  I present a simple numerical model based on iteratively updating subgroups of
a population, individually modeled by nonnegative real numbers, by a constant
decay factor; however, at each iteration, one group is selected to instead be
updated by a constant growth factor. I discover a relationship between these
variables and their respective probabilities for a given subgroup, summarized
as the variable $c$. When $c>1$, the subgroup is found to tend towards
behaviors reminiscent of antifragility; when at least one subgroup of the
population has $c\ge1$, the population as a whole tends towards significantly
higher probabilities of "living forever," although it may first suffer a drop
in population size as less robust, fragile subgroups "die off." In concluding,
I discuss the limitations and ethics of such a model, notably the implications
of when an upper limit is placed on the growth constant, requiring a population
to facilitate an increase in the decay factor to lessen the impact of periods
of failure.
