 Later theorists such as Cartwright (1979) and Eells (1991) developed this condition by making causal claims relative to a causally homogenous background context, which is specified by a set of variables \(\b{K}\). Consider the following example of association reversal presented by Cartwright. Supposing that smoking \((\r{S})\) is a cause of heart disease \((\r{H})\), one might expect that smoking would raise the probability of heart disease. Yet this might not be the case. Suppose that in a population there is a strong correlation between smoking and exercising (X), and that exercise lowers the probability of heart disease by more than smoking raises its probability. In such a case, smoking might lower the probability of heart disease although conditional on either \(X\) or \(\neg X\), \(\r{S}\) raises \(\r{H}\)’s probability.