解决冲突、谈判和改变的神经语言编程方法

Eduard Vinyamata
{"title":"解决冲突、谈判和改变的神经语言编程方法","authors":"Eduard Vinyamata","doi":"10.7238/JOC.V2I1.1085","DOIUrl":null,"url":null,"abstract":"Neuro-Linguistic Programming (NLP) can bring new perspectives and new results to any endeavour involving personal (i.e. internal) and interpersonal communication. The organisation of information to achieve results is at the core of NLP and also a frequent goal for interpersonal conflict managers such as arbiters, mediators and negotiators. This article sheds light on one particular NLP tool, namely chunking. Chunking is a direct application of the NLP Meta-model, a communications model used to find and challenge linguistic distortions in the client's language. Chunking deals with information size and direction. Information can be chunked up or down in size and can be moved laterally to find alternative examples of a concept at the same level of information. In a conflict resolution or mediation setting, chunking up can be a guide to reach an initial agreement level, a compromise between the parties. Chunking down, on the other hand can be used to deal with specific problems and find a leverage point to make a breakthrough. Overall, NLP technologies such as chunking can bring performance, alternative methodologies and solutions at times where the highest academic approaches are not enough.","PeriodicalId":183832,"journal":{"name":"Journal of Conflictology","volume":"81 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"The Neuro-Linguistic Programming Approach to Conflict Resolution, Negotiation and Change\",\"authors\":\"Eduard Vinyamata\",\"doi\":\"10.7238/JOC.V2I1.1085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Neuro-Linguistic Programming (NLP) can bring new perspectives and new results to any endeavour involving personal (i.e. internal) and interpersonal communication. The organisation of information to achieve results is at the core of NLP and also a frequent goal for interpersonal conflict managers such as arbiters, mediators and negotiators. This article sheds light on one particular NLP tool, namely chunking. Chunking is a direct application of the NLP Meta-model, a communications model used to find and challenge linguistic distortions in the client's language. Chunking deals with information size and direction. Information can be chunked up or down in size and can be moved laterally to find alternative examples of a concept at the same level of information. In a conflict resolution or mediation setting, chunking up can be a guide to reach an initial agreement level, a compromise between the parties. Chunking down, on the other hand can be used to deal with specific problems and find a leverage point to make a breakthrough. Overall, NLP technologies such as chunking can bring performance, alternative methodologies and solutions at times where the highest academic approaches are not enough.\",\"PeriodicalId\":183832,\"journal\":{\"name\":\"Journal of Conflictology\",\"volume\":\"81 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Conflictology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7238/JOC.V2I1.1085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Conflictology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7238/JOC.V2I1.1085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

神经语言程序设计(NLP)可以为涉及个人(即内部)和人际沟通的任何努力带来新的视角和新的结果。组织信息以实现结果是NLP的核心,也是仲裁者、调解者和谈判者等人际冲突管理者经常追求的目标。本文将介绍一种特殊的NLP工具,即分块处理。分块是NLP元模型的直接应用,这是一种用于发现和挑战客户语言中的语言扭曲的通信模型。分块处理信息的大小和方向。信息的大小可以增加或减少,也可以横向移动,以在同一信息级别上找到概念的替代示例。在冲突解决或调解中,分块可以指导双方达成初步协议,即双方之间的妥协。分块,另一方面,可以用来处理具体问题,找到一个杠杆点,取得突破。总的来说,NLP技术,如分块处理,可以带来性能,替代方法和解决方案,有时最高的学术方法是不够的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Neuro-Linguistic Programming Approach to Conflict Resolution, Negotiation and Change
Neuro-Linguistic Programming (NLP) can bring new perspectives and new results to any endeavour involving personal (i.e. internal) and interpersonal communication. The organisation of information to achieve results is at the core of NLP and also a frequent goal for interpersonal conflict managers such as arbiters, mediators and negotiators. This article sheds light on one particular NLP tool, namely chunking. Chunking is a direct application of the NLP Meta-model, a communications model used to find and challenge linguistic distortions in the client's language. Chunking deals with information size and direction. Information can be chunked up or down in size and can be moved laterally to find alternative examples of a concept at the same level of information. In a conflict resolution or mediation setting, chunking up can be a guide to reach an initial agreement level, a compromise between the parties. Chunking down, on the other hand can be used to deal with specific problems and find a leverage point to make a breakthrough. Overall, NLP technologies such as chunking can bring performance, alternative methodologies and solutions at times where the highest academic approaches are not enough.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信