The general form of Hamilton’s rule makes no predictions and cannot be tested empirically [Evolution]
Hamilton’s rule asserts that a trait is favored by natural selection if the benefit to others,
B, multiplied by relatedness,
R, exceeds the cost to self,
C. Specifically, Hamilton’s rule states that the change in average trait value in a population is proportional to
BR−C. This rule is commonly believed to be a natural law making important predictions in biology, and its influence has spread
from evolutionary biology to other fields including the social sciences. Whereas many feel that Hamilton’s rule provides valuable
intuition, there is disagreement even among experts as to how the quantities
C should be defined for a given system. Here, we investigate a widely endorsed formulation of Hamilton’s rule, which is said
to be as general as natural selection itself. We show that, in this formulation, Hamilton’s rule does not make predictions
and cannot be tested empirically. It turns out that the parameters
C depend on the change in average trait value and therefore cannot predict that change. In this formulation, which has been
called “exact and general” by its proponents, Hamilton’s rule can “predict” only the data that have already been given.
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