Browsing by Subject "Vulnerability"

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Because I Write: A Teacher-Writer Teaches Writing
(2018-11) Baker, Jodi
Writing enhances learning and is recognized as being essential; however, writing is neglected in research, teacher preparation and in classrooms. According to the National Assessment of Educational Progress, the majority of students are not proficient at writing. Teachers are often uncomfortable teaching writing because of its complexity, because they lack support or expertise, or because they are not writers themselves. Teachers who identify as writers can bring their knowledge about writing into the classroom. The focus of this study was to deeply understand the pedagogy of a 6th grade teacher-writer. Through seven weeks of daily participation and observations during writing instruction, ethnographic methods were employed to explore how an elementary teacher-writer teaches writing, how an elementary teacher’s writing identity impacts writing instruction and influences student writers, and how identifying as a writer contributes to a teacher’s ability to navigate multiple writing discourses to make informed pedagogical decisions. Prominent themes revealed that the teacher-writer’s instruction honored students’ agency and empowerment, embraced vulnerability, and incorporated reflective practice. The teacher-writer negotiated standards, district curriculum, literacy experts’ theories, students’ needs, and her own writing experiences. Based on the teacher’s dynamic pedagogy, I define a new term, “writing capital,” as the knowledge, experiences, and embodiment teacher-writers draw upon to plan and teach writing. Students identified strongly as writers and named their teacher’s writing and writing identity as influential factors. This study contributes to growing interest in how teachers’ writing identities impact writing instruction and students’ writing identities. Results suggest that teacher preparation programs and professional development should incorporate opportunities for educators to explore and develop writing identities, and writing curriculum should include opportunities for teachers to share their writing and writing lives with students.
BEHAVIORAL PREDICTORS OF INDIVIDUAL DIFFERENCES IN OPIOID ADDICTION VULNERABILITY
(2021-04) Swain, Yayi
Understanding behavioral predictors of individual differences in opioid addiction vulnerability could provide critical insights into the mechanisms underlying opioid addiction and could lead to more effective treatments. However, very few behavioral predictors of individual differences in opioid self-administration (SA), a key preclinical model of opioid addiction, have been established. The goal of this dissertation was to evaluate several potential behavioral predictors of individual differences in morphine SA in rats, and to establish novel methodologies for studying opioid addiction vulnerability using the SA paradigm. Study 1 showed that spontaneous locomotor activity in a novel environment, an animal model of sensation-seeking that predicts SA of several drugs of abuse (e.g., stimulants), did not predict individual differences in morphine SA. Study 2 found that greater severity of anhedonia-like behavior during withdrawal from acute morphine exposure (withdrawal-induced anhedonia, WIA) predicted subsequent lower acquisition, demand, and reinstatement of morphine SA. Study 3 showed the feasibility of using regularized factor analysis on morphine SA measures, and revealed that a common latent factor underlies four separate measures of morphine SA. Additionally, while acquisition, demand and morphine-induced reinstatement associated closely with the common latent Addiction factor, stress-induced reinstatement did not. Overall, these studies extended the opioid individual differences literature by establishing WIA as one of the first behavioral predictors of opioid SA, and also expanded the range of analytical tools to be utilized in preclinical behavioral studies.
The burden of Yellow Fever in Brazil: Quantifying disease mortality and producing short-term forecasts
(2020-07) Servadio, Joseph
Yellow Fever is a mosquito-borne viral disease impacting much of South America and sub-Saharan Africa. It is endemic in several nations, causing hundreds of thousands of annual infections and tens of thousands of deaths. In Brazil, cases in recent decades have been seen in western areas of the nation, typically in regions adjacent to the Amazon Rainforest. A major outbreak beginning in December 2016, however, saw a major increase in cases, particularly in southeastern states. As a result, there is interest in finding ways to predict when and where future Yellow Fever cases are expected. Also of interest is the ability to anticipate future fatalities by finding the proportion of cases that are fatal. Several mechanisms influence risk of Yellow Fever cases, including human activities and environmental conditions. The latter is comprised of many characteristics outside of human control, representing a component of risk that cannot be targeted for direct intervention, but only used for preparations. Using environmental conditions to predict future Yellow Fever burden typically employs the use of either mathematical or statistical models to quantify relationships between environmental predictors and disease burden. In developing such models, several assumptions are made out of necessity. One particular assumption, relating to the time units used in developing a model, is not commonly investigated for its potential impact on describing disease dynamics. In order to investigate these various topics, four studies were conducted in order to predict Yellow Fever burden using various environmental conditions, estimate fatality risk among severe Yellow Fever cases, and examine assumptions of time unit sizes when describing disease incidence probabilistically. The findings of the various studies show sensitivity when changing time unit sizes, offer an update of the estimated fatality risk among severe Yellow Fever cases, and estimate potential for Yellow Fever case burden throughout Brazil both using annual environmental trends and weekly weather patterns. Methodological contributions are discussed.
Cities of (In)Difference: A Mixed-Methods Analysis of Place and Wellbeing In Later Life
(2018-06) Finlay, Jessica
Where one lives constitutes an important determinant of health and quality of later life. Yet few studies to date focus explicitly on the everyday experiences, contexts, and needs of individuals to age well within their physical and social environments. While aging in place represents a widespread goal of individuals, service providers, and policymakers, it remains an ambiguous, problematic, and uncritical concept. This can have devastating consequences as it is frequently applied with little consideration of the places themselves. This study investigated aging in a harsh continental climate with a strong focus on underrepresented low-income and racially diverse older adults. Three case study areas across the Minneapolis (Minnesota, USA) metropolitan area purposefully contrasted socio-demographic and geographic characteristics. Seated and mobile interviews were conducted with independent-dwelling men and women (n=125, mean age 71 years) from May to October, 2015. A geospatial audit evaluated participants’ homes at the dwelling, street, and neighborhood level. Ethnography with six participants over twelve months (September, 2015 – August, 2016) and semi-structured interviews with ten local policymakers and community service providers (May – October, 2016) deepened understanding. The findings depict how built, social, and natural environments contribute to aging in very particular ways. Older bodies literally express structured advantages and disadvantages of their surrounding contexts. Aging in place efforts can exacerbate the deeply uneven conditions of American cities and the vulnerabilities of those aging ‘in the margins’. Theoretical analyses unpack and unsettle discourses about aging in order to address problematic assumptions, blind spots, and unchallenged and unconsidered modes of thought upon which geography rests. The chapters engage political, economic, feminist, critical race, disability, health, and urban theories to enrich not only geographic scholarship, but also the lives of older adults. The dissertation destabilizes the foundations of age-friendly governance and generates novel possibilities for more just and inclusive modes of urban form. It creates more room for alternative ways of ‘being in the world’ based upon a richer understanding of people, place, and space across the life course.
Computational Trust at Various Granularities in Social Networks
(2015-12) Roy, Atanu
Trust has been a ubiquitous phenomenon in human lives. The phenomenon of trust has been studied at various granularities over the centuries by various researchers encompassing all disciplines of academia. Historically, it has been witnessed that the primary mode of studying trust has been surveying subjects and documenting the results. But the burgeoning electronic social media have provided us with the unique opportunity of studying trust under a new perspective, which is known as computational trust. Computational trust is defined as the generation of trust between two human actors mediated through computers. This is an active area of research due to the proliferation of various socially rich datasets over the past decade. This includes massively multi-player online games (MMOs), online social networks and various web services, allowing actors to trust each other in an online virtual setting. The first part of this thesis investigates various aspects affecting dyadic (or interpersonal) trust, i.e., trust between two actors. This includes formation, reciprocation and revocation of trust. Taking into account various nuances of dyadic trust, this thesis predicts the occurrence of these three phenomena in the datasets. Instead of looking at these phenomena by itself, this thesis looks at this phenomena in conjunction with social relations for better predictive modeling. One of the major requirements in trust applications is identifying the trustworthy actors in the social networks which will be the subject of investigation for the second part of this dissertation. An important factor in the prediction of trust is an actor's inherent ability to trust others and the perception of the actor in the network. This thesis proposes a pair of complementary measures that can be used to measure trust scores of actors in a social network using involvement of social networks. Based on the proposed measures, an iterative matrix convergence algorithm is developed that calculates the trustingness and the trustworthiness of each actor in the network. Trustingness of an actor is defined as the propensity of an actor to trust his neighbors in the network. Trustworthiness, on the other hand, is defined as the willingness of the network to trust an individual actor. The algorithm runs in O(k * |E|) time where k denotes the number of iterations and |E| denotes the number of edges in the network. This thesis also shows that the algorithm converges to a finite value very quickly. Lastly, this thesis introduces the concept of "vulnerable paths" and identifies those paths in a social network. Based on the hypothesis that these vulnerable paths are imperative for influence flow, a new algorithm proposed in this thesis, exploits these paths for better and more targeted viral marketing using trust scores. It is shown that there is an improvement as high as 9% in identifying these paths using the proposed algorithm than state of the art trust scoring algorithms. This thesis makes the following contributions. It studies the generative mechanisms of trust not in isolation, but in conjunction with the social processes(relations) around trust. Whereas earlier studies were interested in looking at the cross-sectional view of trust, this study investigates the longitudinal view of trust. Instead of looking only at the dynamics of initiation of interpersonal trust, this study looks at the various other dynamics such as reciprocation and revocation of interpersonal trust. This study also exploits the negative feedback property in trust to propose computationally stable pair of global trust measures, which can be used to measure the propensity of actors to trust and be trusted in a network. Finally, this pair of scores is leveraged to be used in various applications such as viral marketing, identification of "vulnerable paths" and inoculation of a network from rumor spread.
Development and Application of the Network Weight Matrix to Predict Traffic Flow for Congested and Uncongested Conditions
(2016-08-01) Ermagun, Alireza; Levinson, David M
To capture a more realistic spatial dependence between traffic links, we introduce two distinct network weight matrices to replace spatial weight matrices used in traffic forecasting methods. The first stands on the notion of betweenness centrality and link vulnerability in traffic networks. To derive this matrix, we assume all traffic flow is assigned to the shortest path, and thereby we used Dijkstra's algorithm to find the shortest path. The other relies on flow rate change in traffic links. For forming this matrix, we employed user equilibrium assignment and the method of successive averages (MSA) algorithm to solve the network. The components of the network weight matrices are a function not simply of adjacency, but of network topology, network structure, and demand configuration. We tested and compared the network weight matrices in different traffic conditions using Nguyen-Dupuis network. The results led to a clear and unshakable conclusion that spatial weight matrices are unable to capture the realistic spatial dependence between traffic links in a network. Not only do they overlook the competitive nature of traffic links, but they also ignore the role of network topology and demand configuration. In contrast, the flow-weighted betweenness method significantly operates better than unweighted betweenness to measure realistic spatial dependence between traffic links, particularly in congested traffic conditions. The results disclosed that this superiority is more than 2 times in congested flow situations. However, forming this matrix requires considerable computational effort and information. If the network is uncongested the network weight matrix stemming from betweenness centrality is sufficient.
Examining Well-being and Vulnerability in Data-Poor Nations: Azerbaijan and Kyrgyzstan
(2021-12) Cervantes De Blois, Chelsea
To investigate the complex human-environmental systems in the Eurasian low- and middle-income countries of Azerbaijan and Kyrgyzstan, I apply both qualitative and quantitative methods to four different topics: (1) creating a Toxic Site Identification Program dataset, (2) integrating indigenous knowledge and geospatial analyses, (3) designing a model to reduce toxic hazards from inland bodies of water, and (4) forecasting repeated ethnic conflict through the lens of human-environmental challenges from climate, migration, and conflict. I address research gaps in understudied and data-poor LMICs by generating new datasets and models to address human-environmental problems.
Network Econometrics and Traffic Flow Analysis
(2016-10) Ermagun, Alireza
This dissertation introduces concepts, theories, and methods dealing with network econometrics to gain a deeper understanding of how the components interact in a complex network. More precisely, it introduces distinctive network weight matrices to extract the existing spatial dependency between traffic links. The network weight matrices stem from the concepts of betweenness centrality and vulnerability in network science. Their elements are a function not simply of proximity, but of network topology, network structure, and demand configuration. The network weight matrices are tested in congested and uncongested traffic conditions in both simulation-based and real-world environments. The results of the analysis lead to a conclusion that traditional spatial weight matrices are unable to capture the realistic spatial dependency between traffic links in a network. Not only do they overlook the competitive nature of traffic links, but they also ignore the role of network topology and demand configuration in measuring the spatial dependence between traffic links. However, the proposed network weight matrices substitute for traditional spatial weight matrices and exhibit the capability to overcome these deficiencies. The network weight matrices are theoretically defensible in account of acknowledging traffic theory. They capture the competitive and complementary nature of links and embed additional network dynamics such as cost of links and demand configuration. Building on real-world data analysis, the results contribute to the conclusion that in a network comprising links in parallel and series, both negative and positive correlations show up between links. The strength of the correlation varies by time-of-day and day-of-week. Strong negative correlations are observed in rush hours, when congestion affects travel behavior. This correlation occurs mostly in parallel links, and in far upstream links where travelers receive information about congestion (for instance from media, variable message signs, or personal observations of propagating shockwaves) and are able to switch to substitute paths. Irrespective of time-of-day and day-of-week, a strong positive correlation is observed between upstream and downstream sections. This correlation is stronger in uncongested regimes, as traffic flow passes through the consecutive links in a shorter time and there is no congestion effect to shift or stall traffic.
A Network-Based Framework for Hydro-Geomorphic Modeling and Decision Support with Application to Space-Time Sediment Dynamics, Identifying Vulnerabilities, and Hotspots of Change
(2016-05) Czuba, Jonathan
Increasing pressure to meet the food, water, and energy demands of our growing society in a changing climate has strained the physical, chemical, and biological functioning of watersheds to maintain ecosystem services, such as providing clean water, and to sustain a productive and diverse ecosystem. Confronted with multifaceted environmental issues, watershed managers could use a simple first-order approach for understanding how physical, chemical, and biological processes operate within a watershed to guide watershed-management decisions. This research advances a network-based modeling framework for guiding effective landscape management decisions towards sustainability focusing on understanding large-scale system functioning and predicting the emergence of vulnerabilities, “hotspots” of change, and unexpected system behavior. Based on a combination of mathematical theory, field-data analysis, and numerical simulations applied to the dynamics of bed-material sediment (i.e., the sediment composing the riverbed) on river networks, we (1) identify a resonant frequency of sediment supply from network topology and sediment-transport dynamics that could lead to an unexpected downstream amplification of sedimentological response in the Minnesota River Basin; (2) identify hotspots of likely sediment-driven fluvial geomorphic change where sediment has a tendency to persist and exacerbate channel migration on the Greater Blue Earth River Network; and (3) elucidate the hierarchical role of river-network structure on bed-material sediment dynamics in propagating, altering, and amalgamating the emergent large temporal fluctuations and periodicities of bed-sediment thickness. By embedding small-scale bed-material sediment dynamics on a river network, this research shows that it is possible to gain a better understanding of the large-scale system functioning whereby management actions that target the identified critical times, places, and processes in the landscape will be most effective at improving water quality and the health of the aquatic ecosystem.
Online Mugshots: Vulnerability, Commoditization, and Devastation
(2017) Oppenheimer, Jonathan
My research exploring the legislative debate around online mugshots began in 2015 while interning at the now defunct Council on Crime and Justice (CCJ). As a graduate student studying social work and public policy, I have a passion for criminal justice reform, and my supervisor at CCJ tasked me and a fellow intern with learning more about the proliferation of websites that were profiting from and exploiting open records laws throughout the country by legally obtaining and widely disseminating mugshots on the internet for profit. Our goal then was the same as mine remains today: Devise legislation to curb this practice and mitigate one of the many collateral consequences facing people who have entered the criminal justice system in America. We knew then we faced an uphill battle, with multiple bills dying in the Minnesota legislature in 2014 (Minnesota H.F. 1933, 2014; Minnesota H.F. 1940, 2014). As such, we set out to meet with the advocates and stakeholders whom we knew to have a strong stake in the debate, most notably lobbyists for First Amendment rights, government transparency, and the Minnesota Sheriff’s Association. Only with these perspectives in hand could we consider approaching legislators and persuading them to put forth new legislation.
User inequity implications of road network vulnerability
(Journal of Transport and Land Use, 2010) Jenelius, Erik
An important purpose of the road transport system is to allow people to commute in efficient and reliable ways. For various undesired reasons, however, link capacities are sometimes reduced or links are closed completely. To assess and reduce the risk of such events, a key issue is to identify road links that are particularly important, i.e. roads where disruptions would have particularly severe consequences. This paper presents a method for incorporating user equity considerations into a road link importance measure. As a complement to measuring the total increase in vehicle travel time, we also measure the disparity in the distribution among individual users. These two components are combined to form an equity-weighted importance measure. We study the properties of this measure both analytically and in a full-scale case study of the Swedish road network. A main result is that increasing the weight put on the equity aspect transfers importance from the main roads to smaller local roads. The use of the measure in transport policy and planning is discussed.

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