AAP 2026 CONFERENCE

I propose a contextualized conception of proportionality, which requires bringing the concrete context of answering/raising a particular causal inference question into the picture when assessing proportionality. So, the new formula is this: a cause-variable C is proportional to an effect-variable E relative to a given context T. This conception is bolstered by a brief exposition of recent scientific practice in causal feature learning. Moreover, it gets further support by showing how it readily and elegantly resolves a threat posed by Franklin-Hall (2016).