Copious academic scholarship has considered legalising assisted dying (AD). However, notwithstanding its obvious importance, safety has been relatively excluded from the AD debate. The debate has now reached an impasse and can arguably be distilled to one bone of contention: "slippery slope" fears. Opponents argue proposed safeguards will be unable to prevent the development of slippery slopes, in which vulnerable populations (namely the mentally ill, dying, and disabled) will be implicitly or explicitly pressured into receiving assistance in dying. Whilst safeguards are a valid field of inquiry, they represent just one facet of safety. Safety is conceived broadly as the prevention of harm, interdependent on timeliness, quality, effectiveness, and access. Whereas safeguards are predominantly concerned with employing preventative, defensive measures to avoid the emergence of harm, patient safety also depends on the improvement of latent conditions and active failures according to Reason's Swiss Cheese Model of safety, which this thesis subscribes to. A myopic focus on safeguards has facilitated the premature and unduly defeatist conclusion that AD and patient safety are mutually exclusive. This thesis seeks to rebut opposition by identifying potential risks to patient safety throughout the AD process and advancing proposals to protect safety under four themes: communication, symptom management, data monitoring, and safety cultures. This dissertation explicitly endorses an overarching focus on patient recovery, achieved via a multidisciplinary approach to symptom management prior to AD authorization. Thoroughly investigating patient motivations behind AD requests is more conducive to patient safety than perfunctory 'safeguards' which restrict eligibility to terminally ill patients with a six-month life expectancy or exclude disabled or mentally ill individuals. Thus, to ensure that AD remains an absolute last resort, several proposals are advanced, including a specific AD statute, a specialist national monitoring committee with regional subdivisions, and ongoing medical AD education.

Race is fraught with meaning, but unequal status is central. Race-status associations (RSAs) link White Americans with high status and Black Americans with low status. RSAs could occur via observation of racially distributed jobs, perceived status-related stereotypic attributes, or simple ranking. Nine samples (N = 3,933) validate three novel measures of White=high status/Black=low status RSAs—based on jobs, rank, and attributes. First, RSA measures showed clear factor structure, internal validity, and test-retest reliability. Second, these measures differentially corresponded to White Americans’ hierarchy-maintaining attitudes, beliefs, and preferences. Potentially based on observation, the more spontaneous Job-based RSAs predicted interracial bias, social dominance orientation, meritocracy beliefs, and hierarchy-maintaining hiring or policy preferences. Preference effects held after controlling for bias and support for the status quo. In contrast, the more deliberate Rank- and Attribute-based RSAs negatively predicted hierarchy-maintaining beliefs and policy preferences; direct inferences of racial inequality linked to preferences for undoing it. Third, Black=low status, rather than White=high status, associations largely drove these effects. Finally, Black Americans also held RSAs; Rank- or Attribute-based RSAs predicted increased perceived discrimination, reduced social dominance, and reduced meritocracy beliefs. Although individuals’ RSAs vary, only White Americans’ Jobbased stratifying associations help maintain racial status hierarchies. Theory-guided evidence of race-status associations introduces powerful new assessment tools.

This report describes the data and materials used to produce the Superdiversity in Metropolitan New York visualization website (www.superdiv-newyork.mmg.mpg.de), launched in 2020. This includes the data sources, design principles and methods, as well as the properties and categories of the variables used in the visualizations presented on the website.

Due to advances in unconventional extraction techniques, the rate of fossil fuel production in the United States (US) is higher than ever before. The disposal of waste gas via intentional combustion (flaring) from unconventional oil and gas (UOG) development has also been on the rise, and may expose nearby residents to toxic air pollutants, light pollution and noise. However, little data exists on the extent of flaring in the US or the number of people living near UOG flaring activity. Utilizing nightly sattelite observations of flaring from the Visible Infrared Imaging Radiometer Suite Nightfire product, 2010 Census data and a dataset of remotely sensed building footprints, we applied a dasymetric mapping approach to estimate the number of nightly flare events across all oil shale plays in the contiguous US between March 2012 and February 2020 and characterize the populations residing within 3 km, 5 km and 10 km of UOG flares in terms of age, race and ethnicity. We found that three basins accounted for over 83% of all UOG flaring activity in the contiguous US over the 8 year study period. We estimated that over half a million people in these basins reside within 5 km of a flare, and 39% of them lived near more than 100 nightly flares. Black, indigenous, and people of color were disproportionately exposed to flaring.

This thesis studies the impact of the early adoption of electricity by some manufacturing industries at the beginning of the 20th century on labor market transitions. Using the same empirical strategy as Fiszbein et al. (2020) and data from the matched US Population Census, I examine the effect of electricity on entry and exit into industries and occupations. Results suggest that new technologies do not affect the probability that existing manufacturing workers changed occupation or industry. There is a positive effect on the probability of staying in the same county and manufacturing sector. Furthermore, the evidence found on the impact of electricity on workers’ transition to lower-skill occupations is limited. I discuss possible explanations for these results, and sample endogeneity cannot be ruled out. Therefore, the findings should be interpreted in their context.

The environment plays a key role in the spread and persistence of antimicrobial resistance (AMR). Antimicrobials and antimicrobial resistance genes (ARG) are released into the environment from sources such as wastewater treatment plants, and animal farms. This study describes an approach guided by spatial mapping to quantify and predict antimicrobials and ARG in Minnesota’s waterbodies in water and sediment at two spatial scales: macro, throughout the state, and micro, in specific waterbodies. At the macroscale, the highest concentrations across all antimicrobial classes were found near populated areas. Kernel interpolation provided an approximation of antimicrobial concentrations and ARG abundance at unsampled locations. However, there was high uncertainty in these predictions, due in part to low study power and large distances between sites. At the microscale, wastewater treatment plants had an effect on ARG abundance (sul1 and sul2 in water; blaSHV, intl1, mexB, and sul2 in sediment), but not on antimicrobial concentrations. Results from sediment reflected a long-term history, while water reflected a more transient record of antimicrobials and ARG. This study highlights the value of using spatial analyses, different spatial scales, and sampling matrices, to design an environmental monitoring approach to advance our understanding of AMR persistence and dissemination.

In migration studies, immigrant health is a concern before, during, and after migration. This study uses a large late 19th and early 20th century data set of over 20 US prisons to assess migrant net nutrition. Native-born individuals were taller and had the lowest BMIs. International immigrants had lower BMIs and shorter statures. After controlling for other characteristics, native-born females had lower BMIs than men; however, foreign-born women’s’ BMIs were higher than domestic-born women. Females and males with darker complexions had greater BMIs than their counterparts with fairer complexions.

Affordable housing programs as place-based programs in the United States have an impact on the neighborhoods, but little is known about the impact of affordable housing construction on individuals living in the neighborhoods hosting these projects. This paper investigates the effects of affordable housing construction under the Low-Income Housing Tax Credit (LIHTC) program on individuals' labor market outcomes and welfare dependence. We exploit the timing of changes in the LIHTC program leading to spatial changes in the affordable housing supply to compare labor market outcomes of individuals exposed to varying levels of housing construction. We overcome the empirical challenges posed by the selective sorting of individuals into neighborhoods by matching the timing of the change in housing supply to an individuals' neighborhood of residence. We find an average improvement in the labor market outcomes of individuals as a result of higher exposure to the supply of affordable housing in their neighborhood. In addition, we document significant heterogeneities by race and ethnicity and find evidence that these heterogeneities are likely explained by the program-induced and migration-induced changes in neighborhood quality.

Objective: This paper asks: do black immigrants have higher rates of white partnership than African Americans?. Background: Some say white Americans feel more comfortable among black immigrants than among African Americans. Anglo-Caribbean accents, in particular, have been described as appealing. Research finds that some black immigrant groups do have higher rates of union with whites, but that advantage disappears when confounding factors are controlled. Yet, marriage markets have different characteristics. Using metropolitan areas as proxies for marriage markets, this study explores whether taking metropolitan conditions into account improves the odds that black immigrants and whites marry or cohabit. Method: The analysis pools data from the 2008–2016 American Community Surveys. Black immigrants are divided into Anglophone Afro-Caribbeans, Haitians, sub-Saharan Africans, and a residual group of “Other Blacks.” Two generations are created: those arriving before the age of 13 and those arriving later. The critical technique is multi-level logistic regression. Results: The findings replicate previous multivariate analyses in showing that black immigrants do not have higher rates of white partnership than African Americans. Still, rates are higher for the 1.5 than the 1.0 generation and higher among males than females. Among black ethnic groups, unions with whites are least common among Haitians and most common among sub-Saharan Africans. Conclusion: The findings weaken the hope that the black immigrant presence will moderate the “color line” in America.

The literature offers limited insights into the labor market experiences of women and men of different racial/ethnic groups by social class beyond considering their educational achievements or occupational status, common proxies for social class, or their positions on the wage distribution. This paper follows a different approach by thinking of class as life conditions at the family level, which we approximate with family income, and by exploring wages at the intersection of gender, race/ethnicity, and family class. Dealing with "individuals in families," this paper delves deeper into the stratification of women and racial minorities. Our analysis suggests that the "mark of gender" extends beyond race and class. No matter the social class to which individuals belong, women of any race/ethnicity receive conditional wages below the average wage of workers in the corresponding class. Our investigation also suggests that the racial wage penalty of Black women (vis-à-vis White women) stems from a stratification by class that penalizes them. When compared with individuals of the same class, Black women do not earn less than White women with similar characteristics do. On the contrary, the wage disadvantage of Black men (vis-à-vis White men) goes beyond class. No matter the class to which they belong, Black men have lower wages than comparable White men do because they tend to concentrate in occupations that pay less.

Using time-diary data from the U.S. and six wealthy European countries, I demonstrate that non-partnered mothers spend slightly less time performing childcare, but much less time in other household activities than partnered mothers. Unpartnered mothers' total work time-paid work and household production-is slightly less than partnered women's. In the U.S. but not elsewhere they watch more television and engage in fewer other leisure activities. These differences are independent of any differences in age, race/ethnicity, ages and numbers of children, and household incomes. Non-partnered mothers feel slightly more pressured for time and much less satisfied with their lives. Analyses using the NLSY79 show that mothers whose partners left the home in the past two years became more depressed than those whose marriages remained intact. Coupled with evidence that husbands spend substantial time in childcare and with their children, the results suggest that children of non-partnered mothers receive much less parental care-perhaps 40 percent less-than other children; and most of what they receive is from mothers who are less satisfied with their lives.

Economic inequality has been rising in many sub-Saharan African countries alongside rapid changes to union and family formation. In high-income countries marked by rising inequality, union and family formation practices have diverged across socioeconomic statuses, with intergenerational social and health consequences for the disadvantaged. In this study, we address whether there is also evidence of demographic divergence in low-income settings. Specifically, we model the age at first marriage and first birth by socioeconomic status groups for women born between 1960 and 1989 using Demographic and Health Survey data from 12 sub-Saharan African countries where economic inequality levels are relatively high or rising. We argue that economic and sociocultural factors may both serve to increasingly delay marriage and childbearing for the elite as compared to others in the context of rising inequality. We find emerging social stratification in marriage and childbearing, and demonstrate that this demographic divergence is driven by the elites who are increasingly marrying and having children at later ages, with near stagnation in the age at first marriage and birth among the remaining majority. We urge further research at the intersection of socioeconomic and demographic inequality to inform necessary policy levers and curtail negative social and health consequences.

The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is an important source of nutritional support and education for women and children living in poverty; although WIC participation confers clear health benefits, only 50% of eligible women and children currently receive WIC. In 2010, Congress mandated that states transition WIC benefits by 2020 from paper vouchers to electronic benefits transfer (EBT) cards, which are more convenient to use, are potentially less stigmatizing, and may improve WIC participation.

We present an approach for indexing encrypted data stored at external providers to enable provider-side evaluation of queries. Our approach supports the evaluation of point and range conditions on multiple attributes. Protection against inferences from indexes is guaranteed by clustering tuples in boxes that are then mapped to the same index values, so to ensure collisions for individual attributes as well as their combinations. Our spatialbased algorithm partitions tuples to produce such a clustering in a way to ensure efficient query execution. Query translation and processing require the client to store a compact map. The experiments, evaluating query performance and client-storage requirements, confirm the efficiency enjoyed by our solution.

While the environmental justice literature establishes that enviromental burdens are often concentrated among poor communities of color, little scholarship assesses the distribution of positive sustainability policies and how those policies, inturn, reshape those communities. Only recently have scholars started examining how green policies are distributed within a city (Reames, 2016; Rigolon et al., 2018) and how those policies might gentrify a community (Lubitown, 2016; Stehlin, 2015).

Children increase time demands with important consequences for sleep. Here, we test whether parents’ paid and unpaid time demands and the presence of young children equally reduce mothers’ and fathers’ sleep, comparing the married/cohabiting to unmarried. Applying data from the American Time Use Survey (ATUS, 2003–2016), we find married/cohabiting mothers report less sleep when young children or multiple children are present; they are employed; their spouses are employed; and they spend more time in housework and childcare. By contrast, unmarried mothers report less sleep when children are present because of their larger domestic loads. For married/cohabiting fathers, the presence of multiple children is associated with less sleep but doing more housework results in more sleep. Finally, unmarried fathers’ employment time explains the association of children on their sleep. Parents report a sleep deficit relative to the childless but the reasons vary by gender and the co-presence of a partner.

This paper develops a framework for assessing the welfare effects of labor income tax changes on married couples. I build a static model of couples' labor supply that features both intensive and extensive margins and derive a tractable expression that delivers a transparent understanding of how labor supply responses, policy parameters, and income distribution affect the reform-induced welfare gains. Using this formula, I conduct a comparative welfare analysis of four tax reforms implemented in the United States over the last four decades, namely the Tax Reform Act of 1986, the Omnibus Budget Reconciliation Act of 1993, the Economic Growth and Tax Relief Reconciliation Act of 2001, and the Tax Cuts and Jobs Act of 2017. I find that these reforms created welfare gains ranging from -0.16 to 0.62 percent of aggregate labor income. A sizable part of the gains is generated by the labor force participation responses of women. Despite three reforms resulted in aggregate welfare gains, I show that each reform created both winners and losers. Furthermore, I uncover two patterns in the relationship between welfare gains and couples' labor income. In particular, the reforms of 1986 and 2017 display a monotonically increasing relationship, while the other two reforms demonstrate a U-shaped pattern. Finally, I characterize the bias in welfare gains resulting from the assumption about a linear tax function. I consider a reform that changes tax progressivity and show that the linearization bias is given by the ratio between the tax progressivity parameter and the inverse elasticity of taxable income. Quantitatively, it means that linearization overestimates the welfare effects of the U.S. tax reforms by 3.6-18.1%.

Nurse practitioners (NPs) are able to complete training and enter the workforce faster than physicians, and they have labor cost advantages. Since they are able to provide many of the same primary care services as physicians, utilizing them as independent providers may help improve access to healthcare and contain costs. Prior evidence has shown NPs achieve patient satisfaction and health outcomes that are on par with or better than those of physicians. There is also some evidence to indicate that NP practice patterns result in similar or lower patient medical expenditures when compared to physician care. However, this evidence is limited, with little study at the national level. In an effort to contribute evidence, I use data from the 2015 and 2016 Medical Expenditure Panel Survey (MEPS) to examine whether a greater ratio of patient NP visits to total NP and physician visits is associated with a lower level of expenditures. Because of unobserved confounders, particularly those associated with the generally healthier case mixes of NPs, I estimate both an OLS and a 2SLS model. The 2SLS model uses as an instrument the percentage of providers at the respondent’s usual source of care who are NPs or PAs. Patients’ capacity for choice at the facility level is expected to be less than that at the provider level within facilities, thereby reducing the magnitude of selection bias. I find from the OLS model that an increase of one point in the percentage of visits to NPs is associated with a statistically significant decrease in expenditures of .24%. The corresponding 2SLS estimate is a decrease of 1.13%, but based on the commonly used cutoff of an F-statistic of 10, the instrument appears to be weak. I cannot rule out the possibility that these estimates are negative only because of selection bias. An extension of this analysis involving applying for access to restricted geographic information would enable merging MEPS data with county-level NP and physician counts from the Area Health Resource Files. County provider distribution may be a less endogenous instrument, alleviating concerns over selection bias.

Recent studies document a decline in U.S. labor-market fluidity from as early as the 1970s on. Making use of the Annual Social and Economic supplement to the Current Population Survey, I uncover a pronounced increase in job-to-job mobility from the 1970s to the 1990s, i.e. the annual share of continuously employed job-to-job movers rises from 5.9% of the labor force in 1975–1979 to 8.8% in 1995–1999. Job-to-job mobility exhibits a downward trend only since the turn of the millennium. In order to provide a formal economic interpretation, I additionally estimate the parameters of the random on-the-job search model. Furthermore, I document that job-to-job mobility has an unconditional correlation of −0.86 with the unemployment rate at business-cycle frequencies in 1975–2017, varying by around 3 percentage points over the business cycle.

Science, Technology, Engineering and Mathematics (STEM) jobs have grown in importance in the labor market in recent decades, and they are widely seen as the jobs of the future. Using data from the U.S. Census and American Community Survey, we first investigate the role of employment in STEM occupations when it comes to recent changes in the occupational employment distribution in the U.S. labor market. Next, with data from the High School and Beyond sophomore cohort (Class of 1982) recent midlife follow-up, we investigate the importance of high school students’ mathematics and science coursework, knowledge, and skills for midlife occupations. The Class of 1982 completed high school prior to technological changes altering the demand for labor. We find that individuals who took more advanced levels of high school mathematics coursework enjoyed occupations with a higher percentile rank in the average wage distribution and were more likely to hold STEM-related occupations. Findings suggest that the mathematics coursework enabled workers to adapt and navigate changing labor market demands.