 When these assumptions are weakened, we get more variants of Hamilton’s rule. Particularly important are the payoff parameters c and b. Sometimes these denote the values of a particular model, called HRS (Hamilton’s Rule, special), but other times, they denote averaging effects or partial regression coefficients, in the case of HRG (Hamilton’s Rule, general). A third approach, HRA (Hamilton’s Rule, approximate), which uses first-order approximates of regression coefficients, is the approach most commonly used in contemporary kin selection theory. The special version is very restrictive, while the general version allows a wide variety of cases. According to the philosophical analysis of the cases, Nowak et al. are using the special version of Hamilton’s rule when they say it “almost never holds,” whereas Gardner, West, and Wild are using the regression-based, general version of the rule, which allows a great deal of leeway in application. In other words, they are talking past each other (Birch &amp; Okasha 2015). Significantly, 