Humans judge each other's actions, which at least partly functions to detect and deter cheating and to enable helpfulness in an indirect reciprocity fashion. However, most forms of judging do not only concern the action itself, but also the moral status of the receiving individual (to deter cheating it must be morally acceptable to withhold help from cheaters). This is a problem, when not everybody agrees who is good and who is bad. Although it has been widely acknowledged that disagreement may exist and that it can be detrimental for indirect reciprocity, the details of this crucial feature of moral judgments have never been studied in depth. We show, that even when everybody assesses individually (aka privately), some moral judgement systems (aka norms) can lead to high levels of agreement. We give a detailed account of the mechanisms which cause it and we show how to predict agreement analytically without requiring agent-based simulations, and for any observation rate. Finally, we show that agreement may increase or decrease reputations and therefore how much helpfulness (aka cooperation) occurs.

翻译：人类对他人的行为进行评判，这至少在部分功能上是为了以间接互惠的方式发现并遏制欺骗，同时促进互助。然而，大多数评判形式不仅涉及行为本身，还涉及接受方的道德地位（为了遏制欺骗，必须从道德上接受对欺骗者不予帮助）。当并非所有人都认同谁好谁坏时，这就成了一个难题。尽管人们普遍承认可能存在分歧，且分歧可能对间接互惠有害，但道德评判这一关键特征的细节从未被深入研究。我们证明，即使每个人都进行独立（即私人）评估，某些道德评判系统（即规范）也能导致高水平的共识。我们详细阐述了导致这一结果的机制，并展示了如何通过分析而非基于智能体的模拟来预测共识，且适用于任何观察率。最后，我们表明共识可能会提高或降低声誉，从而影响互助（即合作）发生的程度。