Introduction to causality in science studies

The paper provides an introduction to structural causal models, which are essential for making sound causal inferences in science studies. The authors explain the importance of distinguishing between correlation and causation and illustrate how structural causal models can be used to make causal assumptions explicit. By using graphical representations of causal models, researchers can better communicate their assumptions and findings, thereby fostering clearer discussions and more robust causal inferences.