The Populist Paradox: A Critical Framework Proposal

Donald Trump’s presidency has undeniably reignited academic interest in understanding the populist phenomenon and its political implications. Trumpian politics are frequently considered to be a stark departure from status quo politics, in favor of a radical right populism. Yet, the Trump presidency and populist theory itself poses a key contradiction, namely a populist paradox. I will propose a critical framework to understand populism as a mechanism of political power by the liberal state. In What is Populism?, Jan-Werner Müller identifies a contradictory nature to populism, as it often perpetuates the same political problems that the populist politics sought to replace. How could populist ideology, which is lauded as recognizing the systematic failures of the liberal state, also be a mechanism for its continued control? This paradox requires a theoretical framework to explain and unpack its implications. The seminal work of political philosopher Michel Foucault has immense explanatory power for this paradox when utilized as a conceptual framework. Populism ideology functions as a democratic justification for the maintenance of status-quo politics, which ultimately reproduces state power. I intend to develop a theoretical contribution to radical right populism studies, especially in regard to Trumpism in the United States. Interpreting Foucault’s state power theories, this article applies the key concepts of power-knowledge, domination, and governmentality to populism studies

Stratified Multilevel Logistic Regression Modeling for Risk Factors of Adolescent Obesity in Tennessee

Background: US adolescent obesity rates have quadrupled over the past 3 decades. Research examining complex factors associatedwith obesity is limited.Objectives: The purpose of this study was to utilize a representative sample of students (grades 6 - 8) in Tennessee to determine theco-occurrence of risk behaviors with adolescent obesity prevalence and to analyze variations by strata. Methods: The 2010 youth risk behavior survey dataset was used to examine associations of obesity with variables related to sampledemographics, risk and protective behaviors, and region. Hierarchical logistic regression analyses stratified by demographics andregion were conducted to evaluate variation in obesity risk occurring on three hierarchical levels: class, school and district. Results: The sample consisted of 60715 subjects. The overall obesity rate was 22%. High prevalence of obesity existed in males, non-white race, those ever smoked and was positively correlated with age. Across three state regions, race, gender, and specific behaviors (smoking, weight misperception, disordered eating, +3 hours TV viewing, and no sports team participation) persisted as significantpredictors of adolescent obesity, although variations by region and demographics were observed. Multilevel analyses indicate that\u3c 1%, 0 - 1.97% and4.03 - 13.06% of the variation in obesity was associated with district, school and class differences, respectively, whenstratifying the sample by demographic characteristics or region. Conclusions: Uniform school-based prevention efforts targeting adolescent obesity risk may have limited impact if they fail torespond to geographical and demographic nuances that hierarchal modeling can detect. Study results reveal that stratified hi-erarchical analytic approaches to examine adolescent obesity risk have tremendous potential to elucidate significant prevention insights

DU Undergraduate Showcase: Research, Scholarship, and Creative Works: Abstracts

Abstracts from the DU Undergraduate Showcase

SN 2022crv: IIb, Or Not IIb: That is the Question

We present optical and near-infrared observations of SN~2022crv, a stripped envelope supernova in NGC~3054, discovered within 12 hrs of explosion by the Distance Less Than 40 Mpc Survey. We suggest SN~2022crv is a transitional object on the continuum between SNe Ib and SNe IIb. A high-velocity hydrogen feature ($\sim$$-$20,000 -- $-$16,000 $\rm km\,s^{-1}$) was conspicuous in SN~2022crv at early phases, and then quickly disappeared around maximum light. By comparing with hydrodynamic modeling, we find that a hydrogen envelope of $\sim 10^{-3}$ \msun{} can reproduce the behaviour of the hydrogen feature observed in SN~2022crv. The early light curve of SN~2022crv did not show envelope cooling emission, implying that SN~2022crv had a compact progenitor with extremely low amount of hydrogen. The analysis of the nebular spectra shows that SN~2022crv is consistent with the explosion of a He star with a final mass of $\sim$4.5 -- 5.6 \msun{} that has evolved from a $\sim$16 -- 22 \msun{} zero-age main sequence star in a binary system with about 1.0 -- 1.7 \msun{} of oxygen finally synthesized in the core. The high metallicity at the supernova site indicates that the progenitor experienced a strong stellar wind mass loss. In order to retain a small amount of residual hydrogen at such a high metallicity, the initial orbital separation of the binary system is likely larger than $\sim$1000~$\rm R_{\odot}$. The near-infrared spectra of SN~2022crv show a unique absorption feature on the blue side of He I line at $\sim$1.005~$\mu$m. This is the first time that such a feature has been observed in a Type Ib/IIb, and could be due to \ion{Sr}{2}. Further detailed modelling on SN~2022crv can shed light on the progenitor and the origin of the mysterious absorption feature in the near infrared.Comment: 33 pages, 23 figures, submitted to Ap

Strong Carbon Features and a Red Early Color in the Underluminous Type Ia SN 2022xkq

We present optical, infrared, ultraviolet, and radio observations of SN 2022xkq, an underluminous fast-declining type Ia supernova (SN Ia) in NGC 1784 ($\mathrm{D}\approx31$ Mpc), from $<1$ to 180 days after explosion. The high-cadence observations of SN 2022xkq, a photometrically transitional and spectroscopically 91bg-like SN Ia, cover the first days and weeks following explosion which are critical to distinguishing between explosion scenarios. The early light curve of SN 2022xkq has a red early color and exhibits a flux excess which is more prominent in redder bands; this is the first time such a feature has been seen in a transitional/91bg-like SN Ia. We also present 92 optical and 19 near-infrared (NIR) spectra, beginning 0.4 days after explosion in the optical and 2.6 days after explosion in the NIR. SN 2022xkq exhibits a long-lived C I 1.0693 $\mu$m feature which persists until 5 days post-maximum. We also detect C II $\lambda$6580 in the pre-maximum optical spectra. These lines are evidence for unburnt carbon that is difficult to reconcile with the double detonation of a sub-Chandrasekhar mass white dwarf. No existing explosion model can fully explain the photometric and spectroscopic dataset of SN 2022xkq, but the considerable breadth of the observations is ideal for furthering our understanding of the processes which produce faint SNe Ia.Comment: 38 pages, 16 figures, accepted for publication in ApJ, the figure 15 input models and synthetic spectra are now available at https://zenodo.org/record/837925

National and State Trends in BMI Percentile, Obesity, and Overweight Rates Among Youth using YRBSS Data

Adolescent obesity is an area of growing public health concern. The Centers for Disease Control and Prevention conducts surveys through their Youth Risk Behavior Surveillance System (YRBSS) every two years to monitor a variety of health risk factors and behaviors among high school and middle school students. The YRBSS compiles information about obesity and BMI percentile, among many other factors. We accessed a combined dataset available on the YRBSS website which includes all data collected from high school students’ surveys from 1991 to 2013. Due to updating of questionnaires and adding of variables over the years, some variables only appear in the most recent years, limiting trend analysis to the timeframe in which the variable of interest was included. We analyzed the linear and quadratic trends in BMI percentile, obesity, and overweight rates in the national Youth Risk Behavior Survey (YRBS) from 1999 to 2013 and in the Tennessee YRBS from 2003 to 2013. Each variable was stratified by age and race to observe differences among groups. National trends show an increase in average BMI percentiles overall from 1999 to 2007, a decrease between 2007 and 2009, then another increase between 2009 and 2013. Tennessee trends show a dramatic increase in average BMI percentile overall from 2003 to 2007, then a decrease between 2007 and 2013. Since 2005, Tennessee has maintained a higher average BMI percentile (64.23, 66.37, 65.00, 64.96, 64.23) than the national average (63.47, 64.23, 62.81, 63.00, 63.51) for each recorded year, however, the decreasing trends in Tennessee and increasing trends in the nation have brought the average BMI percentiles of each to comparable rates. There is literature to support the variation of BMI among young, middle-aged, and elderly individuals. However, there is currently little evidence of differences in BMI percentiles, obesity, or overweight rates between different age groups of high school students. We expect to see little, if any, differences across different age groups of high school students in this study both nationally and at the state level. Racial and ethnic disparities exist for a variety of health conditions and outcomes. Many conditions, including obesity, disproportionately affect minority populations. We expect to see differences in BMI percentiles, obesity, and overweight rates across different races at both nationally and at the state level

Tennessee Stroke Registration Report, 2015

Background: Stroke is the fifth leading cause of death in Tennessee. The Tennessee Stroke Registry (TSR) Act requires East Tennessee State University’s College of Public Health to maintain a stroke database of participating hospitals and produce an annual report. Currently, twelve hospitals submit data to the TSR. Objectives: The TSR seeks to provide stroke information to Tennessee residents, policy makers, and health-care professionals. This presentation will highlight the key findings of the 2015 TSR report and will serve as an update to the 2014 report presented at the 2015 Tennessee Public Health Association conference. Methods: Data for the TSR was collected via Quintiles, American Heart Association’s online database. Microsoft Excel and ArcMap 10.3.x were used to conduct a descriptive analysis of stroke across Tennessee, observing characteristics of both stroke overall and of individual subtypes. Results: Seventy-nine percent of strokes in Tennessee in 2015 were ischemic. Some subtypes showed significantly different proportions of males versus females. For instance, females made up 63% of subarachnoid hemorrhage patients. The average age of stroke patients in Tennessee was 67.1 years, but varied for subtypes, ranging from 58.2 to 69 years. The majority of stroke patients (75.1%) had a recorded history of hypertension. Counties with high stroke mortality rates tended to cluster in areas of few certified stroke centers. Conclusion: Stroke subtypes exhibited different characteristics than stroke overall and geographic disparities were highlighted through the descriptive mapping. Identifying and understanding these differences and disparities can help in addressing ways to improve stroke care in Tennessee

Prevalence of and Risk factors for Adolescent Obesity in Tennessee using the 2010 Youth Risk Behavior Survey (YRBS) Data: an Analysis Using Stratified Hierarchical Logistic Regression

The purpose of the present study was to utilize a statewide, representative sample of students in grades 6-8 in Tennessee to determine the co-occurrence of health risk behaviors such as smoking, substance use and eating disorders, among adolescents by determining the impact gender, age, race, and geographic region have on the association of these behaviors with the prevalence of adolescent obesity. We also explored the role that district, school, and class level health risk behavior variables play in adolescent obesity. Among adolescent females in the sample, 17.25% were obese, whereas 27.27% of males were obese. Stratified Hierarchical Logistic Regression Analysis demonstrated that several variables such as having ever tried smoking, having a weight misperception, and eating disorder, watching TV for more than 3 hours a day, and not engaging on a sports team remained consistent in their significant association with adolescent obesity across all groups. The findings from this study suggest that certain risk behaviors play an important role in adolescent obesity. Perhaps the most significant finding of our study that requires more investigation is the effect of education on adolescent obesity