In this short note, I derive the Bell-CHSH inequalities as an elementary result in the present-day theory of statistical causality based on graphical models or Bayes' nets, defined in terms of DAGs (Directed Acyclic Graphs) representing direct statistical causal influences between a number of observed and unobserved random variables. I show how spatio-temporal constraints in loophole-free Bell experiments, and natural classical statistical causality considerations, lead to Bell's notion of local hidden variables, and thence to the CHSH inequalities. The word "local" applies to the way that the chosen settings influence the observed outcomes. The case of contextual setting-dependent hidden variables (thought of as being located in the measurement devices and dependent on the measurement settings) is automatically covered, despite recent claims that Bell's conclusions can be circumvented in this way.

翻译：在这个简短的注释中,我得出Bell-CHSH不平等是当今基于图形模型或Bayes网的统计因果关系理论的一个基本结果,该理论的定义是DAG(Directed Acyclic Graphs),它代表着一些观察到和没有观察到的随机变量之间的直接统计因果影响。我展示了无漏洞的贝尔实验和自然古典统计因果考虑中的时空限制如何导致Bell对本地隐藏变量的概念,并由此导致CHSH不平等。“当地”一词适用于所选环境影响观察到的结果的方式。根据环境设置的隐藏变量(被认为是位于测量装置中,取决于测量设置)的情况自动被涵盖,尽管最近有人声称Bell的结论可以以这种方式规避。