Academic literature on the topic 'Statics and dynamics (Social sciences) – Mathematical models'
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Journal articles on the topic "Statics and dynamics (Social sciences) – Mathematical models"
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WEIDLICH, WOLFGANG. "SOCIODYNAMICS — A SYSTEMATIC APPROACH TO MATHEMATICAL MODELLING IN THE SOCIAL SCIENCES." Fluctuation and Noise Letters 03, no. 02 (June 2003): L223—L232. http://dx.doi.org/10.1142/s0219477503001294.
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A general concept is presented which allows of setting up mathematical models for stochastic and quasi deterministic dynamic processes in social systems. The basis of this concept is the master equation for the probability distribution over appropriately chosen personal and material macrovariables of the society. The probabilistic transition rates depend on motivation potentials governing the decisions and actions of the social agents. The transition from the probability distribution to quasi-meanvalues leads to in general nonlinear coupled differential equations for the macrovariables of the chosen social sector. Up to now several models about population dynamics, collective political opinion formation, dynamics of economic processes and the formation of settlements have been published.
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Xia, Haoxiang, Huili Wang, and Zhaoguo Xuan. "Opinion Dynamics." International Journal of Knowledge and Systems Science 2, no. 4 (October 2011): 72–91. http://dx.doi.org/10.4018/jkss.2011100106.
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As a key sub-field of social dynamics and sociophysics, opinion dynamics utilizes mathematical and physical models and the agent-based computational modeling tools, to investigate the spreading of opinions in a collection of human beings. This research field stems from various disciplines in social sciences, especially the social influence models developed in social psychology and sociology. A multidisciplinary review is given in this paper, attempting to keep track of the historical development of the field and to shed light on its future directions. In the review, the authors discuss the disciplinary origins of opinion dynamics, showing that the combination of the social processes, which are conventionally studied in social sciences, and the analytical and computational tools, which are developed in mathematics, physics and complex system studies, gives birth to the interdisciplinary field of opinion dynamics. The current state of the art of opinion dynamics is then overviewed, with the research progresses on the typical models like the voter model, the Sznajd model, the culture dissemination model, and the bounded confidence model being highlighted. Correspondingly, the future directions of this academic field are envisioned, with an advocation for closer synthesis of the related disciplines.
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Liebovitch, Larry S., Peter T. Coleman, and Joshua Fisher. "Approaches to Understanding Sustainable Peace: Qualitative Causal Loop Diagrams and Quantitative Mathematical Models." American Behavioral Scientist 64, no. 2 (July 4, 2019): 123–44. http://dx.doi.org/10.1177/0002764219859618.
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Scholarly research on peace has overwhelmingly focused on negative peace, or the absence of conflict, aggression, violence, and war. We seek to understand holistic peace systems, the political, economic, and social systems that sustain peaceful societies. We show how two methods can help us understand the properties and dynamics of such complex peace systems. Each method provides insights from different perspectives to help understand sustaining peace. The causal loop diagram helps us to identify the peace factors and the connections between them. The mathematical model helps us determine the quantitative results of the interactions between all the peace factors. Using these methods, we found that there is no single “leverage” factor that is the lynchpin in creating sustainable peace. Rather, the small effects of a large number of positive peace factors that support peace can collectively overcome the stronger emotional response to the negative conflict factors that jeopardize peace.
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SOBKOWICZ, PAWEL. "STUDIES OF OPINION STABILITY FOR SMALL DYNAMIC NETWORKS WITH OPPORTUNISTIC AGENTS." International Journal of Modern Physics C 20, no. 10 (October 2009): 1645–62. http://dx.doi.org/10.1142/s0129183109014655.
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There are numerous examples of societies with extremely stable mix of contrasting opinions. We argue that this stability is a result of an interplay between society network topology adjustment and opinion changing processes. To support this position we present a computer model of opinion formation based on some novel assumptions, designed to bring the model closer to social reality. In our model, the agents, in addition to changing their opinions due to influence of the rest of society and external propaganda, have the ability to modify their social network, forming links with agents sharing the same opinions and cutting the links with those they disagree with. To improve the model further we divide the agents into "fanatics" and "opportunists," depending on how easy it is to change their opinions. The simulations show significant differences compared to traditional models, where network links are static. In particular, for the dynamical model where inter-agent links are adjustable, the final network structure and opinion distribution is shown to resemble real world observations, such as social structures and persistence of minority groups even when most of the society is against them and the propaganda is strong.
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Delgadillo-Aleman, Sandra, Roberto Ku-Carrillo, Brenda Perez-Amezcua, and Benito Chen-Charpentier. "A Mathematical Model for Intimate Partner Violence." Mathematical and Computational Applications 24, no. 1 (March 2, 2019): 29. http://dx.doi.org/10.3390/mca24010029.
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In the context of mathematical models applied to social sciences, we present and analyze a model based on differential equations for the intimate partner violence (IPV). Such a model describes the dynamics of a heterosexual romantic couple in which the man perpetrates violence against the woman. We focus on incorporating different key factors reported in the literature as causal or motivational factors to perpetrate IPV. Among the main factors included are the failures in self-regulation, the man’s need to control the woman, the social pressure on the woman to remain married, and empowerment programs. Another aspect that we include is periodic alcohol consumption for the man. The discussion of the model includes a stability analysis of its equilibrium points and the asymptotic behavior of its solutions. Also, the interpretation of results is presented in terms of IPV phenomenon. Finally, a brief review is given on different scales to quantify human behavioral traits and numerical simulations for some IPV scenarios.
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Oraby, Tamer, Vivek Thampi, and Chris T. Bauch. "The influence of social norms on the dynamics of vaccinating behaviour for paediatric infectious diseases." Proceedings of the Royal Society B: Biological Sciences 281, no. 1780 (April 7, 2014): 20133172. http://dx.doi.org/10.1098/rspb.2013.3172.
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Mathematical models that couple disease dynamics and vaccinating behaviour often assume that the incentive to vaccinate disappears if disease prevalence is zero. Hence, they predict that vaccine refusal should be the rule, and elimination should be difficult or impossible. In reality, countries with non-mandatory vaccination policies have usually been able to maintain elimination or very low incidence of paediatric infectious diseases for long periods of time. Here, we show that including injunctive social norms can reconcile such behaviour-incidence models to observations. Adding social norms to a coupled behaviour-incidence model enables the model to better explain pertussis vaccine uptake and disease dynamics in the UK from 1967 to 2010, in both the vaccine-scare years and the years of high vaccine coverage. The model also illustrates how a vaccine scare can perpetuate suboptimal vaccine coverage long after perceived risk has returned to baseline, pre-vaccine-scare levels. However, at other model parameter values, social norms can perpetuate depressed vaccine coverage during a vaccine scare well beyond the time when the population's baseline vaccine risk perception returns to pre-scare levels. Social norms can strongly suppress vaccine uptake despite frequent outbreaks, as observed in some small communities. Significant portions of the parameter space also exhibit bistability, meaning long-term outcomes depend on the initial conditions. Depending on the context, social norms can either support or hinder immunization goals.
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Williams, John R., and Roy M. Anderson. "Mathematical Models of the Transmission Dynamics of Human Immunodeficiency Virus in England and Wales: Mixing Between Different Risk Groups." Journal of the Royal Statistical Society. Series A (Statistics in Society) 157, no. 1 (1994): 69. http://dx.doi.org/10.2307/2983506.
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Wodarz, Dominik, Shaun Stipp, David Hirshleifer, and Natalia L. Komarova. "Evolutionary dynamics of culturally transmitted, fertility-reducing traits." Proceedings of the Royal Society B: Biological Sciences 287, no. 1925 (April 15, 2020): 20192468. http://dx.doi.org/10.1098/rspb.2019.2468.
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Human populations in many countries have undergone a phase of demographic transition, characterized by a major reduction in fertility at a time of increased resource availability. A key stylized fact is that the reduction in fertility is preceded by a reduction in mortality and a consequent increase in population density. Various theories have been proposed to account for the demographic transition process, including maladaptation, increased parental investment in fewer offspring, and cultural evolution. None of these approaches, including formal cultural evolutionary models of the demographic transitions, have addressed a possible direct causal relationship between a reduction in mortality and the subsequent decline in fertility. We provide mathematical models in which low mortality favours the cultural selection of low-fertility traits. This occurs because reduced mortality slows turnover in the model, which allows the cultural transmission advantage of low-fertility traits to outrace their reproductive disadvantage. For mortality to be a crucial determinant of outcome, a cultural transmission bias is required where slow reproducers exert higher social influence. Computer simulations of our models that allow for exogenous variation in the death rate can reproduce the central features of the demographic transition process, including substantial reductions in fertility within only one to three generations. A model assuming continuous evolution of reproduction rates through imitation errors predicts fertility to fall below replacement levels if death rates are sufficiently low. This can potentially explain the very low preferred family sizes in Western Europe.
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GONZÁLEZ-PARRA, GILBERTO, ABRAHAM J. ARENAS, and F. J. SANTONJA. "STOCHASTIC MODELING WITH MONTE CARLO OF OBESITY POPULATION." Journal of Biological Systems 18, no. 01 (March 2010): 93–108. http://dx.doi.org/10.1142/s0218339010003159.
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In this paper, we investigate the dynamics of a mathematical model of obesity population within fluctuating social environment. A stochastic differential equation model is constructed by perturbing two social related parameters of the deterministic model with white noise terms characterized by Gaussian distribution having zero mean and unit spectral density. In order to compute the numerical solution of the stochastic models Euler-Maruyama numerical method is used. Confidence intervals for the overweight and obesity childhood population are computed using Monte Carlo method. Analysis of the numerical results reveals that small perturbations on the parameters are not a major driving force for dynamical transitions from the underlying deterministic model. In addition, numerical results indicate a close relationship between the amplitude of the fluctuation of the social environment parameters and the variability of forecasts for the incidence of the obesity in the population.
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Xue, Yiran, Rui Wu, Jiafeng Liu, and Xianglong Tang. "Crowd Evacuation Guidance Based on Combined Action Reinforcement Learning." Algorithms 14, no. 1 (January 18, 2021): 26. http://dx.doi.org/10.3390/a14010026.
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Existing crowd evacuation guidance systems require the manual design of models and input parameters, incurring a significant workload and a potential for errors. This paper proposed an end-to-end intelligent evacuation guidance method based on deep reinforcement learning, and designed an interactive simulation environment based on the social force model. The agent could automatically learn a scene model and path planning strategy with only scene images as input, and directly output dynamic signage information. Aiming to solve the “dimension disaster” phenomenon of the deep Q network (DQN) algorithm in crowd evacuation, this paper proposed a combined action-space DQN (CA-DQN) algorithm that grouped Q network output layer nodes according to action dimensions, which significantly reduced the network complexity and improved system practicality in complex scenes. In this paper, the evacuation guidance system is defined as a reinforcement learning agent and implemented by the CA-DQN method, which provides a novel approach for the evacuation guidance problem. The experiments demonstrate that the proposed method is superior to the static guidance method, and on par with the manually designed model method.
Dissertations / Theses on the topic "Statics and dynamics (Social sciences) – Mathematical models"
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Verdy, Ariane. "Dynamics of marine zooplankton : social behavior, ecological interactions, and physically-induced variability." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/43158.
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Thesis (Ph. D.)--Joint Program in Physical Oceanography (Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution), 2008.Includes bibliographical references (p. [221]-232).
Marine ecosystems reflect the physical structure of their environment and the biological processes they carry out. This leads to spatial heterogeneity and temporal variability, some of which is imposed externally and some of which emerges from the ecological mechanisms themselves. The main focus of this thesis is on the formation of spatial patterns in the distribution of zooplankton arising from social interactions between individuals. In the Southern Ocean, krill often assemble in swarms and schools, the dynamics of which have important ecological consequences. Mathematical and numerical models are employed to study the interplay of biological and physical processes that contribute to the observed patchiness. The evolution of social behavior is simulated in a theoretical framework that includes zooplankton population dynamics, swimming behavior, and some aspects of the variability inherent to fluid environments. First, I formulate a model of resource utilization by a stage-structured predator population with density-dependent reproduction. Second, I incorporate the predator-prey dynamics into a spatially-explicit model, in which aggregations develop spontaneously as a result of linear instability of the uniform distribution. In this idealized ecosystem, benefits related to the local abundance of mates are offset by the cost of having to share resources with other group members. Third, I derive a weakly nonlinear approximation for the steady-state distributions of predator and prey biomass that captures the spatial patterns driven by social tendencies. Fourth, I simulate the schooling behavior of zooplankton in a variable environment; when turbulent flows generate patchiness in the resource field, schools can forage more efficiently than individuals.
(cont.) Taken together, these chapters demonstrate that aggregation/ schooling can indeed be the favored behavior when (i) reproduction (or other survival measures) increases with density in part of the range and (ii) mixing of prey into patches is rapid enough to offset the depletion. In the final two chapters, I consider sources of temporal variability in marine ecosystems. External perturbations amplified by nonlinear ecological interactions induce transient ex-cursions away from equilibrium; in predator-prey dynamics the amplitude and duration of these transients are controlled by biological processes such as growth and mortality. In the Southern Ocean, large-scale winds associated with ENSO and the Southern Annular Mode cause convective mixing, which in turn drives air-sea fluxes of carbon dioxide and oxygen. Whether driven by stochastic fluctuations or by climatic phenomena, variability of the biogeochemical/physical environment has implications for ecosystem dynamics.
by Ariane Verdy.
Ph.D.
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Schwartz, Carmit M. Economics Australian School of Business UNSW. "Individuals' responses to changes in risk: a person-specific analysis." 2007. http://handle.unsw.edu.au/1959.4/40575.
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In this thesis we consider two comparative statics questions of changes in risk. The first question concerns situations where an individual faces some risk and has no control over the uncertain environment. In these situations we ask what kind of changes in risk will cause the individual's expected utility to increase. The second comparative statics question concerns situations where an individual faces some risk and has some control over the uncertain environment. In particular, we consider situations where the individual maximizes her expected utility with respect to some control parameter. Here we ask what kind of changes in risk will cause the individual's optimal value of the control parameter to increase. The existing literature has answered these questions for a class of individuals (for example, the class of risk averse individuals). This thesis differs from existing literature as it focuses on a given individual, and thus reveals some of the person-specific factors that affect individual?s responses to changes in risk. The aim of the thesis is to show how an order on distributions, termed single crossing likelihood ratio (SCLR) order, can intuitively answer both questions for a given individual. The main contributions of the thesis are as follows. First, the thesis presents the SCLR order and its main properties. Second, the thesis shows that the SCLR order can answer the above comparative statics questions in an intuitive way. In particular, the thesis shows that the answer to the above questions, with the use of the SCLR order, depends on a risk reference point which can be interpreted as a "certainty equivalent" point. Thus it is demonstrated that individual's responses to changes in risk are affected by her "certainty equivalent" point. Lastly, the results of the thesis can be used to provide an intuitive explanation of related existing results that were obtained for a class of individuals.
Books on the topic "Statics and dynamics (Social sciences) – Mathematical models"
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Creedy, John. Statics and dynamics of income distribution in New Zealand. Wellington, N.Z: Institute of Policy Studies, Victoria University of Wellington, 1997.
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Gandolfo, Giancarlo. Economic dynamics. 3rd ed. Berlin: Springer, 1996.
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Economic dynamics. Berlin: Springer Verlag, 1997.
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Economic dynamics: Theory and computation. Cambridge, MA: MIT Press, 2009.
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András, Simonovits. Mathematical methods in dynamic economics. New York: St. Martin's Press, 2000.
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András, Simonovits. Mathematical methods in dynamic economics. Basingstoke: Macmillan, 2000.
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M, Guillermo L. Gómez. Dynamic probabilistic models and social structure: Essays on socioeconomic continuity. Dordrecht: Kluwer Academic Publishers, 1992.
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Norbert, Müller. Civilization dynamics. Aldershot, Hants, England: Avebury, 1989.
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Gandolfo, Giancarlo. Economic dynamics. 4th ed. Heidelberg: Springer, 2009.
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V, Evstigneev I., Medova E. A, and Dempster, M. A. H. 1938-, eds. Stochastic models of control and economic dynamics. London: Academic Press, 1987.
Find full textBook chapters on the topic "Statics and dynamics (Social sciences) – Mathematical models"
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Bischi, Gian-Italo, and Ugo Merlone. "Global dynamics in adaptive models of collective choice with social influence." In Mathematical Modeling of Collective Behavior in Socio-Economic and Life Sciences, 223–44. Boston: Birkhäuser Boston, 2010. http://dx.doi.org/10.1007/978-0-8176-4946-3_9.
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Xia, Haoxiang, Huili Wang, and Zhaoguo Xuan. "Opinion Dynamics." In Multidisciplinary Studies in Knowledge and Systems Science, 311–32. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-3998-0.ch021.
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As a key sub-field of social dynamics and sociophysics, opinion dynamics utilizes mathematical and physical models and the agent-based computational modeling tools, to investigate the spreading of opinions in a collection of human beings. This research field stems from various disciplines in social sciences, especially the social influence models developed in social psychology and sociology. A multidisciplinary review is given in this paper, attempting to keep track of the historical development of the field and to shed light on its future directions. In the review, the authors discuss the disciplinary origins of opinion dynamics, showing that the combination of the social processes, which are conventionally studied in social sciences, and the analytical and computational tools, which are developed in mathematics, physics and complex system studies, gives birth to the interdisciplinary field of opinion dynamics. The current state of the art of opinion dynamics is then overviewed, with the research progresses on the typical models like the voter model, the Sznajd model, the culture dissemination model, and the bounded confidence model being highlighted. Correspondingly, the future directions of this academic field are envisioned, with an advocation for closer synthesis of the related disciplines.
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Pepper, John W., and Barbara B. Smuts. "The Evolution of Cooperation in an Ecological Context : An Agent-Based Model." In Dynamics in Human and Primate Societies. Oxford University Press, 2000. http://dx.doi.org/10.1093/oso/9780195131673.003.0008.
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The social and behavioral sciences have a long-standing interest in the factors that foster selfish (or individualistic) versus altruistic (or cooperative) behavior. Since the 1960s, evolutionary biologists have also devoted considerable attention to this issue. In the last 25 years, mathematical models (reviewed in Wilson and Sober 1994) have shown that, under particular demographic conditions, natural selection can favor traits that benefit group members as a whole, even when the bearers of those traits experience reduced reproductive success relative to other members of their group. This process, often referred to as "trait group selection" (D. S. Wilson 1975) can occur when the population consists of numerous, relatively small "trait groups," defined as collections of individuals who influence one another's fitness as a result of the trait in question. For example, consider a cooperative trait such as alarm calling, which benefits only individuals near the alarm caller. A trait group would include all individuals whose fitness depends on whether or not a given individual gives an alarm call. If the cooperative trait confers sufficiently large reproductive benefits on the average group member, it can spread. This is because trait groups that happen to include a large proportion of cooperators will send out many more offspring into the population as a whole than will groups containing few, or no cooperators. Thus, even though noncooperators out reproduce cooperators within trait groups (because they experience the benefits of the presence of cooperators without incurring the costs), this advantage can be offset by differences in rates of reproduction between trait groups. Numerous models of group selection (Wilson and Sober 1994) show that whether cooperative traits can spread depends on the relative magnitude of fitness effects at these two levels of selection (within and between trait groups). In addition, there is a growing body of empirical evidence for the operation of group selection in nature (e.g., Colwell 1981; Breden and Wade 1989; Bourke and Pranks 1995; Stevens et al. 1995; Seeley 1996; Miralles et al. 1997; Brookfield 1998) and under experimental conditions (reviewed in Goodnight and Stevens 1997).
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Monge, Peter R., and Noshir Contractor. "Computational Modeling of Networks." In Theories of Communication Networks. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195160369.003.0010.
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Computer simulations have long been used as an effective tool in engineering, economics, psychology, and a number of other social sciences. Engineers typically use simulations to predict performance of a system that has known dynamic characteristics. These characteristics are typically obtained from theory and are then articulated in the simulation as difference or differential equations. The goal of engineering simulation is then to assess the dynamic performance of a system based on a priori knowledge of the dynamic relationships among the various elements of the system. Forrester (1961, 1973) was one of the earliest and most influential advocates of simulation modeling of dynamic social systems. Forrester advocated this approach as a way to model and assess the dynamics of industrial and world phenomena. Sterman (2000) provides a recent review of research on dynamics simulation from this tradition. While this approach has produced a considerable number of studies, it too is based on the assumption that the researcher has a priori knowledge of the dynamic relationships among elements of the system. Indeed, many of the results of these models have been criticized for specifying relationships that were at best untested and at worst flawed. In response to these criticisms, more recent interest has focused on redefining the utility of simulations in the social sciences. Rather than using simulations to test the long-term dynamics of systems with known interrelationships, theorists (Carley & Prietula, 1994; Contractor, 1994; Hanneman, 1988) have suggested that social scientists should use simulations to help construct theory, to identify the heretofore-unknown interrelationships. This section describes the traditional use of computer simulations as well as the adaptation of this approach toward theory construction and testing in the social sciences. Later sections will apply these general approaches to the computational modeling of networks in particular. Carley and Prietula (1994) suggest that the emergence of the new field of computational organizational theory (COT) signals the growing interest in the construction of computational models to augment and assist theory building. Most social science theories are richly evocative but highly abbreviated (Poole, 1997), that is, they offer explanations that suggest complex interrelationships but do not provide precise, falsifiable mathematical formalizations of the theory.
Reports on the topic "Statics and dynamics (Social sciences) – Mathematical models"
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Tucker-Blackmon, Angelicque. Engagement in Engineering Pathways “E-PATH” An Initiative to Retain Non-Traditional Students in Engineering Year Three Summative External Evaluation Report. Innovative Learning Center, LLC, July 2020. http://dx.doi.org/10.52012/tyob9090.
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The summative external evaluation report described the program's impact on faculty and students participating in recitation sessions and active teaching professional development sessions over two years. Student persistence and retention in engineering courses continue to be a challenge in undergraduate education, especially for students underrepresented in engineering disciplines. The program's goal was to use peer-facilitated instruction in core engineering courses known to have high attrition rates to retain underrepresented students, especially women, in engineering to diversify and broaden engineering participation. Knowledge generated around using peer-facilitated instruction at two-year colleges can improve underrepresented students' success and participation in engineering across a broad range of institutions. Students in the program participated in peer-facilitated recitation sessions linked to fundamental engineering courses, such as engineering analysis, statics, and dynamics. These courses have the highest failure rate among women and underrepresented minority students. As a mixed-methods evaluation study, student engagement was measured as students' comfort with asking questions, collaboration with peers, and applying mathematics concepts. SPSS was used to analyze pre-and post-surveys for statistical significance. Qualitative data were collected through classroom observations and focus group sessions with recitation leaders. Semi-structured interviews were conducted with faculty members and students to understand their experiences in the program. Findings revealed that women students had marginalization and intimidation perceptions primarily from courses with significantly more men than women. However, they shared numerous strategies that could support them towards success through the engineering pathway. Women and underrepresented students perceived that they did not have a network of peers and faculty as role models to identify within engineering disciplines. The recitation sessions had a positive social impact on Hispanic women. As opportunities to collaborate increased, Hispanic womens' social engagement was expected to increase. This social engagement level has already been predicted to increase women students' persistence and retention in engineering and result in them not leaving the engineering pathway. An analysis of quantitative survey data from students in the three engineering courses revealed a significant effect of race and ethnicity for comfort in asking questions in class, collaborating with peers outside the classroom, and applying mathematical concepts. Further examination of this effect for comfort with asking questions in class revealed that comfort asking questions was driven by one or two extreme post-test scores of Asian students. A follow-up ANOVA for this item revealed that Asian women reported feeling excluded in the classroom. However, it was difficult to determine whether these differences are stable given the small sample size for students identifying as Asian. Furthermore, gender differences were significant for comfort in communicating with professors and peers. Overall, women reported less comfort communicating with their professors than men. Results from student metrics will inform faculty professional development efforts to increase faculty support and maximize student engagement, persistence, and retention in engineering courses at community colleges. Summative results from this project could inform the national STEM community about recitation support to further improve undergraduate engineering learning and educational research.