Depth: Three Interesting Theses
Less Is More
Sometimes, the best causal explanation of an event leaves out causally relevant information. Many explanations in the special sciences owe their distinctive form to the artful leaving out of parts of the causal story: equilibrium explanations in chemistry and economics; probabilistic explanations in statistical mechanics and evolutionary biology; and with a little extra work, idealization in explanation almost everywhere.
A New Explanatory Relation
Although the causal relation is the most important explanatory relation, there is another explanatory relation that I call
entanglement. Entanglement hitches an explanatory ride on causation: if a certain state of affairs is an explanatory cause of a phenomenon, then anything entangled with that state of affairs is also explanatorily relevant to the phenomenon.
Probabilistic Explanation in Deterministic Systems
In certain kinds of deterministic systems, some phenomena are better explained probabilistically than deterministically – in which case you will have a deterministic and a probabilistic model for the same phenomena, the first of which is predictively better, the second explanatorily better. As a corollary, counterfactual dependence between events is not sufficient for explanatory relevance: in a context in which probabilistic explanation is called for, probability-raising is required in addition.