Reflections from Elsewhere: Ambivalence, Recuperation, and Empathy in Moral Geographies of Appalachian Ohio

Patterson, Cassie Rosita ProQuest Dissertations & Theses The Ohio State Uni 2015 해외박사(DDOD)

Throughout Appalachian Ohio, residents in small post-industrial cities grapple with redefining themselves as a place and a people in order to compete in the global economy. Young people caught in the middle of this economic transition—those born after the major factory closings in the early 1980s—struggle to negotiate their relationships with their hometowns, which typically offer limited career options beyond the service sector.Listening to the stories of college students and residents from postindustrial Appalachian Ohio helps us understand the ways in which place, economics, and identity intersect in their lives. In a region where cooperation regularly makes up for a lack of resources, leaving to attend college becomes a fraught decision. Moral geographies of the region—the ways in which people position themselves in relation to people and place—are thus filled with reflections from elsewhere, constructions of self and community that are responsive to the expectations of peers, outsiders, and discourses of success and failure that influence everyday choices. Reflections from elsewhere work in two ways in this dissertation: they are both the lived negotiations of self in response to the expectations of others as well as the ways that students and residents reflect upon, evaluate, and tell stories about the ruptures that have shaped their experiences.Students’ negotiations of place reveal the tensions they experience in coming from a place that is impossible to return to without the stigma of failure and to which continued belonging is possible only by habitually traversing the long-worn road home. Road stories, then, become all the more important as units of analysis, and force us to consider notions of place that cannot be defined in terms of a single locale. Contextualizing the students’ evaluative discourse, I examine critical positionings staked out by the university and home communities that shed light on the ways in which economic instability strains students’ relationships with home. I attend to important spaces in which reflections from elsewhere are prominent, analyzing both public and private “moral archives” of deindustrialization and recuperation. These moral archives are analyzed in contrast to the negative relationship between home and opportunity constructed by a university service-learning initiative directed toward the region (Ohio State University’s Buck-I-Serv Alternative Spring Break), as it seeks to orient young people toward college.Appalachia has long been a place where knowledge, resources, and representation intersect. While the moral archives of community elders attempt to hold these conflicting elements together, the moral geographies constructed by college students map that struggle onto the binary oppositions offered to them by the dominant culture. Both in reflection and reality, Appalachian Ohio students continuously travel the roads between points of value. This evaluative activity leads to some unexpected outcomes for individuals and undermines the seeming split between “going” and “staying.” Reflections from elsewhere among Appalachian Ohioans—as among many populations pushed toward mobility by a global economy—shape the life decisions of individuals. They merit the attention of the educators and policymakers who, wittingly or unwittingly, provide some of the mirrors.

An Economic Evaluation of Two Community Health Worker Models of Tobacco Dependence Treatments among Ohio Appalachian Smokers

Reisinger, Sarah A ProQuest Dissertations & Theses The Ohio State Uni 2019 해외박사(DDOD)

Background: Tobacco use poses a significant economic burden on public health. Tobacco dependence treatments are highly cost-effective; however, these methods are typically clinical in nature and may exclude groups who are disadvantaged. Identifying alternative cost-effective approaches is essential to improve health outcomes.Objective: The social ecological model (SEM) is applied to illustrate how economically informed policy, such as the cost-effectiveness of two evidence-based community health worker (CHW) models, can lead to sustainable benefits. This study: (1) systematically assessed the cost-effectiveness and quality of economic evaluations of community-based tobacco dependence treatments conducted as randomized controlled trials in the U.S.; (2) evaluated the cost-effectiveness of two evidence-based CHW-promoted models of tobacco dependence treatments among adult Ohio Appalachian smokers at end-of-treatment, and six and 12 months post-treatment; and (3) determined the difference in cost-effectiveness by subgroups.Methods: The systematic review searched eight databases and grey literature from their beginning to February 2018. Studies included focused on community-based tobacco dependence treatments conducted as randomized trials within the U.S. and excluded targeted populations unless they were disadvantaged. Two independent researchers reviewed nine publications and used Drummond and Jefferson’s economic evaluation checklist to assess quality. The economic evaluations utilized data from a group randomized trial comparing the effectiveness of two CHW models of tobacco dependence treatment among adult Appalachian smokers (NCT02695225) where participants were assigned to a CHW face-to-face condition or a CHW-promoted quitline condition. The provider perspective was used to determine the cost per quit and incremental cost-effectiveness ratio (ICER). Results were stratified by cigarettes per day and depression score subgroups.Results: The systematic review revealed the most cost-effective interventions had costs per quit or ICERs less than $6800. When examining the cost-effectiveness of two CHW interventions, the CHW quitline condition had the lowest cost per quit at each time point for both biochemically confirmed and self-reported outcomes. Costs per quit ranged from $3200 to $5450 for the CHW quitline condition and $7400 to $9800 for CHW face-to-face condition. ICERs ranged from $10,500 to $28,500. Both CHW models were more cost-effective among the lower risk subgroups. The quitline condition was most cost-effective with an average cost per quit of $2900 for both subgroups. The average cost per quit for the face-to-face condition ranged from $4100 to $6300 for the low risk subgroups. Sensitivity analyses confirmed the robustness of the findings.Conclusion: This study demonstrates that community-based tobacco dependence treatments within the U.S. are cost-effective among disadvantaged populations, such as Appalachia Ohio. When strategically engaged, economically informed tobacco control policies, such as CHW approaches, address community and individual smokers’ needs at and through multiple levels of the SEM; thereby reducing smoking prevalence and relapse rates, and improving health outcomes. Subgroup analyses underlined the importance of assessing intrapersonal characteristics and the potential to bundle multi-level services to address the needs of smokers with greater risk of relapse. These findings can inform future tobacco control efforts, address disparities, and impact public health in low resource and hard-to-reach communities.

Applications of Complex Network Dynamics in Ultrafast Electronics

Charlot, Noeloikeau ProQuest Dissertations & Theses The Ohio State Uni 2022 해외박사(DDOD)

The success of modern digital electronics relies on compartmentalizing logical functions into individual gates, and controlling their order of operations via a global clock. In the absence of such a timekeeping mechanism, systems of connected logic gates can quickly become chaotic and unpredictable -- exhibiting analog, asynchronous, autonomous dynamics. Such recurrent circuitry behaves in a manner more consistent with neural networks than digital computers, exchanging and conducting electricity as quickly as its hardware allows. These physics enable new forms of information processing that are faster and more complex than clocked digital circuitry. However, modern electronic design tools often fail to measure or predict the properties of large recurrent networks, and their presence can disrupt other clocked architectures.In this thesis, I study and apply the physics of complex networks of self-interacting logic gates at sub-ns timescales. At a high level, my unique contributions are: 1. I derive a general theory of network dynamics and develop open-source simulation libraries and experimental circuit designs to re-create this work; 2. I invent a best-in-class digital measurement system to experimentally analyze signals at the trillionth-of-a-second (ps) timescale; 3. I introduce a network computing architecture based on chaotic fractal dynamics, creating the first `physically unclonable function' with near-infinite entropy.In practice, I use a digital computer to reconfigure a tabletop electronic device containing millions of logic gates (a field-programmable gate array; FPGA) into a network of Boolean functions (a hybrid Boolean network; HBN). From within the FPGA, I release the HBN from initial conditions and measure the resulting state of the network over time. These data are transferred to an external computer and used to study the system experimentally and via a mathematical model.Existing mathematical theories and FPGA simulation tools produce incorrect results when predicting HBNs, and current FPGA-based measurement tools cannot reliably capture the ultrafast HBN dynamics. Thus I begin by generalizing prior mathematical models of Boolean networks in a way that reproduces extant models as limiting cases. Next I design a ps-scale digital measurement system (Waveform Capture Device; WCD). The WCD is an improvement to the state-of-the-art in FPGA measurement systems, having external application in e.g. medical imaging and particle physics. I validate the model and WCD independently, showing that they reproduce each-other in a self-consistent manner. I use the WCD to fit the model parameters and predict the behavior of simple HBNs on FPGAs.I go on to study chaotic HBN. I find that infinitesimal changes to the model parameters -- as well as uncontrollable manufacturing variations inherent to the FPGAs - cause near-identical HBNs to differ exponentially. The simulations predict that fractal patterns separate infinitesimally distinct networks over time, motivating the use of HBN dynamics as 'digital fingerprints' (Physically Unclonable Functions; PUFs) for hardware security. I conclude by rigorously analyzing the experimental properties of HBN-PUFs on FPGAs across a variety of statistical metrics, ultimately discovering super-exponential entropy scaling -- a significant improvement to the state-of-the-art.

Social Origins of Conflict: Individual, Transnational, and Interstate Political Violence

Edgerton, Jared F ProQuest Dissertations & Theses The Ohio State Uni 2021 해외박사(DDOD)

What are the social origins of conflict? In a three article dissertation, I analyze how social relations can help explain the spread of suicide terrorism over social ties, historical and contemporary group grievances can explain the onset of transnational political violence, and show that state socialization can help explain the diffusion of political institutions and conflict among groups of states.Article 1: Previous research has attributed the motivations of suicide bombers to religious fervor, political engagement, and organizational strategic goals, among others. However, the processes underlying suicide bomber mobilization may also be related to primary and secondary socialization through family and peer network ties. To better understand the association between kin and peer ties and suicide bomber mobilization, I use a data set of 2,923 individual fighter-level observations of combatants for the Islamic State. These data include individual demographic data and if a combatant volunteered to be a suicide bomber. Through these data, I assess ideational, material, and the social origins of suicide bomber mobilization. I find that a one unit increase in kin or peer network ties is positively associated with a combatant's odds of volunteering to be a suicide bomber.Article 2: Researchers and policymakers have increasingly recognized foreign fighter mobilization as a national security threat to foreign states and domestic populations. Yet, scholars remain divided on the motivations of foreign combatants, arguing that fighters may be motivated by material incentives, grievances, or opportunity. The motivations of foreign fighters may be especially complex, as they are engaging in a conflict outside of their home country. In this article, I analyze how historical and present-day group exclusionary policies affect contemporary patterns of conflict. To do so, I leverage novel data consisting of 4,101 individual fighter data of Islamic State volunteers fighting in Iraq and Syria. I argue that foreign fighters are mobilized by group grievances based on political and social exclusion and opportunity. I find that Islamic State fighters come from areas where Sunni Muslims were denied access to political power and have greater state capacity.Article 3: How do groups of cooperative states with similar political institutions form? Previous research on international regimes has focused on how regimes facilitate cooperation by aligning the incentives of states. Yet, our understanding of the social origins of cooperation in the international system is still limited. This research gap is notable given that social causes are potentially powerful mechanisms for explaining the characteristics and behaviors of states. If social relations influence the domestic organization of and conflict among states, then associations between these outcomes could lead to spurious correlations on the causes of conflict. I connect these processes and argue that social relations affect the domestic organization of states through socialization and conflict among states through in-group bias. Together, these dynamics create cooperative regimes, or groups of states with similar political and economic institutions that exhibit a higher level of intra-group cooperation along multiple dimensions.

An Investigation of Materials at the Intersection of Topology and Magnetism using Scanning Tunneling Microscopy

Walko, Robert ProQuest Dissertations & Theses The Ohio State Uni 2022 해외박사(DDOD)

Material systems that combine magnetism and topology have garnered intense interest recently due to predictions of a variety of phenomena such as the quantum anomalous Hall effect, chiral topological edge states, magnetoelectric effects, and Weyl semimetal and axion insulator phases. In this dissertation scanning tunneling microscopy (STM) and scanning tunneling spectroscopy (STS) are used to investigate the structural and electronic properties of several materials that exist at the intersection of topology and magnetism such as topological insulators, van der Waals layered materials, two-dimensional magnets, and intrinsic magnetic topological insulators.Specifically, STM was used to confirm the growth quality and properties of thin films grown by molecular beam epitaxy including Bi2Se3, SnSe2, MnSe, and Fe3GeTe2. In the van der Waals heterostructure SnSe2/Bi2Se3 a moire pattern was observed which was found to be correlated to a set of localized electronic states in STS measurements. STM was also used to provide feedback for the growth of the heterostructure MnSe/Bi2Se3, which led to successful growth of partial monolayers of MnSe. In Fe3GeTe2, a magnetic field dependent Kondo lattice behavior was observed as well as a ferromagnetic hysteresis loop using spin-polarized STM.In addition, this work reports the first STM study of the recently experimentally verified intrinsic antiferromagnetic topological insulator (AFM TI) MnBi2Se4. Its atomic and layered properties are found to reasonably match theoretical predictions. Two different terminations of its layered structure are observed on the surface with distinct electronic properties. In-gap states are observed near some step edges which could be related to predicted topological edge states. Another AFM TI, the related material MnBi2Te4, was also studied in which nanoscale surface manipulation using an STM tip was demonstrated.

Three Essays on Regional and Urban Economics

Deng, Nanxin ProQuest Dissertations & Theses The Ohio State Uni 2019 해외박사(DDOD)

This dissertation is composed of three chapters on regional and urban economics. The first chapter evaluates a regional policy in China. “City-County Consolidation” has been used during the last two decades as a primary tool to promote urbanization in China. Previous studies suggest this policy promotes economic growth in the urban area. Yet the effect of urban-led policy on surrounding rural areas has not been investigated. Using both city-level and county-level data in China, I propose a Difference-in-Difference (DID) framework to examine the impact of such consolidation on unconsolidated rural counties within the same prefectures. I further discuss the mechanism and the heterogeneous effect according to a machine learning tree approach. In the short term, the results suggest that consolidation leads to a significant loss of GDP per capita in surrounding rural counties. I also find that this policy has no significant effect at the prefecture level, although previous research finds that this policy has fostered agglomeration in the urban core. Therefore, consolidation seems to merely redistribute short-run economic activities across space, which exacerbates regional economic disparities. The second chapter examines the effect of city size on innovation. Innovation is an important driving force of regional and urban development. Cities of different size tend to have different innovative activities. The previous theoretical literature on agglomeration has suggested that city size may affect innovation through localization economies (e.g., input sharing, labor market matching, and knowledge spillovers) and urbanization economies (scale effects and urban diversity). However, whether urbanization economies come from city size or urban diversity is still under debate. This study aims to identify how city size effects innovation, controlling for the diversity effect and localization economies. I use city-level data in China to investigate how city size affects local patent intensity. Both 2SLS methods with different instrumental variables and a difference-in-difference framework with a quasi-experiment design are used to address the potential endogeneity issues. I find that city size has a significant positive effect on patent intensity in general, but this effect decreases with population size and shows clear heterogeneity across geographical locations. The results are robust to different specifications and methodologies. The findings are also consistent with previous theory and empirical evidence.The third chapter explains the reasons for the decreasing migration flows in the United States. Migration has been viewed as critical for the flexibility of the U.S. labor market, but its role of smoothing out macroeconomic shocks has been falling in recent years (Partridge et al. 2012). This study investigates the reasons for decreasing migration flows and provides evidence for the link between dwindling migration and increasing industry mobility in the United States from 2005 to 2015. Linked to the labor search theory (Mortenson, 1986), this study illustrates how industry mobility substitute for migration flows. Empirical results suggest that industry mobility is inversely associated with out-migration rate. The role of migration for smoothing out demand shocks becomes less important in regions where industry mobility rates are high. The findings justify that the increasing industry mobility can explain the decreasing migration flows in the U.S.

Response Surface Modeling Vehicle Subframe Compliance Optimization Framework and Structural Topology Optimization Through Differentiable Physics-Informed Neural Network

Chen, Liang ProQuest Dissertations & Theses The Ohio State Uni 2021 해외박사(DDOD)

Sizing and topology optimization are the two main structural optimization tools in a wide range of applications in aerospace, mechanical, and design. An iterative process solves the sizing optimization using classical gradient-based methods, usually carried out with an integrated process including a full-scale finite element analysis (FEA) to evaluate the design performance and a gradient search step at each iteration. With a complex real-world model, the optimization process is extremely cumbersome, time-consuming, and with no guarantee for an optimal solution or design. Alternatively, global population-based methods, such as genetic algorithm and particle swarm, can achieve the global optimal design with many simulations for every iteration to evaluate different designs for searching for the best candidates. This tremendous computational effort for simulations at each iteration prevents the global method from optimizing with complex physics simulation models. As for topology optimization, state-of-the-art methods, such as the Solid Isotropic Material with Penalty (SIMP) method, uses hand-coded gradient functions for optimization and must be run repeatedly for different boundary and loading conditions. Several practical and efficient machine-learning-based data-driven approaches have been proposed to optimize structures instantaneously using the generative adversarial network. Nevertheless, a complex machine learning model is costly because of the large amount of data and long training time.This dissertation presents several new, rapid, and accurate optimal design approaches for improving current structural sizing and topology optimization methods. First, for sizing optimization, to reduce the optimization time while preserving global optimality, a new optimization framework with response surface method and global sensitivity method is presented to approximate the simulation model with high accuracy while using a minimum number of simulations. The response surface approximates the original physics model using a mathematical basis, which reduces the time for function evaluation significantly. Global sensitivity analysis is conducted to reduce the model dimension and further reduce the number of function evaluations. A novel vehicle subframe compliance optimization framework is proposed using a response surface. The response surfaces approximate vehicle dynamic performance from multi-body dynamic simulation and subframe structure compliance from finite element analysis. It is shown that the mass of the subframe is reduced without violating the vehicle performance constraints. A physics-informed deep neural network for the structural topology optimization process is proposed in the second part of the dissertation. The deep neural network is trained with a built-in finite element model. The finite element model is made to be fully differentiable, and with the help of automatic differentiation, the gradient of the finite element model can be backpropagated to adjust the weights of the neural network. It is shown that the neural network can quickly learn the optimized structure without using much training data. Furthermore, no hand-code adjoint/gradient equations are required since the neural network can be trained to generate optimal structures based on the gradient information directly from the finite element model via automatic differentiation. The benefits of this physics-informed deep learning approach provide a data-efficient training process to construct a generator neural network to learn optimized topology under different design target conditions.

Occurrence, Diversity, and Impact of Viruses in Ohio

Hodge, Brian A ProQuest Dissertations & Theses The Ohio State Uni 2020 해외박사(DDOD)

Production of soft red winter wheat (Triticum aestivum), the type of wheat used for baking cookies, crackers, and cakes, is known to be reduced by several biotic diseases; however, the impact of virus diseases on wheat health is widely underestimated in Ohio. This is partially due to a lack of knowledge of which specific viruses are in Ohio and their distribution, which results in fewer resources for growers to control virus diseases. Our overarching goal was to identify and assess the prevalence of wheat viruses in Ohio and begin to fill knowledge gaps from identification, to impact on wheat production, to effective management. Two distinct research pathways were undertaken to accomplish this goal. In the first pathway, we conducted multiple surveys of Ohio wheat fields to identify viruses that pose a risk to wheat production. In the second pathway, we examined the impact of brome mosaic virus, one of the viruses identified in the surveys, on wheat production across multiple growth stages of infection and cultivars.Surveys of Ohio wheat fields were conducted in 2012, 2016, and 2017 in which samples showing virus-like symptoms were collected and subjected to high throughput sequencing, reverse-transcription PCR, or ELISA to assess virus sequence diversity, prevalence, and incidence within fields. From our surveys we identified barley yellow dwarf virus, cereal yellow dwarf virus, wheat streak mosaic virus, and wheat spindle streak mosaic virus as viruses that are a high risk to wheat production in Ohio based on sequence diversity, prevalence, and incidence within fields. Other viruses, including High Plains wheat mosaic virus, soilborne wheat mosaic virus, and oat necrotic mottle virus, were detected in Ohio but were determined to currently be low risk to wheat. Agropyron mosaic virus and cocksfoot mottle virus were identified in Ohio for the first time. We also identified and characterized novel members of Rymovirus, Luteovirus, and Endornaviridae. Further investigation of the novel Endornaviridae virus, Triticeae associated endornavirus, demonstrated that this virus is persistently associated with cultivated rye Secale cereale, rye relatives Secale sylvestre and Secale vavilovii, and soft red winter wheat. Logistic regression analysis indicated that four viruses were associated with the presence of volunteer wheat, three viruses with the presence of monocots as the previous crop, and BMV with the presence of nearby corn fields (P < 0.010). Several viruses were demonstrated to show spatial clustering at multiple spatial scales.From these surveys we discovered that brome mosaic virus (BMV), which was previously described as an unimportant pathogen of cereals, was highly prevalent in Ohio in certain years. The Ohio isolate of BMV was demonstrated to have an expanded host range that includes soybean and cowpea. Field experiments during the 2015-2016 and 2016-2017 field seasons with BMV-OH demonstrated that the virus can reduce grain yield up to 61% from infection at Feekes 1 and up to up to 25, 36, and 31% when infection occurred at Feeeks 5, 8, and 10, respectively. The yield loss caused by BMV would cause an estimated $25,302 loss in gross cash income on a 40-hectare wheat field for a grower, assuming similar incidence of infection. In the study, infection at Feekes 1 was associated with reduced plant population and height, infection at Feekes 5 was associated with induction of chlorosis in the flag leaf, and infection at Feekes 8 and 10 were not associated with any discernable symptoms or physiological changes. BMV also caused significant reductions in wheat test weight, a measure that is often associated with wheat quality, though additional analysis indicated little impact on the potential quality of food products.Field experiments were conducted during the 2017-2018 and 2018-2019 field seasons to determine if there was a causal relationship between BMV infection at Feekes 5, chlorophyll concentration in the flag leaf, and yield reduction. Increases in BMV infection were significantly correlated with changes in measures of flag leaf chlorosis, including chlorophyll concentration and incidence of chlorosis. These changes in measures of chlorosis were correspondingly correlated with changes in reductions in seed weight and yield, but not seeds spike-1. Relationships between BMV infection, chlorosis symptoms, and yield were more apparent in the susceptible cultivar Hopewell vs. the moderately resistant cultivar Truman, likely due to reduced infection titer in Truman.A field experiment was conducted in the 2018-2019 field season to determine if BMV infection at Feekes 1-2 caused increases in winterkill leading to yield reduction. This one-year experiment indicated that BMV did cause winterkill at high incidence of infection in the susceptible cultivar Hopewell. However, yield loss was also correlated with reductions in plant growth and development, with BMV infection correlated with changes in plant population assessed Feekes 3 and 11, fractional green canopy cover, and plant height. The results indicated that BMV caused high reductions in plant population in both a susceptible and resistant cultivar, but the impact on yield was more severe in the susceptible cultivar, potentially due to inhibiting compensation mechanisms of wheat.A greenhouse experiment was conducted to investigate the potential cause of yield reduction from BMV infection at Feekes 10. The results of this experiment indicated that BMV infection at Feekes 10 leads to a reduction in the number of kernels spike-1. The reduction in kernels spike-1 was associated with high BMV titer in the spike, and increased concentrations of total sugars and proteins. This work provides preliminary data to investigate the potential mechanisms of yield reduction from late growth stage infections, which may be linked to a stress response to BMV infection in susceptible cultivars.A panel of 196 historical soft red winter wheat varieties were screened under field conditions for resistance to BMV. The results of this experiment demonstrated that all cultivars were susceptible to infection, with most of the cultivars showing >70% incidence of infection. Similar results were observed in other collected responses, in which most of the cultivars showed >10% reduction in plant height, >10% reduction in chlorophyll concentration in the flag leaf, and >10% reduction in spike weight. Regression analyses between incidence of BMV infection and other collected responses showed poor correlation between responses (R-square<0.35), indicating that most cultivars in this population may be tolerant to BMV infection.Our results demonstrate that, contrary to dogma, BMV can have an economic impact on wheat production and can do so through both early and late growth stages, unlike many other cereal viruses. Overall, this work has developed a comprehensive database of viruses that are in Ohio, identified viruses of high risk to wheat production, and provided valuable sequence diversity, host range, plant resistance phenotyping, and yield impact data that can be used to enhance management strategies.

Thinking Patria: Figurations of the in Discourses of the Liberal Spanish State, 1859-1906

Barrile, Matthew James ProQuest Dissertations & Theses The Ohio State Uni 2017 해외박사(DDOD)

"Thinking patria: Figurations of the Jew and Discourses of the Liberal Spanish State, 1859-1906" examines how the formation of the Spanish State in the late nineteenth and early twentieth centuries was envisioned and debated through the discursive Jew. Figurations of the Jew function as malleable signifiers constructed by non-Jews to convey ideas and make sense of the rapidly changing world around them. This project explores how themes pertinent to the consolidation of the liberal Spanish State are articulated: national homogeneity and cultural heterogeneity; the debate surrounding religious freedom and the resultant economic benefit; the tension between centralization and federalism; and the importance of the literary novel for cultural hegemony. Moreover, it analyzes how nineteenth-century Spain's centralizing political paradigm could account for the emergence of specific and autonomous regional identities that implied detachment from the desired homogeneity of the State. Included in the discussion are literary novels, plays, poetry, paintings, periodicals, and personal correspondence, produced by some of the era's most prominent novelists, politicians, historians, and artists, including Benito Perez Galdos, Emilia Pardo Bazan, Leopoldo Alas, Gasper Nunez de Arce, Emilio Castelar, Angel Pulido, Francisco Pi i Margall, Manuel Murguia, Isidoro de Hoyos, and Maria Mariano Fortuny, to name a few.

Three Essays on Community Service Volunteers' Self-Efficacy and Learning in the AmeriCorps Programs

Ma, Yinglin ProQuest Dissertations & Theses The Ohio State Uni 2022 해외박사(DDOD)

Volunteering is an important component of the daily lives of many individuals in the United States. Volunteering not only increases the capacity of organizations to provide essential services, but it may also positively affect the self-development of individual volunteers. My dissertation examines individual volunteers' self-efficacy development and learning in an AmeriCorps community-service volunteering context. The empirical analyses use survey and administrative data of Ohio AmeriCorps service volunteer members. The data were collected between 2017 and 2020 in partnership with ServeOhio, the Ohio Commission on Service and Volunteerism, which oversees the state AmeriCorps programs in Ohio.My first chapter draws on social cognitive theory to examine the development of AmeriCorps' volunteers' self-efficacy to perform community service. The analysis uses panel survey data collected from Ohio AmeriCorps volunteers collected at the beginning and end of their service terms in 2017-18 or 2018-19 (n=189). Using a random-effects model, the results indicate that self-efficacy generally increased from the beginning to the end of the service term. Perceptions of having performance accomplishments, positive role models, and receiving useful feedback significantly increased self-efficacy to perform community service, while experiencing service stress diminished self-efficacy development.My second chapter focuses on AmeriCorps volunteers' learning. Through volunteering, volunteers may increase their knowledge of social issues and the needs of their service beneficiaries, gain interpersonal and career-related skills, and develop abilities to work with diverse populations. Previous studies discuss the benefits of volunteer learning, but few delve into the mechanisms through which volunteers learn. Social cognitive theory suggests managerial support may enhance volunteers' self-efficacy, which in turn, motivates their learning. Using panel survey data from two cohorts of Ohio AmeriCorps volunteers, I examine whether their self-efficacy and perceived managerial support at the beginning of the service term predict perceived learning outcomes reported at the end of the service term. Further, I probe the mediating and moderating influence of managerial support and self-efficacy on volunteers' learning. Results provide empirical evidence that both self-efficacy and managerial support predict volunteers' perceived learning. Further, self-efficacy partially mediates the effect of managerial support on perceived learning, where managerial support matters more for those with a lower level of sense of control, a component of self-efficacy. The study constructs indicators for perceived learning outcomes, self-efficacy, and managerial support and discusses strategies for volunteer managers and others to support volunteers' development in self-efficacy and learning.My third chapter further examines volunteer self-development and learning in a time of crisis ' the onset of the COVID-19 pandemic. The COVID-19 pandemic disrupted the nonprofit sector and its volunteers in multiple ways. This study investigates the relationship between the onset of the pandemic and volunteer outcomes ' specifically, volunteer learning in the context of the AmeriCorps program. I leverage survey data collected for three consecutive cohorts of AmeriCorps community service volunteers, including two cohorts who served prior to the pandemic and one cohort serving when the pandemic began. In addition to exploring the direct relationship between serving during the onset of the pandemic and volunteer learning, I find that managerial support significantly moderates the relationship between serving during the onset of the COVID-19 pandemic and volunteer learning outcomes. The study suggests practical strategies for managers and others to support volunteers' learning in a crisis period, including providing helpful feedback, positive role models, sufficient training, and treating volunteers with respect.