The Social Complexity of Immigration and Diversity

我们的时代被称为“迁徙时代”。移民是一个重大的政治问题，媒体的报道越来越多，反移民情绪上升，反移民政党崛起。移民问题在关于族裔和宗教多样性及其对社会凝聚力的影响的更广泛辩论中处于核心地位。然而，我们距离理解这些问题及其潜在后果还有很长的路要走。它们似乎建立在关于国家认同和种族的信念上，但不能脱离社会阶级、教育、经济竞争和不平等的影响，以及地理和社会隔离、社会结构和制度的影响。这个项目将把社会科学和复杂性科学这两个非常不同的学科结合起来，以获得对这些复杂的社会问题的新理解。它将通过建立这些社会过程的一系列计算机模拟模型来实现这一点。人们可能会认为这些是严肃的模拟人生计划，追踪许多人之间的社会互动。这种模拟允许进行“假设”实验，以便基于许多个人的相互作用，对整个社会可能的结果建立更深层次的理解。复杂系统的计算机模拟的一个困难是，如果将它们变得逼真(在人们实际行为的意义上)，它就变得非常复杂，这使得模拟很难理解，而如果它们足够简单，可以理解它们可能太抽象，对真实的人来说没有任何有用的意义。这个项目旨在通过建立相关模型链来绕过这个问题，从一个复杂的“描述性”模型开始，然后分阶段简化，这样每个模拟都是下面一个模拟的一个模型。较简单的模型帮助我们了解较复杂的模型中发生了什么。更复杂的模型揭示了简单模型在哪些方面是准确的，以及它们过度简化的方式。通过这种方式，该项目将把社会科学的相关性与硬科学的严谨性结合起来，但代价是必须建立、检查和维护整个模型链。该项目建立在曼彻斯特社会科学家和复杂性科学家之间已建立的合作基础上，该项目将整合这两个学科，为政策制定者及其顾问提供新的见解、技术和方法。然而，这将需要复杂性和社会科学家开发新的技术。复杂性科学家将开发新的计算机模型家族，在一个模拟中捕捉社会的几个方面，包括：不同群体、出身、阶级等的成员资格如何由人们发出信号(例如他们的着装方式或态度)；同时属于几个不同的社会群体的利弊；不同但平行的社会网络可能相互关联；以及人们对特定问题的看法可能如何随着他们的朋友、更广泛的群体甚至政客的反应而改变。社会科学家将开发方法，将这些类型的模型与可用的丰富社会数据来源联系起来，并在这些来源被证明不充分的情况下收集额外的社会数据。他们还将确保对建模结果进行有意义和有用的解释，特别是确保它们不被过度解释。通过将社会科学证据、模拟模型层层和研究人员的综合专业知识结合在一起，该项目旨在在理解围绕移民和多样性对社会凝聚力和融合的影响的过程的复杂、重要但敏感的问题方面取得真正进展。从一开始，它将让政策专家和决策者帮助指导该项目并确保其相关性。

Ours has been dubbed the 'age of migration'. Immigration is a major political issue, with increasing media coverage, rising anti-immigration sentiment and the rise of anti-immigration political parties. The issue of migration sits centrally within the wider debate about ethnic and religious diversity and its effects on social cohesion. We are still, though, a long way from understanding these issues and their potential consequences. They seem to rest on beliefs about national identity and ethnicity, but cannot be divorced from the effects of social class, education, economic competition and inequality, as well as the influences of geographical and social segregation, social structures and institutions.This project will integrate the two very different disciplines, social science and complexity science, in order to gain new understanding of these complex, social issues. It will do this by building a series of computer simulation models of these social processes. One could think these as Serious Sims programmes that track the social interactions between many individuals. Such simulations allow 'what if' experiments to be performed so that a deeper understanding of the possible outcomes for the society as a whole can be established based on the interactions of many individuals. A difficulty with the computer simulation of complex systems is that if they are made realistic (in the sense of how people actually behave) it becomes very complex, which makes the simulation hard to understand, whilst if they are made simple enough to understand they can be too abstract to mean anything useful in terms of real people. This project aims to get around this by making chains of related models, starting with a complex, 'descriptive' model and then simplifying in stages, so that each simulation is a model of the one below it. The simpler models help us understand what is going on in the more complex ones. The more complex models reveal in what ways the simpler ones are accurate as well as the ways they over-simplify. In this way this project will combine the relevance of social science with the rigour of the hard sciences, but at the cost of having to build, check and maintain whole chains of models.Building on an established collaboration between social and complexity scientists in Manchester, this project will integrate the two disciplines to produce new insights, techniques and approaches for policy makers and their advisors. However this will require both the complexity and social scientists to develop new techniques. The complexity scientists will develop new families of computer models that capture several aspects of society in one simulation, including: how the membership of different groups, origins, classes, etc. are signalled by people (e.g. the way they dress, or their attitudes); the advantages and disadvantages of belonging to several different social groups at the same time; how different but parallel social networks might relate to each other; and how the views of people on specific issues might change in response to their friends, wider group and even politicians. The social scientists will develop ways of relating these kinds of models to the rich sources of social data that are available, and will collect additional social data where these sources prove inadequate. They will also ensure that the modelling results are interpreted meaningfully and usefully, in particular in ensuring that they are not over-interpreted. By bringing together the social science evidence, the layers of simulation models and the combined expertise of the researchers this project aims to make real progress in understanding the complex, important yet sensitive issues surrounding the processes that underlie the effects of immigration and diversity on social cohesion and integration. From the beginning it will involve policy experts and decision makers to help guide the project and ensure its relevance.