Alcohol and other substance use are associated with a range of negative physical, mental, and social consequences including blackouts, unintended injuries, involvement in interpersonal violence, and other health problems. Young adults in college are particularly at risk for alcohol and other substance use. While existing research on reduction interventions often emphasized individual responsibilities of those that engage in alcohol and substance use, peer interventions remain an overlooked approach to harm reduction. Bystander interventions have been shown to be effective in preventing and reducing the harm of sexual assaults among college students. However, there is less empirical attention on applying bystander interventions to reduce the negative consequences of substance use. An important first step of understanding how to incorporate bystander interventions to address substance use is to have a reliable and valid measure assessing these behaviors. This study aims to develop and examine the psychometric properties of a new bystander behavior scale specific to substance use. Data came from a large multi-site survey study with 930 college students (Mage = 19.39, 69.6% female, 58.1% White). I will conduct exploratory factor analysis to extract underlying factors that best explain the observed correlations between the items. Next, I will examine convergent and discriminant validity of the scale scores by correlating them with established instruments such as Drinking Refusal Self-Efficacy Questionnaire and Personal Assessment of Responsible Drinker Identity. Individuals who score higher on the bystander behaviors measure are expected to score higher on self-efficacy in resisting alcohol and be more likely to identify as responsible drinkers. Results will provide initial validation data for the bystander behaviors measure and can be used in future research and intervention implementation that address substance use among college students.

The composition of metropolitan governance has many effects on land use decisions, budget allocations, housing development, transportation planning, and racial, economic, and social equity in urban areas. However, there has been little academic inquiry into the effect of regional governance structure on transportation accessibility. This paper seeks to examine statistical linkages between regional governance fragmentation and trends toward and away from greater transportation accessibility in metropolitan areas. I perform a comparative statistical analysis of 47 of the 50 largest Metropolitan Statistical Areas, examining census data from 2002 to 2022 and transit accessibility data from the University of Minnesota Accessibility Observatory from 2014 to 2021 to examine this relationship. The causal factor I investigate is metropolitan governance fragmentation, which I capture through a Governance Fragmentation Index (GFI). The dependent variable, transportation accessibility, is captured through an Accessibility Gap Index, which categorizes transportation access through accessibility levels throughout each Metropolitan Statistical Area, utilizing data from the Accessibility Observatory from 2014 to 2021. My analysis controls for potential confounding variables, such as geographic area, population size, poverty levels, and region. I expect to find that lower levels of governance fragmentation in a Metropolitan Statistical Area will be associated with greater gains in transportation accessibility. Whether or not a significant relationship is identified, the research conducted will contribute to literature and ongoing research surrounding metropolitan governance and transportation accessibility.

Affordable housing has recently emerged as a central focus of many policymakers’ agendas, especially in big cities, and they have implemented a variety of reforms to address this. In Seattle, the Mandatory Housing Affordability (MHA) program was rolled out in 2017, and then implemented citywide in 2019. The MHA created zones within the city, with new developments in MHA zones required to either build a certain number of rent-restricted affordable housing units for low-income people, or pay into a fund for affordable housing. Studies have shown mixed impacts of programs like the MHA on the housing supply; research about the impacts of such programs on housing and especially rent prices, however, is limited. Additionally, there is evidence that the effects of such policies are heterogeneous, varying by location and other factors. In this paper, I test for changes in rent and housing prices in Seattle overall using a difference-in-differences analysis. I also test for spatial variation within Seattle in these rent and housing prices by comparing MHA zones with non-MHA zones. The implications of these results will be important in addressing the next steps in housing policy. Since the MHA was a novel program in the inclusionary housing policy space, analyzing its effectiveness is crucial to determining how future policies should be shaped.

Although oft-cited, the effects of campaign finance are neither well-understood nor well-evidenced; in particular, the supposed vote-buying motive --- contributions given with the expectation the recipient legislator will change their vote on specific bills --- lacks systematic evidence, and literature is mixed both in findings and in methodological quality. Nevertheless, since 2000 (before which much of the literature of “vote-buying” developed), gross campaign expenditures have exponentially increased; prima facie, this suggests that contributors expect returns to their campaign contributions and that (if their expectations are not systematically irrational) campaign finance does affect political outcomes. Building on the public choice theory of regulation, I theorize agents pay the cost of campaign contribution to produce political pressure on a recipient politician, who must then trade-off between the support of competing interest groups. Thus, it is expected that increased campaign finance contributions from interest groups that favor a bill’s passage are associated with a ceteris paribus increased likelihood of the recipient politician supporting the bill. Moreover, because interest groups are heterogeneous in their ability to generate pressure, the estimated treatment effect should systematically vary by contributor type. Previous literature has generally attempted to find statistical associations between contributions from a select few contributing groups and votes on a handful of selected bills (often selected because they are ex ante expected to give significant results), while also failing to incorporate adequate regression controls. Hence, this paper attempts to reconcile the literature’s differing results by using logistic regression to examine a large dataset of US House members’ legislative votes from 1980-2022 and concurrent campaign finance data. This paper's primary contribution is to extend current methods into a large-n analysis, the statistical strengths and methodological limitations of which are informative for future research into interactive mechanisms in economic theories of regulation.

What role does foreign aid play in migration? Does aid encourage people to migrate, or does it encourage people to stay in their home country? Some scholars argue that foreign aid can target various push factors of migration such as economic insecurity, political persecution, and lack of support, decreasing the demand for out-migration. Other scholars argue that foreign aid can increase emigration by providing people with the funds necessary to emigrate. I explore the relationship between aid and migration in El Salvador by comparing out-migration data with US foreign aid data between the years of 2001 and 2022 to examine if more aid corresponds with lack of migration. My data draws from the US Department of State Bureau of Consular Affairs, TRAC Immigration, the Pew Research Center, the United Nations High Commissioner for Refugees, and USAID Data. I hypothesize that a large increase in US foreign aid will correlate to a small, delayed decrease of out-migration. The implications of this work inform policymakers on their use of foreign aid and contribute to the research surrounding the role of foreign aid. Instead of strict border policies in countries of destination, the use of foreign aid, if done in a recipient-centered and respectful way, could be an effective way to promote growth, peace, security, and democracy while ethically reducing out migration.

Vaccines have successfully reduced global infectious disease burden, but there is room to improve vaccination technologies. Because many pathogens infect at mucosal sites, a goal of new vaccines is to promote strong mucosal and systemic antibody and T-cell responses. Integrated fiber microneedle devices (iFMN) are a novel oral vaccination method that may achieve this goal. These devices are patches with a polymer backfill matrix and multiple >1 mm pyramidal needles that penetrate immune cell-rich mucosal tissue in the mouth, inducing immune responses at draining lymph nodes. To test the hypothesis that priming with iFMN delivery of a DNA vaccine increases mucosal and systemic antibody responses after systemic booster immunization with the same vaccine, male rhesus macaques (n=6) were primed with an iFMN delivery of a DNA vaccine encoding Influenza A Virus (IAV) Nucleoprotein (NP) at weeks (0) and (6). The macaques then received a single boost of the same NP DNA vaccine at week (12) using the proven delivery modality of Gene Gun epidermal delivery (GG). Mucosal secretions (including bronchoalveolar lavage, saliva, and nasal/tracheal swabs) and serum were collected 2-4 weeks before and after each immunization. I conducted enzyme-linked immunosorbent assays (ELISAs) to quantify antigen-specific IgG and IgA binding antibody at each timepoint. To characterize the priming effect of iFMN oral delivery on systemic and mucosal antibody responses, I compared these animals’ responses to macaques (n=8) previously immunized with a single GG dose of the same NP DNA vaccine. The iFMN-primed animals had robust post-GG boost NP-specific IgG responses in serum but these responses were not significantly higher than for macaques boosted solely with GG DNA. These results demonstrate that iFMN delivery did not effectively prime for robust systemic and mucosal antibody responses. Additional experiments will be done to confirm these findings.

Gravitational waves are ripples in the fabric of space-time caused by the rotation and merging of black holes deep in our universe. On earth, these waves cause a minute strain that can be measured with the Laser Interferometer Gravitational-wave Observatory (LIGO). We are developing a calibrator that exerts an oscillating gravitational force on the test mass of LIGO to precisely calibrate the strain sensitivity of the interferometer. The calibrator consists of four motor-driven rotors which are placed around the test mass. The four motors have to run at a constant speed and have to maintain an exact phase relationship. In this research, I designed motor-controller software in Python, which rotates the motors with constant speed with a phase uncertainty of less than 2 degrees. The system uses one of the motors as the reference and converts its encoder position changes to frequency. A Proportional-Integral-Derivative (PID) loop locks the encoder’s frequency to a reference frequency. Then, the three witness encoders are locked to the lead encoder. The gravitational force from the calibrator is calculated using a Python program from Prof. Gundlach's team. The code decomposes the calibrator into 3D points and applies multipole expansions to accurately compute the force at the center of LIGO’s test mass. The gravitational calibrator will help to reduce uncertainties in LIGO’s strain readouts.

Exclusionary zoning laws — which limit population densities and land uses in specific neighborhoods — are a typical feature of American municipal land use regulation. An extensive body of evidence links traffic-related air pollutant (TRAP) exposure to adverse health effects. Using zoning data and a model of TRAP levels in cities across the Seattle metropolitan area, I hypothesize that TRAP exposure will be greater on average in zones where higher-density housing is an allowed use, and lower on average in zones reserved for lower-density housing. I used the software package QGIS to spatially join zoning and air pollution data and used the software package R to perform correlation analyses between zone types (classified by maximum population density) and three common TRAPs (NO₂, black carbon, and ultra-fine particles.) This research highlights the public health implications of normative policy regimes like exclusionary zoning. These results can assist elected officials and planners in pursuing a more geographically distributive approach to increasing housing supply in the Seattle area, in order to minimize the TRAP exposure burden – and associated adverse health effects – faced by residents.

Despite the extensive literature on Canada and European countries, there is relatively little research on paid maternity policies in U.S. states due to its recency. Economic theory would suggest that fertility rates would increase with a paid maternity leave policy as the cost of having a child would be effectively subsidized. A strong family leave plan could be the deciding factor for many families to have a child. However, current research is inconclusive with there being no studies on U.S. fertility rates specifically in mind. The goal of my research is to provide insight on the way in which the U.S. fertility rate may be affected by paid leave programs. To accomplish these goals, I will be studying the implementation of paid maternity leave in Washington state specifically. I will be using a difference in difference method to measure the effect of this policy. I will be using data from the National Center for Health Statistics and the American Community survey for my fertility rate estimates. My research is in progress; however, I would expect either slight or no change in fertility rates in Washington based on previous research in the field. The goal of this research is further insight to nationwide implementation of this program by analyzing a specific possible implication of this policy and to contribute to the literature of paid maternity leave on fertility rates.

My research is an analysis of the pervasive issue of gender-based violence faced by women in India. Despite the presence of constitutional safeguards, the entrenched patriachal norms, and the prevalent misogyny in Indian society continue to deny women the healthy and peaceful lives they rightfully deserve. By analyzing pre-existing data along with data collected from interviews conducted with women between the ages of 35-45 from village Gumtala in Punjab, I have conducted a study to examine the relationship between postponed age of marriage and gender-based violence. It's through the lens of these women, I argue that decades of suppression in the name of culture have normalized violence against them. I conducted this study with careful consideration, ensuring that the questions posed in the semi-structured interviews were sensitive to the unique backgrounds and experiences of the women involved. Through the method of convenience sampling and qualitative analysis of interview data, I identified patterns of gender based violence and socio-economic factors. The results of my study suggest that early marriage not only increases women's vulnerability but also fosters economic dependence and social isolation of young brides that fuels the act of dowry practices causing marital abuse.These findings are not only essential in creating awareness regarding the vulnerable state of these women but also help me pose possible policy interventions by the Governmnet of India. My research has allowed me to argue how raising the legal marriage age for women to 25 mitigates gender-based violence, allowing women more time to pursue education and build financial independence before marriage. This study is an ode to all the women who are denied a voice.

While discussing as a group what types of experimentation we could potentially do, we had a variety of different ideas. We thought that with the DC plasma source available to us, it would be interesting to compare how the cleanliness of the vacuum chamber impacted when breakdown would occur. For our research, we are using a DC Plasma Discharge device, which creates a plasma between two electrodes inside of a vacuum chamber. A high DC (direct current) voltage is applied across the two electrodes and a current flows between them. Plasma, the 4th state of matter, is a gas where electrons have been stripped from atoms or molecules in a gas. What results is an electrically charged gas consisting of negative electrons and positive ions. The point at which a gas becomes a plasma is called breakdown. Breakdown depends on the pressure in the vacuum vessel, the distance between the electrodes, the type of gas and the voltage applied. A Paschen curve relates the breakdown voltage to the product of the distance between the electrodes and the pressure in the vacuum vessel. Our goal was to see how a dirty vacuum chamber would impact the Paschen curve. We expected that breakdown would happen at lower voltages with the clean vacuum chamber. We obtained data for creating the curve by running the plasma tube and measuring the pressure as the voltage increased while the vacuum chamber was contaminated with oil. We recorded pressure and voltage values for when breakdown occured and repeated this process with different distances. We then gathered the same data after the vacuum was cleaned. The implication of our research is that it will add to information on how the cleanliness of a vacuum chamber determines when breakdown happens in a plasma tube. In the future, more trials could be run and different gases could be tested. 

Acute pancreatitis (AP), inflammation of the pancreas in response to injury, is the leading cause of hospitalizations for gastrointestinal disorders in the US. Severe AP is correlated with a 30% mortality rate and treatment options are limited to supportive care. Our lab has previously reported that increasing serum levels of activin A, a TGF-β family member that regulates inflammation, is correlated to severity of AP in humans. Additionally, activin A has an established role in immunomodulation of neutrophils, which are critical innate immune cells driving AP. Our project aims to test the hypothesis that activin A promotes neutrophil activation and infiltration in AP. We performed qPCR on HL-60 cells treated with DMSO and/ or activin A to identify changes in the mRNA expression of immune activation genes, including CD11b, CD66b, and TNFɑ. We will also perform transwell migration assays on HL-60 cells treated with DMSO and/ or activin A to observe differences in neutrophil migration in vitro. We also intend to perform Western blot analyses, probing for pAKT and pERK, to identify the mechanism of activin A-induced neutrophil stimulation. We observed an increase in immunostimulatory mRNA in neutrophils treated with DMSO, which was further increased by activin. Additionally, we anticipate activin A and DMSO stimulation to promote neutrophil immunomodulation via the ERK pathway and increase neutrophil migratory capacity. The results of this project can provide more evidence that activin A can be a biomarker useful for risk stratification of patients with AP and allow for individualized treatments.

In the period of 1996-2000, within the greater context of the Peruvian internal conflict, a forced sterilization regime affected over 300,000 people, the majority of which were indigenous women. The program operated under the guise of promoting maternal healthcare within indigenous and impoverished communities and went largely unnoticed by the greater public both internationally and within Peru. The Quipu project (2017) was established as a way to reconcile with the notion that such sterilizations were left out of the state funded truth and reconciliation process. The project's unique transmedia approach created a database led by women who were forcibly sterilized, allowing them to simply call a telephone line that would record their stories and publish directly on a website. This truth telling and testimonial regime is remarkable in several ways as an approach for truth and reconciliation, in that its approach specifically mimics cosmological and community networks in a digital realm. This study posits that Andean women engage with the Quipu Project’s truth-telling regime to reclaim their identities as indigenous women, mothers, and community members as was disrupted by sterilization. Through a rhetorical examination of testimonials, I analyze the impact of sterilization and subsequent involvement in the project on community relationships, identity, spiritual beliefs, and calls for justice. Additionally, through first-hand interviews with Quipu Project researchers, I draw specific insights into the development of the project. This research develops a vital understanding of testimonial processes in the face of traumatic events, especially in the context of failed statewide policies and reconciliation efforts.

This study explores the impact of recent exchange rate fluctuations between China and the United States on Washington state agricultural exports to China. The substantial change in exchange rates, with the U.S. dollar appreciating against the Chinese yuan, has the potential to significantly affect Washington's agricultural exports to China. Given that almost one-third of the state's agricultural products are exported, with a substantial portion heading to Asian markets, particularly China, understanding the implications of exchange rate changes for Washington farmers is crucial. Therefore, this research also aims to investigate the effects of changes in the yuan/dollar exchange rate on the average income of Washington farmers and the prices of top agricultural commodities in the state. I analyze these effects by collecting data and constructing and estimating an empirical model. The results can provide valuable insights for policymakers, businesses, and stakeholders involved in the agricultural trade relationship between Washington and China.

This thesis discusses the impact of the Washington State Ferry (WSF). It provides the background of Washington State Ferry since COVID-19 and talks about the challenges that Washington State Ferry faced. Washington State Ferries are the primary public transportation between the San Juan Islands and Anacortes. The disruption of Washington State Ferries challenges San Juan Island's local economy. The paper aims to find how Washington State Ferries affects local short-term tourism by measuring tax revenue, business sales, and mobility. It uses regression models to study how the number of WSF cancellations, average delay times, ridership, and COVID-19 affect local businesses. The study compares the period before, through, and post-COVID-19 to prevent bias and to find out the actual impact of WSF. In conclusion, the research allows people to understand the importance of public transportation and provides some possible reasons for changes in the local economy.

This paper quantifies the impact on the South Korean Cultural Entertainment Industry (CEI) after China's "Korea Limitation Order". In November 2016, Beijing restricted South Korean artists to hold concerts and the broadcast of South Korean TV dramas, also banned cooperation between the two countries in the entertainments industries. This paper examines the effect did this had on exports of cultural products from Korea, and how Korea was able to adjust to this Geopolitical shock. I examine exports from Korea, to China, Japan, and the United States: Data from Cultural Entertainment Industry Products Exports, tangible or intangible goods that can create economic added value, such as Korean music and Filming Industries, and South Korea inbound foreign tourism statistics during 2011-2019 were collected. Deriving the deviation from an estimated autoregressive moving average (ARMA) model specification of exports from Korea after the “Korea Limitation Order,” in Difference-in-Difference (DID) Model, I found that South Korea's tourism industry has been particularly affected, with the most significant decline compared to the other two countries. At the same time, in the tourism industry, the substitution effect of Japanese market for the Chinese market is clear to see. The film and broadcasting industries have seen similar but less dramatic declines than tourism industry. There is no evidence that sectors of the cultural industry that are not included in this restriction category such as cartoon industry, are impacted by this shock.

The COVID-19 pandemic disrupted learning for students across the U.S., leading to a sharp decline in academic performance nationwide. Learning losses from the pandemic pose dire consequences on students’ future financial and social wellbeing as well as the health of the labor market as a whole. Policymakers have recognized the necessity of educational interventions such as high-dosage tutoring that can accelerate learning to make up for this gap, dedicating $122 Billion in funds for Elementary and Secondary School Relief (ESSER) as part of the American Rescue Plan Act of 2021. The State of Ohio utilized ESSER funds by launching its Statewide Mathematics and Literacy Tutoring Grant, through which college students in teacher training programs are paid to tutor school students in small groups. I am analyzing the impacts of this Grant on educational achievement of Ohio’s students to determine whether it has been sufficient to overcome pandemic-induced learning losses. I hypothesize that schools that have received tutoring through Grant partnerships experience significantly higher growth in student achievement than those that do not. I utilize data from Ohio School Report Cards from 2013 to 2023, published by the Ohio Department of Education and Workforce, to conduct a difference-in-differences analysis with propensity score matching. The findings of this study will enable critical analysis of educational policy efforts and their differential impacts on students of different backgrounds. Particularly, the study will provide insight into the efficacy and cost-efficiency of tutoring by “paraprofessional” teachers such as the college students who will receive payment through the Grant, which is not as well studied as tutoring by professional teachers. Finally, it will explore the feasibility of adapting reactionary educational interventions to programs that can help students in the long term.

The technology industry has developed rapidly since the last decade of the 20th century. It has provided a large amount of job positions for cities. However, when society was getting back to the pre-pandemic condition in 2022, the tech industry announced layoffs. More than 188,568 workers were unemployed in the United States. My research focuses on the indirect effect of mass tech layoffs. The indirect effect is the employment changes of other companies in the same community as the firm that announced the layoffs. In other words, the indirect effect measures the impact on the locals. The research topic is to analyze the short-term effect of technology industry layoffs in 2022, focusing on the indirect effect on the labor market. I measured the relationship between every sector’s employment, except the technology sector, and tech layoffs in this city using fixed effects models. After layoffs, numerous unemployed people are looking for jobs. Many people have to find other jobs to support their family or themselves. They are more likely to look for jobs in the same city because it is the easiest way to overcome adversity. Therefore, employment in other companies will increase. The anticipated result is that the correlation is positive, meaning when layoffs happen, employment in other non-tech industries will increase.

At 1:44 PM EST on March 11th of 2020, Trump tweeted that he would be “addressing the nation” at 9 PM EST that same day. This oval office address was a statement on COVID-19 and what the pandemic meant for America. This research is a rhetorical analysis of Trump’s public address on that day. His speech, already given in a time of uncertainty, led to widespread panic amongst consumers, with U.S. stocks falling the next day by almost 10%, in their worst day since the 1987 crash. News outlets and economists reported that the uncertainty that came along with the pandemic was only worsened because of Trump’s fear stoking and the atmosphere of uncertainty this speech created. What were people reading in the speech that could have pushed them towards this economic behavior? Conducting a rhetorical analysis of the speech through an innovation on the textual-intertextual method, this paper analyzes Trump’s speech and what people and the Trump administration said in response. In the first part of the paper, close textual analysis allows us to have an in-depth, microscopic understanding of the speech itself. In the second part of the thesis, we examine intertextual evidence of the speech’s extrinsic effect. Reading secondary sources that explicitly mention the primary text, including those produced by audiences hailed by the text as well as by Trump and his proxies, we can understand its broader reception especially as it relates to investor behavior and consumer attitudes. This study finds that Trump’s lack of key information, sparse emphasis on international cooperation, and contradictory rhetoric towards public officials all help explain the economic uncertainty that resulted from this speech. Studying the relationship between rhetoric and the economy through this research has implications on presidential rhetoric, unsuccessful early pandemic communication and the factors influencing stock price volatility.

The war in Ukraine has resulted in a high number of refugees fleeing to nearby countries. The literature on the economic effects followed by such migration is very limited. In particular, the effects of the influx of refugees on the labor markets of host countries are broadly researched. The purpose of this study is to analyze such effects in the context of Poland and Ukrainian refugees. This study investigates the effects of labor supply shocks caused by refugees on Poland’s labor market outcomes. Analysis was conducted using data on Ukrainian refugee migration within Poland, and the labor market factors such as wages and employment. The findings of this research help to have a clearer understanding of the expected effects on labor markets in similar refugee situations as Poland. Recognizing these effects can help countries be more prepared when facing labor market supply shocks which is beneficial for both the host country and the refugees.