My research focuses on how inspiration porn articles perpetuate the Medical Model of Disability, and specifically, on how those articles objectify and devalue people with Down syndrome. Inspiration porn refers to the representation of disability as a form of disadvantage that can be overcome; it often celebrates disabled people simply for living with a disability. This “overcoming” narrative stems from the Medical Model of Disability, which defines disability as an individual defect and personal tragedy. While many Americans have not heard the specific term “inspiration porn,” most have been exposed to inspiration porn articles. I conducted a qualitative content analysis to explore my research aim; this methodology allows for the investigation of the underlying, context-dependent meanings of a text. My unit of analysis was individual articles. I identified these articles through use of the search engine Access World News. These articles have been published in the USA between the dates of 1/1/16 and 12/31/16, and have the words “Down syndrome,” “Down’s syndrome,” “Downs’ Syndrome,” or “Downs Syndrome” in the headline. After I created my coding frame, I analyzed every 10th article, and then interpreted the findings to ascertain the prevalence of inspiration porn, and how inspiration porn perpetuates the Medical Model of Disability. I initially anticipated the results of my content analysis would indicate that inspiration porn articles, in perpetuating the Medical Model, reinforce limiting and unrealistic stereotypes of people with Down syndrome. This result would show how the growing popularity of inspiration porn is troubling. This new phenomenon does not promote inclusion and diversity – rather it encourages interactions between those with disabilities and those without, in a superficial, condescending manner. My research is important because it draws attention to disability as a sociological topic, and further expands upon media studies by examining the role of mainstream media in perpetuating stereotypes.

Over the past century, the United States has seen many large changes in immigration patterns. One important change has been the emergence of new immigrant destinations within the past thirty years. While many traditional destinations (e.g., New York, NY) continue to draw immigrant populations, new metropolitan areas (e.g., Atlanta, GA) are also drawing large numbers of immigrants. What is largely unknown about these new destinations is how they differ from traditional destinations in terms of the health outcomes of their immigrant populations compared to their local native-born counterparts. I hypothesize that immigrants in new destinations will have worse health outcomes compared to the surrounding native-born population than that of immigrants in traditional destinations. I conduct a logistic regression analysis using data from the 1997-2001 National Health Interview Survey (NHIS) in order to compare health outcomes between immigrants and native-born populations in six new destination cities (Atlanta, Dallas, Fort Worth, Orlando, Washington D.C., and West Palm Beach) and eight traditional gateway cities (Bergen-Passaic, Boston, Chicago, Jersey City, Middlesex-Somerset-Hunterdon, Nassau-Suffolk, New York, and San Francisco). Health is measured using two different models: (1) access to a primary care physician (based on the question “Is there a place that you usually go to when you are sick or need advice about your health?”) and (2) self-reported health (based on the question “Would you say your health in general is excellent, very good, good, fair, or poor?” with responses coded on a five point Likert scale, where 1 is “excellent” and 5 is “poor”). This research can be used to inform those interested in immigrant health on contexts that might increase immigrant health risks, such as patient-doctor communication issues and discrimination. Policymakers and public health officials can use this research to identify areas where intervention is needed.

Universal sport analytics was made possible with the emergence of different technology in the past two decades. With existing statistical software and data recording, the performance of players can be quantified by organizations that are seeking to obtain a more scientific analysis of player performance. Specifically, more statistics are made to eliminate biases and better summarize a player’s contribution to their team. Major League Baseball and its drafting rules place themselves above other professional sports for analytics because players do not have to sign up for the draft, draft picks and players cannot be traded during the draft, and the lengthiness of its draft. Although individual organizations make efforts to pick suitable selections in the draft, the performance of baseball players is more difficult to predict at the professional level when compared to other sports. Despite the publication of MoneyBall, a book by Michael Lewis about methods to make quantifiable player signings, other research on player selection is often sensitive and discoveries are rarely published due to organizations fearing they will give away their competitive edge in the process. For this specific research project, data was gathered through web-scraping Baseball-Reference, a widely used online database for baseball analytics. By using analytical statistics and accounting for other factors, statistical analysis was done on different categories of players. This research identified differences between the predictability of success for pitchers and position players, and observed the impact of age or level of education of the player that is drafted. This study demonstrates how the different characteristics of these players reflect on the predictability of their accumulated value throughout their career. Preliminary results show pitchers’ performance as more predictable, perhaps due to the physicality prowess of pitching. This research suggests further work to produce better indicators for prospective players at the Major League level.

Black men are disproportionately represented among the number of people killed through the use of police deadly force each year. With the development of technology and the pervasiveness of social media in every day life, people have the ability to watch and re-watch these deaths on a daily basis. This phenomenon has become particularly prevalent in recent years, sparked by the graphic videos of deadly force used on Eric Garner and Philando Castile. Although there is a significant body of literature on the impact of racism, discrimination, and violence on black male self-perception, group identity and political attitudes, little is understood about the impact of this new form of publicized fatal violence. For this research project, I explore how black men are being exposed to this specific type of fatal violence, and outcomes related specifically to changes in political response, attitudes, and group identity. This process included a series of three open-ended focus groups, each comprised of 7-8 black male undergraduate and graduate students at the University of Washington. From these focus groups I identified 4-5 individuals and conducted semi-structured in-depth interviews to build on themes established in the focus groups. The information from these focus groups and interviews provide a unique insight into changing forms of discrimination and violence black men face, and the implications this violence has for their own political actions and behaviors.

Himalayan adventure travel is a burgeoning industry in some mountainous regions of Nepal. The development of a trekking and expedition mountaineering infrastructure has created vital employment opportunities in remote areas and allowed visitors to embark on life-changing explorations. However, with the rapid, uneven, and largely unregulated growth of this industry have come environmental and resource challenges, the creation of new economic and social arrangements, and renewed questions of equity and safety. This intersectionality revealed itself dramatically on April 18, 2014, when a serac collapsed on Mt. Everest’s Khumbu Icefall and killed 16 Nepali high altitude workers. After several contentious days of deliberation and protests at Base Camp, the climbing season effectively ended when rumors began to circulate that attempts to continue climbing would be met with violence by individuals purportedly associated with the Communist Party of Nepal (Unified Marxist-Leninist). In this investigation, I combine the theoretical framework of James Scott’s transcript theory with the interpretive frame of Susan Birrell’s treatment of Everest as a text to be read and analyzed to show how rumors of Maoist involvement, though unsubstantiated, encapsulated specific anxieties and dominant preconceived notions about the structure and function of the Himalayan adventure travel industry. A traumatic and seemingly incomprehensible event created an ambiguous space where dominant discourses could be anonymously engaged with and challenged even as they shaped events in real time, a process of recontextualization that blurred the boundaries between a jointly-constructed public transcript of heroic adventure and hidden transcripts that portray far more polarized and nuanced views of sociopolitical orderings. My research reveals how spread of this particular rumor at a particular moment in time betrays both the discursive power of Everest itself and reveals quite unconsciously the essential structural features that order the social, economic, and political life of the remote Himalaya.

The city of Seattle currently finds itself in a state of emergency in reference to a growing number of people experiencing homelessness. In 2016, 4,505 people in King County were identified as living outside, and 6,183 living within the shelter system. While some in Seattle struggle to meet their most basic needs, others thrive in the economic growth of the cloud computing industry. Many tech workers are moving to Seattle to take these high-skill, high-paying jobs, and are subsequently reshaping neighborhoods and local economies. Historically, people experiencing homelessness have been forced out of Seattle’s gentrifying neighborhoods through processes of banishment. Banishment is defined as the legal removal of individuals from specified urban spaces for extended periods of time, and operates through police policies that criminalize activities associated with the poor. In recent years, many of these policies have been abandoned or deemed unconstitutional in the city of Seattle. Regardless, there appear still to be sanctioned spaces for homelessness and spaces where it is mysteriously absent. I have conducted series of interviews with people experiencing homeless in a rapidly gentrifying Seattle neighborhood. My sample includes individuals of a wide range of backgrounds and forms of homelessness to reveal the complex ways in which identity and homelessness intersect. Through analysis of response content, I have identified common themes that illuminate the social interactions that take place between housed and homeless community members throughout the process of neighborhood gentrification. These findings may help us to understand social forces that influence the migration of people experiencing homelessness between Seattle neighborhoods, and to understand broader concepts of the exclusion, seclusion, and accumulation of urban poverty. Results from this research may also help inform the provision of social services for people experiencing homelessness.

The city of Seattle has experienced immense urban change. Over the past 15 years, we see companies expanding, neighborhoods evolving, and populations being displaced. Recently, sociologists have discovered that neighborhoods that were traditional oases for queer life and living, including neighborhoods in Seattle, have experienced losses in the queer population. The body of research emerging on this topic largely credits this to a greater public acceptance of LGBTQ+ identities which have reduced barriers that kept queer populations from living in other areas. Though many public sources of information, news sites, blogs, and forums, propose gentrification of these neighborhoods as the force driving queer people from their homes. Between 2000 and 2012 Seattle’s traditional gayborhood, Capitol Hill, has seen a significant decrease in same-sex couples, according to the US census. With Amazon and other tech companies expanding into the Capitol Hill neighborhood and subsequent rising rents in that area, it may be the case that queer people can no longer afford to live in the gayborhood has made itself known in Seattle. In this research project I examine the motives for why queer people leave Capitol Hill through a series of interviews with LGBTQ+ people who are moving out of Capitol Hill. These interviews will provide insight into how gentrification and greater acceptance of LGBTQ+ people and other social factors may play a role in this new form of urban change.

A growing field of sociological research has provided evidence that Hispanic immigrants in the United States tend to have better health outcomes than their native-born counterparts. Despite the fact that Hispanic immigrants tend to be of a lower socioeconomic status and are less fluent in the English language compared to native-born Americans, immigrants show lower rates of both physical and mental health disorders. This phenomenon is commonly referred to as the “epidemiological paradox” or the “immigrant health paradox.” This study questions the nature of the epidemiological paradox as it applies to mental health disorders among Hispanic immigrants in Seattle. The primary aim of this research is to better understand why immigrants have low rates of mental disorders by examining factors such as perception of mental illness, interaction with and access to the American healthcare system, treatment of mental illness, social connectivity, and cultural determinants. I am conducting semi-structured interviews with first-generation immigrants attending the University of Washington (i.e. Hispanic immigrants born outside of the U.S who first moved to the country after age 16 and have resided in the country for less than 4 years). My sampling strategy involves contacting students through clubs on campus in addition to snowball sampling in order to generate a sufficient sample of 20 subjects for interview. Results from this research will contribute to an in-depth understanding of the nature and mechanisms behind the immigrant health paradox as it relates to rates of mental health disorders in the United States.

A large body of research has examined the association between disadvantage and crime in neighborhoods, usually finding a strong positive association between neighborhood disadvantage and crime. Neighborhood disadvantage is associated to crime via a variety of pathways, including, but not limited to, reduced educational opportunities and reduced collective efficacy (i.e., the ability of residents to control or influence the behavior of other individuals and groups in the neighborhood). However, research that links neighborhood disadvantage to crime has not examined the effects of clustering, better understood as grouping, of neighborhoods on the relationship between neighborhood disadvantage and crime. In metropolitan areas, predominantly minority-occupied, disadvantaged neighborhoods are often grouped together into specific areas. In other words, poor neighborhoods are adjacent to other poor neighborhoods compounding the disadvantage that inhabitants of these neighborhoods face. This is important to understand because it means that segregation of neighborhoods may be helping to drive high crime rates within neighborhoods. I extend this body of research by considering the role of clustering in the relationship between neighborhood disadvantage and crime. I use data from the National Neighborhood Crime Study, which includes tract, city, and metropolitan level variables to analyze crime and spatial inequality. The poverty and spatial proximity data is provided by the Neighborhood Change Database, which includes tract level data for impoverished neighborhoods as well as longitude and latitude of said neighborhoods. I use these two data sets to analyze the effects of neighborhood clustering through various data analyses. Preliminary data analyses show a statistically positive relationship between spatial proximity and number of murders. From this, it is expected that spatial proximity will also have a statistically positive relationship with overall crime.