Dynamic Social Models Research Articles

Educação em saúde: uma visão desde antropologia

Objetivo: Com base na revisão da literatura de 577 artigos dos mais altos revistas de impacto na área da saúde, presentes no banco de dados Biblioteca Virtual em Saúde (lilacs, Scielo, entre outros) y PubMed, diferentes ênfases e as tendências teóricas em mostras de discussão relacionados com a saúde doença-cultura. Desenvolvimiento: Estas tendências surgem a partir da interacção de um número de elementos complexos, mediada pelas características do indivíduo, compreendendo-a a partir de uma perspectiva antropológica. A partir do trabalho desenvolvido por Canguilhem para interpretação; os modelos sociais ontológicas e dinâmicas são descritos. Além disso, a situação sócio-política como condição da doença ea forma como eles levou o conceito sociológico mencionado. A seguir, algumas tendências contemporâneas são descritos com base na perspectiva interpretativa da antropologia médica, enfatizando o desenvolvimento dos conceitos de saúde, doença e cultura. Conclusões: No final, ele encontrou um fato determinante que um monte de ações de educação em saúde, enfatizar a importância de explorar as crenças e práticas culturais em relação à saúde. Este item torna-se um ponto de partida para investigações levantadas através do eixo-doença-cultura de saúde.

A probabilistic estimation and prediction technique for dynamic continuous social science models: The evolution of the attitude of the Basque Country population towards ETA as a case study

In this paper, a computational technique to deal with uncertainty in dynamic continuous models in Social Sciences is presented. Considering data from surveys, the method consists of determining the probability distribution of the survey output and this allows to sample data and fit the model to the sampled data using a goodness-of-fit criterion based on the χ2-test. Taking the fitted parameters that were not rejected by the χ2-test, substituting them into the model and computing their outputs, 95% confidence intervals in each time instant capturing the uncertainty of the survey data (probabilistic estimation) is built. Using the same set of obtained model parameters, a prediction over the next few years with 95% confidence intervals (probabilistic prediction) is also provided. This technique is applied to a dynamic social model describing the evolution of the attitude of the Basque Country population towards the revolutionary organisation ETA.

Understanding the Future of Change Agency in Sustainability Through Cellular Automata Scenarios: The Role of Timing †

One of the main interdisciplinary challenges today is to understand and change the dominant social perceptions and values that support and perpetuate unsustainable practices. Social computational simulations have been conceived in recent years to understand emergent results from complex systems. These dynamic social models are of interest to sustainability researchers because they provide a means to implement hypotheses and explore scenarios that could help extend our understanding of the future role of change agency in society. Change agents are individuals who directly or indirectly enable sustainable behaviors or inhibit practices that damage the environment and large social groups. Evidence-based strategies, guidelines and methods are necessary in order to manage creative change agency more effectively. This paper presents work with computational simulations, known as cellular automata, in order to explore the role of timing in triggering social change through uncoordinated, autonomous individual action. The paper identifies a number of issues related to creative change agency and proposes associated guidelines for practitioners. As a means of early validation, these findings are portrayed against empirical studies in the literature.