Abstract

Although authoritarianism has predominantly been studied among political conservatives, authoritarian individuals exist on both “poles” of the political spectrum. A 39-item multidimensional measure of left-wing authoritarianism, the Left-wing Authoritarianism Index, was recently developed to extend the study of authoritarianism to members of the far-left. The present study coupled a fully automated machine learning approach (i.e., a genetic algorithm) with multidimensional item response theory in a large, demographically representative American sample (N = 834) to generate and evaluate two abbreviated versions of the Left-wing Authoritarianism Index. We subsequently used a second community sample (N = 477) to conduct extensive validational tests of the abbreviated measures, which comprise 25- and 13-items. The abbreviated forms demonstrated remarkable convergence with the full LWA Index in terms of their psychometric (e.g., internal consistency) and distributional (e.g., mean, standard deviation, skew, kurtosis) properties. This convergence extended to virtually identical cross-measure patterns of correlations with 14 external criteria, including need for chaos, political violence, anomia, low institutional trust. In light of these results, the LWA-25 and LWA-13 scales appeared to function effectively as measures of LWA.

摘要

尽管威权主义主要在政治保守派中进行研究，但威权主义个人存在于政治光谱的两个“极点”。最近开发了一个包含 39 项的左翼威权主义多维衡量指标，即左翼威权主义指数，以将威权主义研究扩展到极左翼成员。本研究将完全自动化的机器学习方法（即遗传算法）与多维项目反应理论相结合，在一个具有人口统计学代表性的大型美国样本（N = 834）中生成和评估左翼威权主义指数的两个缩写版本。我们随后使用第二个社区样本 (N = 477) 对包含 25 项和 13 项的简化措施进行广泛的验证测试。缩写形式在其心理测量（例如，内部一致性）和分布（例如，均值、标准差、偏度、峰度）属性方面表现出与完整 LWA 指数的显着收敛。这种趋同扩展到与 14 个外部标准相关的几乎相同的交叉测量模式，包括对混乱的需要、政治暴力、失范、低制度信任。根据这些结果，LWA-25 和 LWA-13 量表似乎可以有效地作为 LWA 的度量。政治暴力、失范、机构信任度低。根据这些结果，LWA-25 和 LWA-13 量表似乎可以有效地作为 LWA 的度量。政治暴力、失范、机构信任度低。根据这些结果，LWA-25 和 LWA-13 量表似乎可以有效地作为 LWA 的度量。