背景告知跨文化合作的稳定性和支持行动

M. Hoffman, B. Kettler, Terry Padgett
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引用次数: 0

摘要

世界银行发展研究局前局长保罗•科利尔(Paul Collier)表示,在所有“已解决”的冲突中,53%的冲突在5年内复发。身份通常是大多数冲突的核心,个人和集体的身份都植根于文化。理解和欣赏新出现的冲突各方的文化特性对于理解和改变冲突至关重要。不幸的是,当采用标准的西方冲突解决模式时,许多冲突的文化差异被忽视了。本文描述了最近为国家情报界在这一领域进行的研究。这项工作得到了扩展,供诺贝尔呼吁基金会使用,并应用于几个现实世界的缔造和平情况。在美国国防高级研究计划局(DARPA)资助的一项新努力下,这项工作目前正在扩大,以确定维持和平进程中活动或拟议活动的文化“指标和警告”。这种环境提供了一种机制,可以将状态信息和新闻自动吸收到机器可以理解的“情境上下文”中。智能体社区将已知情境上下文部分匹配到系统内两个语义相连的模型类:任务独立的文化模型;以及文化独立的使命模式。任务和文化指标和警告(i&w)结果和可视化,供用户解释和反应
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Context informed cross cultural collaboration in stability and support operations
According to Paul Collier, former Director of the Development Research group at the World Bank, 53% of all "resolved" conflicts relapse within 5 years. Identity is generally at the heart of most conflicts, and identity oth individual and collective - is rooted in culture. Understanding and appreciation of the cultural identity of the parties to an emerging conflict is critical to both understanding and transforming that conflict. Unfortunately, the cultural nuances of many conflicts are overlooked when standard Western models of conflict resolution are applied. This paper describes recent research in this area conducted for the National Intelligence Community. This work was extended for use by the Nobel Appeal Foundation and applied in several real-world peacemaking situations. That work is now being extended to identify cultural "indicators and warnings" to activities or proposed activities within the peacekeeping process under a new effort funded by the Defense Advance Research Projects Agency (DARPA). This environment provides a mechanism for the automatic ingestion of status information and news into a machine understandable "situation context". A community of agents does partial matching of the known situation context to two semantically linked classes of models within the system: mission-independent cultural models; and culturally-independent mission models. Mission and cultural indicators and warnings (I&Ws) results and visualized for the user to interpret and react
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