超越内群体/外群体二分法：探究对中间群体的利他行为

中文摘要 AI 辅助

内群体偏爱和外群体敌意已有充分文献记载，但现实世界中的群体设置很少符合简单的二分法。通常，一个“中间群体”与内群体共享某些身份标记，但又不完全属于内群体。人们如何对待这种中间群体？我们使用一个正式的身份标记框架和一个多实验室在线实验（N = 376）来解决这个问题，该实验采用一种不受声誉效应和需求特征影响的私人分配任务。我们发现，中间群体可以被中性对待，即既不同于内群体偏爱也不同于外群体敌意，但仅在特定条件下如此。当中间群体与内群体共享两个身份标记（包括大学隶属关系）时，会出现一个完整的层级：内群体受到偏爱，中间群体按照分配规则被对待，而外群体则承担损失。然而，当中间群体仅共享一个标记时，无论共享哪个标记，它都会与外群体被无差别地对待。此外，差异化行为只在参与者在第二阶段重新遇到实验指令和群体构成后才演化，而不是在各轮次中逐渐形成。这些发现表明，参与者能够感知到超越二元内/外群体分类的范畴，但这种感知既需要足够的身份重叠，也需要对群体设置的重复接触。我们的身份标记框架为在更复杂的设置中系统研究群体关系提供了一个工具。

英文摘要

In-group favouritism and out-group hostility are well-documented, but real-world group settings rarely fit a simple dichotomy. Often, a "middle-group" shares some identity markers with the in-group without fully belonging to it. How do people treat such intermediate groups? We address this question using a formal identity marker framework and a multi-lab online experiment (N = 376) with a private allocation task immune to reputation effects and demand characteristics. We find that a middle-group can be treated neutrally, i.e., distinct from both in-group favouritism and out-group hostility, but only under specific conditions. When the middle-group shares two identity markers with the in-group, including university affiliation, a complete hierarchy emerges: the in-group is favoured, the middle-group is treated according to the allocation rule, and the out-group bears the loss. However, when the middle-group shares only one marker, it is treated indistinguishably from the out-group, regardless of which marker is shared. Furthermore, differentiated behaviour evolves only after participants have re-encountered the experimental instructions and group constellation in a second phase, not gradually across rounds. These findings demonstrate that participants can perceive beyond binary in-/out-group categorisation, but such perception requires both sufficient identity overlap and repeated exposure to the group setting. Our identity marker framework provides a tool for systematically studying group relations in more complex settings.

发表机构

• Heidelberg University（海德堡大学）

机构由 AI 辅助整理，请以论文原文为准。