How to Construct a Mixed Methods Research Design

This article provides researchers with knowledge of how to design a high quality mixed methods research study. To design a mixed study, researchers must understand and carefully consider each of the dimensions of mixed methods design, and always keep an eye on the issue of validity. We explain the seven major design dimensions: purpose, theoretical drive, timing (simultaneity and dependency), point of integration, typological versus interactive design approaches, planned versus emergent design, and design complexity. There also are multiple secondary dimensions that need to be considered during the design process. We explain ten secondary dimensions of design to be considered for each research study. We also provide two case studies showing how the mixed designs were constructed.     

The Sociology of Inequality and the Rise of Neo-Inequality

Sociologists’ conventional approaches to understanding inequality and poverty do not adequately capture the causes, extent, and consequences of new forms of inequality that have emerged in the late 20th and early 21st centuries. Following a critique of conventional sociological theorizing on inequality and stratification, a synthesis of new sociological/social psychology thinking on inequality, and the use of case study data from Detroit, I explore, describe, and explain how neo-liberal ideology, neo-liberal systems of governance, and neo-liberal policies have created the neo-inequalities that now define our age.     

Familial Patterning and Prevalence of Male Androphilia in Samoa

Previous research established that male androphilia (i.e., sexual arousal and attraction to adult males) clusters in families. Some studies find that male androphilia clusters in both the paternal and maternal lines, while others find that it clusters only in the latter. Most of the research investigating the familial nature of male androphilia has taken place in Western cultural contexts that are problematic for such research because they are characterized by low fertility. To address this, our previous work has examined familial patterning of male androphilia in Samoa, a high-fertility population in which androphilic males are readily identified due to their public status as fa’afafine (a third gender category). Building on this work, the present study replicated the familial nature of male androphilia in Samoa using a sample size that was ~122% larger than the one we previously employed (N = 382, M ±SD age: 29.72 years ±10.16). Samoan fa’afafine had significantly more fa’afafine relatives in their maternal and paternal lines compared to Samoan gynephilic males (p < .001). The prevalence of male androphilia was equivalent across both the paternal and maternal lines (all p > .15). The revised prevalence estimate of male androphilia in Samoa falls between 0.61% and 3.51%.     

Long-Term Earnings Differentials Between African American and White Men by Educational Level

This paper investigates long-term earnings differentials between African American and white men using data that match respondents in the Survey of Income and Program Participation to 30 years of their longitudinal earnings as recorded by the Social Security Administration. Given changing labor market conditions over three decades, we focus on how racial differentials vary by educational level because the latter has important and persistent effects on labor market outcomes over the course of an entire work career. The results show that the long-term earnings of African American men are more disadvantaged at lower levels of educational attainment. Controlling for demographic characteristics, work disability, and various indicators of educational achievement does not explain the lower long-term earnings of less-educated black men in comparison to less-educated white men. The interaction arises because black men without a high school degree have a larger number of years of zero earnings during their work careers. Other results show that this racial interaction by educational level is not apparent in cross-sectional data which do not provide information on the accumulation of zero earnings over the course of 30 years. We interpret these findings as indicating that compared to either less-educated white men or highly educated black men, the long-term earnings of less-educated African American men are likely to be more negatively affected by the consequences of residential and economic segregation, unemployment, being out of the labor force, activities in the informal economy, incarceration, and poorer health.     

Estimating Recent Local Impacts of Sea-Level Rise on Current Real-Estate Losses: A Housing Market Case Study in Miami-Dade,Florida

Sea-Level Rise (SLR) Projections from the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Army Corp of Engineers (USACE) indicate increasing, and imminent, risk to coastal communities from tidal flooding and hurricane storm surge. Building on recent research related to the potential demographic impacts of such changes (Hauer et al. 2016, in Nat Clim Chang 3:802–806, 2017; Neumann et al. 2015; Curtis and Schneider in Popul Environ 33:28–54, 2011), localized flooding projections in the Miami Beach area (Wdowinski et al. in Ocean Coast Manag 126:1–8, 2016) and projected economic losses associated with this rise in projected SLR (Fu et al. Ocean Coast Manag 133:11–17, 2016); this research investigates the accrued current cost, in terms of real-estate dollars lost, due to recurrent tidal flooding and projected increases of flooding in Miami-Dade County. Most directly related to this line of research, Keenan et al. (2018) have recently produced results indicating that Climate Gentrification is taking place in Miami, FL with higher elevations in flood prone areas appreciating at a higher rate. In that vein of thinking, we seek to answer a question posed by such research: What is the actual accrued loss to sea-level rise over the recent past? To answer this question, we replicate well-documented estimation methods by combining publicly available sea-level rise projections, tide gauge trends, and property lot elevation data to identify areas regularly at risk of flooding. Combining recent patterns of flooding inundation with future forecasts, we find that properties projected to be inundated with tidal flooding in 2032 have lost $3.08 each year on each square foot of living area, and properties near roads that will be inundated with tidal flooding in 2032 have lost $3.71 each year on each square foot of living area. These effects total over $465 million in lost real-estate market value between 2005 and 2016 in the Miami-Dade area.