Agent-Based Models of In-Group Favoritism and Out-Group Hostility

基于主体的群体内偏袒和群体外敌意模型

基本信息

项目摘要

This project uses agent-based models to develop a deeper understanding of fundamental aspects of in-group favoritism and out-group hostility, in all their manifestations including ethnocentrism, ethnic conflict, and discrimination based on factors such as skin color, religion or national origin. The importance of these problems is manifest. In the US, racial discrimination is a major cause of economic inequality. At the global level, ethnic conflict is endemic, with almost one hundred ethnic conflicts active at the same time. Previous models have assumed that the existence and membership of groups are fixed, and that shared membership entails partiality. The agent-based models in this project are able to drop these restrictive assumptions, and thereby allow the investigation of how individuals form their social identity, how in-groups become coherent, and why perceived similarity often becomes the basis of favoritism. Agent-based modeling starts with specific assumptions about individuals (called agents), how they interact, and how the population changes over time. An agent-based model is run as a computer simulation to generate artificial histories. The artificial histories are then analyzed to see what happens over time and why. In this project, the models emphasize simplicity for the sake of insight, rather than try for a completely accurate depiction of any one case. The project is built on the premise that every person has some observable and relatively stable characteristics such as skin color, language, and religion. These characteristics can then be used by someone else to determine whether that person will be treated as one of "us" or one of "them". The first model is designed to investigate (1) the conditions under which in-group favoritism is likely to arise and persist, (2) why hostility between ethnic groups is so common, (3) what are the likely effects of making discrimination more costly, and (4) how settlement patterns can affect tolerance for immigrants. A more advanced model, called the Multi-Trait Model, is used to investigate (1) why some characteristics are emphasized more than others in discrimination, (2) what social categories agents tend to emphasize in drawing boundaries between groups, and (3) what temporary interventions can have lasting beneficial effects on tolerance, cooperation, and equality, even in a world with scarce resources. The project uses facts, concepts and theories from a broad range of social science disciplines, especially political science and sociology. The project also draws on concepts and theories from evolutionary biology and computer science. The findings provide new opportunities for interdisciplinary research, new perspectives for analyzing in-group/out-group dynamics, and new theoretically grounded hypotheses for later empirical testing. The broader impacts for society will be twofold. 1. The insights from the theoretical models will provide a sounder basis on which to make public policies to prevent, inhibit or correct the problems caused by in-group favoritism and out-group hostility. While a theoretical model can never by itself provide useful guidance, the insights of a simple formal model can be helpful to both analysts and policy makers in providing a framework in which to ask potentially fruitful questions. In particular, the results will suggest new ways of thinking about how limited resources might be most effectively focused to reduce discrimination, lessen social tensions from immigration, increase tolerance through targeted education, and intervene in ethnic conflicts. 2. The project will integrate teaching and research by providing a web site for students in high school through graduate school. The web site will have all the resources needed for a student with little mathematical training to run agent-based models to explore the dynamics of in-group favoritism and out-group hostility. Students and researchers will also be able to modify the Java source code to conduct new experiments of their own design, and to see QuickTime movies showing how their population evolves over time and space. The web site will also include archived data, suggested exercises for students, and a list of unsolved problems.
该项目使用基于代理的模型,以更深入地了解群体内偏袒和群体外敌意的基本方面,包括种族中心主义,种族冲突和基于肤色,宗教或民族血统等因素的歧视。 这些问题的重要性是显而易见的。在美国,种族歧视是经济不平等的主要原因。在全球一级,族裔冲突是地方性的,几乎有一百个族裔冲突同时发生。 以前的模型假设群体的存在和成员是固定的,共享成员会导致不确定性。 在这个项目中,基于代理的模型能够放弃这些限制性的假设,从而允许调查个人如何形成他们的社会身份,如何在群体变得连贯,以及为什么感知的相似性往往成为偏袒的基础。 基于代理的建模从关于个体(称为代理)的特定假设开始,它们如何交互,以及人口如何随时间变化。 一个基于代理的模型作为计算机模拟运行,以生成人工历史。 然后分析人工历史,看看随着时间的推移会发生什么以及为什么。 在这个项目中,模型强调简单性,而不是试图完全准确地描述任何一个案例。 该项目的前提是每个人都有一些可观察的和相对稳定的特征,如肤色,语言和宗教。然后,其他人可以使用这些特征来确定该人是否会被视为“我们”或“他们”中的一员。 第一个模型的目的是调查(1)群体内偏袒可能出现和持续的条件,(2)为什么种族群体之间的敌意如此普遍,(3)使歧视更昂贵的可能影响是什么,以及(4)定居模式如何影响对移民的容忍。一个更先进的模型,称为多特质模型,用于调查(1)为什么在歧视中某些特征比其他特征更受重视,(2)在划分群体之间的界限时,代理人倾向于强调哪些社会类别,以及(3)即使在资源稀缺的世界中,什么临时干预措施也可以对宽容,合作和平等产生持久的有益影响。 该项目使用来自广泛的社会科学学科,特别是政治学和社会学的事实,概念和理论。 该项目还借鉴了进化生物学和计算机科学的概念和理论。这些发现为跨学科研究提供了新的机会,为分析组内/组外动态提供了新的视角,并为后来的实证检验提供了新的理论基础假设。 对社会的更广泛影响将是双重的。 1. 从理论模型中获得的启示将为制定公共政策提供更坚实的基础,以预防、抑制或纠正由群体内偏袒和群体外敌意所造成的问题。 虽然理论模型本身永远不能提供有用的指导,但一个简单的正式模型的见解可以帮助分析师和政策制定者提供一个框架,提出可能富有成效的问题。 特别是,研究结果将提出新的思考方式,即如何最有效地集中有限的资源,以减少歧视,减轻移民带来的社会紧张局势,通过有针对性的教育提高容忍度,并干预种族冲突。 2. 该项目将通过为高中到研究生院的学生提供一个网站来整合教学和研究。该网站将为几乎没有数学训练的学生提供运行基于代理的模型所需的所有资源,以探索内群体偏袒和外群体敌意的动态。学生和研究人员还将能够修改Java源代码,以进行自己设计的新实验,并观看QuickTime电影,展示其人口如何随时间和空间而演变。 该网站还将包括存档的数据,为学生建议的练习,以及未解决问题的列表。

项目成果

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Robert Axelrod其他文献

The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration
  • DOI:
    10.2307/20048800
  • 发表时间:
    1998
  • 期刊:
  • 影响因子:
    7.5
  • 作者:
    Robert Axelrod
  • 通讯作者:
    Robert Axelrod
The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration: Agent-Based Models of Competition and Collaboration
  • DOI:
    10.1515/9781400822300
  • 发表时间:
    1997-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Robert Axelrod
  • 通讯作者:
    Robert Axelrod
Evolutionary Dynamics
  • DOI:
    10.2307/j.ctvcm4gjh.15
  • 发表时间:
    2004
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Robert Axelrod
  • 通讯作者:
    Robert Axelrod
NATO and the war on terror: The organizational challenges of the post 9/11 world
  • DOI:
    10.1007/s11558-006-0164-3
  • 发表时间:
    2006-10-31
  • 期刊:
  • 影响因子:
    4.000
  • 作者:
    Robert Axelrod;Silvia Borzutzky
  • 通讯作者:
    Silvia Borzutzky
Aligning simulation models: A case study and results

Robert Axelrod的其他文献

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{{ truncateString('Robert Axelrod', 18)}}的其他基金

EAGER: Collaborative: Policies for Enhancing U.S. Leadership in Cyberspace
EAGER:协作:加强美国网络空间领导地位的政策
  • 批准号:
    1444500
  • 财政年份:
    2014
  • 资助金额:
    $ 26.75万
  • 项目类别:
    Standard Grant
A Landscape Theory of Aggregation
聚合景观理论
  • 批准号:
    9106371
  • 财政年份:
    1991
  • 资助金额:
    $ 26.75万
  • 项目类别:
    Standard Grant
Theories of Cooperative Behavior III
合作行为理论 III
  • 批准号:
    8808459
  • 财政年份:
    1988
  • 资助金额:
    $ 26.75万
  • 项目类别:
    Continuing Grant
Theories of Cooperative Behavior - II
合作行为理论 - II
  • 批准号:
    8318975
  • 财政年份:
    1984
  • 资助金额:
    $ 26.75万
  • 项目类别:
    Standard Grant
Theories of Cooperative Behavior
合作行为理论
  • 批准号:
    8023556
  • 财政年份:
    1981
  • 资助金额:
    $ 26.75万
  • 项目类别:
    Standard Grant
Dynamics of Foreign Policy Decision Making
外交政策决策的动态
  • 批准号:
    7419773
  • 财政年份:
    1974
  • 资助金额:
    $ 26.75万
  • 项目类别:
    Standard Grant

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