), as part of a project entitled Framework for the Integration of Complex Urban Systems (FICUS), is quantifying the utility of demographic information to inform neighborhood-scale social media models. Using the example topic of infrastructure, an open-source model was constructed to collect Twitter data from the metropolitan Philippines area of Manila, geotag tweets to neighborhood grid cells based on language analysis, and produce a sentiment topic map. ERDC’s social media analysis tools incorporate quantifiable uncertainties with specific on-the-ground reporting techniques. By using the Humanitarian Crisis (HC) framework developed by PACOM (another FICUS product) as a model, a framework quantifying the likelihood of being a regular social media user was created to implement a data-driven, bottom-up framework construction nested within a knowledge-based established framework. This framework, and any other produced by the FICUS team serve as case studies for augmenting the military operational environment with quantifiable reduced uncertainties.

In the post-industrial world, data science and analytics have gained paramount importance regarding digital data privacy. Improper methods of establishing privacy for accessible datasets can compromise large amounts of user data even if the adversary has a small amount of preliminary knowledge of a user. Many researchers have been developing high-level privacy-preserving mechanisms that also retain the statistical integrity of the data to apply to machine learning. Recent developments of differential privacy, such as those in [11], [16], [17], [25], [34], and [35], drastically decrease the probability that an adversary can distinguish the elements in a data set and thus extract user information. In this paper, we develop three privacy-preserving mechanisms with the discrete M-band wavelet transform that embed noise into data. The first two methods (​ LS and ​ LS​ +​) add noise through a "Laplace-Sigmoid" distribution that multiplies Laplace-distributed values with the sigmoid function, and the third method utilizes pseudo-quantum steganography to embed noise into the data. We then show that our mechanisms successfully retain both differential privacy and learnability through statistical analysis in various machine learning environments. Highlights In this paper, we create three different input perturbation stochastic mechanisms that add or embed noise to sensitive datasets. Our mechanisms improve upon traditional noise addition methods, such as the Laplace mechanism and exponential mechanism mentioned in [11], by using the discrete M-band wavelet transform (DMWT) to convert the dataset into a wavelet domain before adding noise. For the first two mechanisms, we combine the Laplace distribution and the sigmoid function to create a complex stochastic function, and we optimize the mechanisms based on the size of the dataset. In the third mechanism, we propose the use of pseudo-quantum steganography to embed noise into a dataset. Due to the nature of the quantum signal, the noisy dataset has an extremely low probability of being correctly denoised by an adversary. While our proposed mechanisms preserve ε-differential privacy, they also maintain the statistical integrity of the datasets. Using five different supervised machine learning environments-logistic regression, support vector machine, support vector regression, classical artificial neural networks, and deep learning-the mechanisms achieve high accuracies in binary classification across multiple datasets. Moreover, our (pseudo-) quantum mechanism is one of the first to use higher computational power to add noise to private data. As data privacy becomes an extremely important issue in our world, and as quantum computing emerges as a major field, our research can link the two branches and shine a light on what data privacy could potentially look like in the future.

We study how import competition affects union membership in the United States, adapting identification strategies from recent work on imports from China. Within manufacturing , union workers are slightly more affected than non-union ones, inducing modest declines in unionization. At the same time, total manufacturing declines are greatest among Right-to-Work states. We provide evidence that firms in Right-to-Work states tend to specialize in lower-quality products, making them more susceptible to competition with Chinese goods. However, while reducing unionization within manufacturing, import competition causes a robust increase in unionization outside of manufacturing, more than offsetting within-manufacturing declines. This appears to be driven by family members of would-be manufacturing workers shifting to higher-wage jobs: for less-educated women, the highest paying opportunities are often in healthcare and education, which are disproportionately unionized. Altogether, we calculate that the decline in US union density would have been 36% larger without Chinese imports. Version 1.0. COMMENTS WELCOME.

Standard models of within-country mobility assume that all migration is speculative: workers move to search for jobs in other labour markets. I establish a new stylised fact showing that the majority of cross-regional migration in the US is in fact with a job in hand, as a result of a job offer from another region. The fact that a significant fraction of migration is a result of cross-regional hiring, and that this hiring is subject to search and matching frictions, has important implications for the level of regional mobility and hence regional differences within a country. In the first two chapters, I show empirically that the availability of cross-regional employment opportunities does matter for workers’ migration behaviour. Using US panel data, I demonstrate that the observed gap in migration propensity between the more and less educated workers can be partly explained by differences in labour market frictions. The less educated workers find job search in more distant regions much more difficult, which limits their options to move for a specific job and reduces their overall mobility. This result opens a new policy channel in addressing regional differences and those left behind: the importance of the ability to find a job before moving suggests a large social return to improving regional search and matching for less educated groups. In the third chapter, I explore the theoretical implications of an imperfect search and matching process on the existence and persistence of regional disparities. First, I show that if the efficiency of the search and matching process increases in the size of the labour market, migration will serve to exacerbate, not equilibrate, the differences in regional economies. A bigger labour market will experience higher wages and lower unemployment rates, attracting migrants from other regions and thus accelerating the process of regional divergence. At the same time, larger labour market frictions in the smaller regions reduce firms’ incentives to hire there, curtailing cross-regional hiring and hence the opportunity to move for a specific job. The interaction of these two forces give rise to multiple equilibria and explain how, in the presence of labour market frictions, regional disparities can be large and persistent at the same time.

Objective: Investigate whether hearing difficulty has an influence on the risk of mortality. Methods: A nationally representative sample of individuals 18 years or older with data available for hearing and mortality status was selected from the National Health Interview Surveys (NHIS) 2005-2009. Self-perceived hearing status was regrouped as excellent/good, a little to moderate trouble, a lot of trouble, and deaf. Other independent variables investigated were demographics and comorbidities. Univariate analysis was performed to calculate the incidence of mortality, and 95% confidence intervals (CI) and multivariate analysis adjusted for demographics and comorbidities was performed to calculate odds ratios (OR) of mortality. Those with excellent/good hearing were considered as reference for ORs. Results: Of 215.6 million Americans (mean age = 45.9 years; 51.7% female), approximately 16.0% (95% CI, 15.6%-16.3%) considered their hearing less than excellent or good. The 5-year mortality rate was 4.2% (95% CI, 4.0%-4.3%). In the univariate analysis, the mortality rate increased with the degree of hearing difficulty from 3.0% in excellent/good hearing to 19.5% in a lot of trouble hearing and 17.8% in deaf. With multivariate analysis, adjusted ORs of mortality were 1.5 (95% CI, 1.3-1.7) in those who had a lot of trouble hearing and 1.6 (95% CI, 1.1-2.3) in those who were deaf. Conclusion: Hearing difficulty may be associated with an increased risk of mortality, and this risk may correlate with the degree of hearing difficulty.

Today, many youth across the United States struggle to achieve their educational goals and secure a good job. Millions of youth and young adults fall behind academically or face unemployment between the ages of 16 and 24, a critical period for brain and identity development and for launching a career trajectory.1 The consequences are enduring for them and for our nation. It is time—long past time—for bold solutions. Youth are forced to navigate underfunded and unconnected secondary, postsecondary, and workforce systems, and they face too few realistic options to advance academically and professionally. Sixty-five percent of all U.S. jobs will likely require postsecondary education and training beyond high school as of 2020, but far fewer young people attain such a degree.2, 3, 4 Youth unemployment rates are double that of the prime-age U.S. population. An estimated 4.6 million youth ages 16 to 24 are disconnected or “Opportunity Youth”—neither in school nor working.5,6 Major disparities persist in young adults’ educational and employment opportunities, and many challenges faced by all youth are exacerbated for youth of color, immigrant youth, LGBTQ youth, and girls and young women, among others. The status quo is not working for America’s youth and young adults. It falls short for employers, who struggle to hire and retain the workers they need, and damages our economy, which will have to rely increasingly on today’s younger workers to support an aging population. Any serious national economic agenda must address this challenge in an ambitious and viable way . . .

Theoretical and empirical analyses typically ignore geographic variation in female employment and racial differences in female employment outcomes. We document that there is substantial heterogeneity in female employment with respect to geographic location, race, and their interaction. We show that a parsimonious set of area-level controls explains a substantial portion of that heterogeneity. Our results suggest that analyses that ignore geographic variation may misstate the determinants of female employment, possibly producing erroneous conclusions and policy prescriptions. They also suggest that understanding geographic heterogeneity is crucial to understanding racial differences in female employment as well as female employment itself.

Citizens’ tendency to overestimate the size of immigrant populations has been the subject of several studies over the past three decades. While we have learned a great deal about the extent, causes, and potential consequences of this population innumeracy, our understanding remains static. The current letter offers the first longitudinal consideration of immigrant population size misperceptions with an analysis across a nine-year span in the U.S. This study considers: 1) whether misperceptions have changed over time; 2) how these changes compare to the growth of the actual foreign-born population size; and 3) whether these changes are related to demographic and ideological factors. Results indicate that misperceptions have grown rapidly in the U.S, far outpacing the modest, actual increases across the period. Pooled cross-sectional analyses indicate that demographic factors do not explain the growth in misperceptions. However, the overestimates of politically conservative Americans have grown increasingly extreme over time.

This paper provides evidence that self-employment is a quantitatively important work alternative that American mothers use to gain workplace flexibility. First, I use panel data from the Survey of Income and Program Participation (SIPP) to show that self-employment rates are higher when women have young children at home in a pattern that has remained largely unchanged over the previous three decades. I estimate that women whose youngest child is two years old have 14% higher predicted self-employment rates due to the birth of that child. Second, I show that self-employed women appear to have more flexibility in their work location, hours, and schedule than wage and salary employed women using data from the American Time Use Survey. I find that mothers with young children use self-employment to spend an additional two hours per day with their children. My results suggest that mothers use self-employment to gain more control over their work environment allowing them to better manage their household responsibilities while working. These findings contribute to the ongoing discussion on the importance of family friendly work policies and the rise of alternative work arrangements.