Reconceptualizing resistance organizations and outcomes: Introducing the Revolutionary and Militant Organizations dataset (REVMOD)
Reconceptualizing resistance organizations and outcomes: Introducing the Revolutionary and Militant Organizations dataset (REVMOD)
复制标题
重新概念化抵抗组织和结果：介绍革命和激进组织数据集 (REVMOD)
DOI：
10.1177/0022343319835888
复制
发表时间：
2019
影响因子：
3.6
通讯作者：
Benjamin Acosta
中科院分区：
文献类型：
--
作者：
Benjamin Acosta
近年来，研究涉及革命和激进组织(如恐怖主义、内战和非暴力斗争)的各种形式的冲突的学者认识到，任意的组织类别和类型往往使大N研究不完整和有偏见。在摆脱产生这种选择偏见的名义上的分类界限，寻找一个更普遍的抵抗组织概念的过程中，我构建了一个原始数据集，旨在弥合冲突文献之间的差距。在传统分类的基础上，革命和激进组织数据集(REVMOD)由1940年至2014年间运作的500多个抵抗组织组成，包括各种类型的抵抗组织--其中许多组织使用多种战术，在各种冲突背景下运作，和/或面对众多目标类型。该数据集以每年(组织年)的间隔记录组织属性、盟友和对手，从而使可靠的时间序列分析成为可能。REVMOD跟踪组织结果-目标类型和实现程度、政治能力、领导人/S、选民身份群体、暴力和示威水平、规模、组织别名和其他几个变量，在收集抵抗组织的信息方面开辟了新的天地，可以刺激无数研究。初步数据分析表明，组织政治能力的差异解释了抵抗结果的总体差异，以及在内战、恐怖主义和非暴力革命等特定背景下的差异。REVMOD提供了一个独特的机会，为阻力研究开发一种新的研究范式，采用大N经验分析，揭示当代不同形式的政治争论之间的共性，以及更好地理解为什么以及如何不同的阻力过程可能产生特定的结果。
In recent years, scholars of various forms of conflict involving revolutionary and militant organizations (such as terrorism, civil war, and nonviolent contestation) recognized that arbitrary organizational categories and typologies often leave large-N studies incomplete and biased. In moving away from nominal categorical boundaries that produce such selection biases and looking to a more generalized conception of resistance organizations, I constructed an original dataset that aims to bridge the gap between conflict literatures. Transcending traditional classifications, the Revolutionary and Militant Organizations dataset (REVMOD) consists of over 500 resistance organizations operative sometime between the years 1940 and 2014 and includes a diverse array of types of resistance organizations – many of which utilize a multitude of tactics, operate in various conflict contexts, and/or confront numerous target types. The dataset documents organizational attributes, allies, and adversaries at annual intervals (organization-years), making reliable time-series analyses possible. Tracking variables like organizational outcome-goal type and degree of achievement, political capacity, leader/s, constituent identity group, violence and demonstration levels, size, organization aliases, and several others, REVMOD breaks new ground in the collection of information on resistance organizations and can spur countless studies. A preliminary data analysis demonstrates that differences in organizational political capacity explain variation in resistance outcomes generally and in particular contexts such as civil war, terrorism, and nonviolent revolutions. REVMOD provides a unique opportunity to develop a new research paradigm for resistance studies that employs large-N empirical analyses to uncover generalities between different forms of political contention in the contemporary era, as well as to better understand why and how distinct resistance processes may produce specific outcomes.
影响因子：
3.6
作者：
Markus;Bethke;Felix S;Lambach;Daniel
通讯作者：
Daniel
影响因子：
19.7
作者：
Kundel, HL;Polansky, M
通讯作者：
Polansky, M