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Magister Artium (Sport, Recreation and Exercise Science) - MA(SRES) / Gymnastics is a sport code that develops basic motor skills, hand-eye coordination and provides participants with an opportunity to socialize and learn new skills. There are various social factors, such as a family’s socioeconomic status or accessibility to sports facilities that may play a role in affecting levels of participation. The aim of this study is to investigate the social factors that have an influence on gymnastics participation in the Western Cape. To this end, a qualitative approach is adopted to collect data. This study also adopts the ecological systems theory (Bronfenbrenner, 1995) as the theoretical framework, and is used to analyse and interpret current social factors that directly or indirectly influence participation in gymnastics. The study’s objectives were to ascertain which social factors hinder participation, and which social factors promote participation, thus, coaches, parents and gymnasts participated in focus group discussions. Key informant interviews took place with experts in the field of gymnastics in the Western Cape. A thematic analysis was conducted on transcriptions from the focus group discussions and key informant interviews. Social factors investigated in this study occurred in the chronosystem, macrosystem, exosystem, mesosystem, and microsystem, and had both a direct and indirect influence on the gymnast’s continued participation. These systems are defined by Bronfenbrenner (1995), as the environment of the individual, in which they grow and develop. The research findings of this thesis are used to draw conclusions and make specific recommendations for practice and further research. The information gathered in this study can assist all stakeholders within the field of gymnastics, such as parents, judges, coaches, gymnasts, and the supporting community which surround the participating gymnast.

The purpose of this paper is to examine social systems theory as it relates to the inclusion of disenfranchised populations into the larger social system by enabling these populations to receive education and resources which can allow them to develop skills needed to achieve inclusion. Specifically this study is concerned with using elements of social systems theory to develop a sexual education program for a population identified with an Intellectually/ Developmentally Disability (ID/DD). In order to do this, it is necessary to work within the family or caregiver system where these individuals live and function. Caregivers must be helped to recognize the potential for inclusion in this area of life for this population, and educational tools appropriate to the developmental and cognitive levels of the participants must be made available. Acknowledgment of the individual's role within the system and understanding of the individual's experience of that systems interaction with the environment and with other systems is primary in developing effective programming which can increase the quality of the participants' interactions and relationships, making life a more productive and more satisfying experience.

The objective of robust portfolio optimization is to find a way to allocate capital to some financial assets such that portfolio return is maximized in the worst-case scenario, which is desirable for investors with a low tolerance for risk. This study aims to apply the robust approach to asset allocation based on 30 of the biggest stocks on the Stockholm Stock Exchange. Three models with different constraints on portfolio return and variance are obtained and solved using the Gurobi Optimizer. The result of any one of the models could be proposed as a low-risk portfolio. The choice between the models is a trade-off between higher expected return and lower variance, and it depends on the individual preferences of the investor.

Addiction has been predominantly viewed through the lens of the individual, thereby leaving the family largely out of the scope of treatment or prevention. Csiernik (2002) calls the family the ‘secondary element’ in addiction treatment. The definitions of addiction and research on the prevalence of use are examples of this narrow, individual focus. This qualitative study sought to widen the lens and explore the family’s experiences of addiction. Families’ voices will be presented and their perspectives captured regarding what would be helpful to them in addiction treatment. This study’s theoretical underpinnings are Family Systems Theory and Social Constructionism. Interviews with the participants were conducted through the use of an open-ended interview process. Interpretive data analysis and phenomenology were used to explore possible themes and meanings to gain a better understanding of the participants’ perspectives regarding addiction. The main finding of this study, based on the testimony of the participants, was that families perceived there to be a need for more clinical and supportive services to deal with the impact of addictions on the family. This study fills a gap in the literature because, though there is ample research on the consequences of addiction for the family, there is very limited research on the family’s perspective regarding what services they require in order to cope with those consequences. The information supplied by the participants of this study will help social workers and treatment centers provide more holistic, family-centered addiction treatment. / Thesis / Master of Social Work (MSW)

This dissertation is a realist intellectual history of systems theory in the second half of the twentieth century. Systems theory can be defined as the study of the informatic patterns that are found within a variety of complex phenomena, both natural and social. The science behind systems theory emerged from wartime engineering projects, and was promoted by major philanthropic organizations such as the Rockefeller Foundation. Theoretical concepts from the nascent systems sciences, including the subfields of information science, cybernetics, and systems biology, migrated into social science fields including political theory and economics. The social applications of systems theory were heavily promoted by major figures within both America's counterculture, and America's neoliberal revolution. Systems theory injected strong elements of political thinking and political reasoning into natural and social scientific fields alike. The integration of systems theory into natural science fields such as biology was paired with an expanded understanding of the purposes of science. These purposes ranged from the attempt to capture sophisticated, systemic mechanisms of control within life processes, to the attempt to describe the spontaneous, creative, and free self-organization within living systems. Likewise, in economics and the social sciences, systems theory provided an apt conceptual terminology to imagine human society as either an intricately interwoven system of control and coercion, or as a spontaneously organizing source of human freedom. Systems approaches to economics rejected simplistic descriptions of human motivation and behavior, and emphasized the importance of collective processes that do not follow central direction. While Friedrich Hayek is the most well-known economist to utilize systems theory, other less known figures such as Kevin Kelly and George Gilder played a major role in the development of systems based, informatic approaches to social and economic thought. Hayek is often blamed for the development of speculative, systems approaches to economics that minimize the importance of material reality. Contradicting this consensus, I argue that Kelly and Gilder are better exemplars of this speculative rejection of materiality. I also challenge the dominant consensus within political theory scholarship that argues that systems theory can only be understood as a tool and modality of control. Instead, I show that freedom and control co-exist ambiguously in systems theory discourses, and that the lasting appeal and uptake of systems theory within American culture must be interpreted in this light. / Doctor of Philosophy / Systems theory describes a body of research that sought to represent the world through the language of the system. Systems theory was applied to diverse contexts, including engineering, biology, psychology, social science, and economics. Systems theorists believed that self-organizing forces could be found in many complex systems, both natural and man-made. Systems theory was a method by which the complexity of these processes could be described and understood. Specifically, systems theory relied on the concept of information. Information was the basic component from which any system was built. For systems theorists, however, information was not simply a unit or isolated measurement. Rather, information could also refer to a pattern or the characteristics of a process. Thus, systems theory was about being able to capture and describe repetitive processes found in the world. Systems theorists were interested in understanding how both natural and social processes could self-regulate themselves, maintain their basic integrity, and change over time. Thus, the emergence of order without centralized direction was a central preoccupation of systems theorists. In this dissertation, I argue that systems theory was more than a scientific theory; it was also a form of political reasoning. At times, systems theory was a way to conceptualize forms of systemic control, coercion, and homogenization. At other times, systems theory became a way to conceptualize how participation in spontaneous processes could support diversity and freedom. I show that systems theorists were divided between such portrayals of control and freedom. Furthermore, control and freedom often coexisted in the language, behavior, and political claims of systems theorists.

Using mathematical models with the purpose to understand and store knowlegde about a system is not a new field in science with early contributions dated back to, e.g., Kepler’s laws of planetary motion. The aim is to obtain such a comprehensive predictive and quantitative knowledge about a phenomenon so that mathematical expressions or models can be used to forecast every relevant detail about that phenomenon. Such models can be used for reducing pollutions from car engines; prevent aviation incidents; or developing new therapeutic drugs. Models used to forecast, or predict, the behavior of a system are refered to predictive models. For such, the estimation problem aims to find one model and is well known and can be handeled by using standard methods for global nonlinear optimization. Descriptive models are used to obtain and store quantitative knowledge of system. Estimation of descriptive models has not been much described by the literature so far; instead the methods used for predictive models have beed applied. Rather than finding one particular model, the parameter estimation for descriptive models aims to find every model that contains descriptive information about the system. Thus, the parameter estimation problem for descriptive models can not be stated as a standard optimization problem. The main objective for this thesis is to propose methods for estimation of descriptive models. This is made by using methods for nonlinear optimization including both new and existing theory.

<p>Using mathematical models with the purpose to understand and store knowlegde about a system is not a new field in science with early contributions dated back to, e.g., Kepler’s laws of planetary motion.</p><p>The aim is to obtain such a comprehensive predictive and quantitative knowledge about a phenomenon so that mathematical expressions or models can be used to forecast every relevant detail about that phenomenon. Such models can be used for reducing pollutions from car engines; prevent aviation incidents; or developing new therapeutic drugs. Models used to forecast, or predict, the behavior of a system are refered to predictive models. For such, the estimation problem aims to find one model and is well known and can be handeled by using standard methods for global nonlinear optimization.</p><p>Descriptive models are used to obtain and store quantitative knowledge of system. Estimation of descriptive models has not been much described by the literature so far; instead the methods used for predictive models have beed applied. Rather than finding one particular model, the parameter estimation for descriptive models aims to find every model that contains descriptive information about the system. Thus, the parameter estimation problem for descriptive models can not be stated as a standard optimization problem.</p><p>The main objective for this thesis is to propose methods for estimation of descriptive models. This is made by using methods for nonlinear optimization including both new and existing theory.</p>

Complex Systems-of-Systems, which form the subject matter of the research presented here, may be considered to be systems that are constituted of several components, each of which could themself be regarded as being a complete system in its own right. These component systems are typically largely managed independently of one another. They each have their own intrinsic goals which they are capable of fulfilling autonomously. These goals are additional to any to which they might contribute as part of the overall System-of-Systems that is being investigated. Systems-of-Systems are epitomised by features such as the prevalence of complex webs of mutual interdependency amongst their component systems, the involvement of a broad diversity of stakeholders and the participation of a number of independent decision-makers, each of whom competes with the others for strictly limited resources. Furthermore, the components of Systems-of-Systems may often be found to be widely scattered across an extensive geographical region. Sometimes such systems may even span global distances. Complex Systems-of-Systems of such a nature would appear to be becoming ever more prevalent in the increasingly interconnected and ever shrinking world which is engendered, in particular, by the proliferation of modern information and communication technology. Systems-of-Systems may arise in both commercial and public sector contexts, hence commercial organisations and governments, alike, confront the daunting challenge of planning, establishing and maintaining novel systems of this type. However, it is to be anticipated that significant difficulties might be encountered in applying existing systems engineering methods, which were designed for dealing with far more monolithic types of system, to the treatment of Systems-of- Systems. Instead, the successful achievement of acceptable resolutions to the various Systems-of-Systems issues and conundrums with which the responsible planners can be expected to be confronted would appear to demand the application of sophisticated distributed decision aids, in order to alleviate the the intolerable burden which the decision-makers would otherwise be forced to endure. Such aids need to be able to take a genuinely fair and unbiased account of the interests of a multitude of stakeholders. At the same time, they must be able to satisfactorily accommodate the enforcement of a range of highly involved and intricate constraints upon the various alternative interventions which might potentially be contemplated. In order to underpin the development of decision aids of the kind demanded, it has been sought to establish some basic theoretical foundations for Systems-of-Systems. This body of theory has then been applied to the identification of the methods which might be most suitable for the treatment of Systems-of-Systems questions. Finally, some decision-support tools which are intended to facilitate the implementation of the methods that have been recommended have been described. Any attempt to dictate a single â??bestâ?? intervention to the decision-makers would generally be totally unacceptable. As a result, the objective which has been pursued has been to seek to filter out and identify a relatively sparing number of what would appear to be the most reasonable alternatives from some much more profuse range of possibilities. These may then be afforded more intensive scrutiny by the pertinent decision-makers.