This is a nice piece by Jonathan on the rivalry—and putative equivalence—of kind selection and group selection. He starts by noting that the well-known equivalence results have done exactly nothing to dissolve the dispute between kin-selectionists and group-selectionists. Why might that be? Jonathan’s answer is that the equivalence is purely statistical, and papers over genuine causal differences between the two. The essay has a useful historical summary of how generalisations of both approaches converged, but the upshot is this. You can decompose the mathematics of selection arbitrarily into (a) within- and between-group components and/or (b) direct and indirect (kin-based) costs and benefits. One gets you the multi-level Price equation; the other gets you rb>c.

The two decompositions *have* to be equivalent, because they are mathematical rearrangements of the same principle (viz, the Price equation with some assumptions). But arbitrarily dividing selection into within and between-group components tells you nothing about the causal role of groups. Nor does multiplying selective benefit by relatedness tell you anything about effects of kinship. (E.g. rb>c is satisfied for purely selfish traits, where r=1 for all beneficiaries.)

So the stubborn disagreement is, quite properly, about the *causal contributions* of kinship and group structure.

Birch closes with a positive proposal for identifying the relative roles of kinship and groups. He defines two scalar properties K and G. High-K populations are ones where whole-genome correlation is a high proportion of genetic correlation; since kinship but not selection can produce whole-genome correlation, that tells you whether the relatedness on which rb>c operates is due to kinship (as opposed to, say, green beards). High-G populations are ones which are clustered and isolated (borrowing from network theory). A population’s position in K-G space tells you something about whether groups or kinship are likely to be selectively ert. (And other things besides: kinship-based relatedness is likely to be more stable than other kinds; really clumpy groups might be setting up for an evolutionary transition.)

Q: It looks to me like high K and high G are *necessary *for group and kin causation—properties can’t be causal unless they’re genuine features of the populations, rather than arbitrary gerrymanders. But I wonder whether they are sufficient. In principle a population can have groups without those groups *doing *much of anything. Similarly a population could have a highly kin-marked structure without producing much in the way of altruism. (Consider any parthenogenetic species.) So I suppose the ultimate question is still counterfactual/interventionist. Unless there’s something relevantly causal in the definition of K and G that I’m missing.

Anyway, this is a very helpful piece, with an admirably concise explanation of the issue and background (with the formalism available but boxed off, which is excellent practice). Useful for philosophers as well as what (presumably, given its venue) is its intended audience of biologists.

It is also, of course, biolgical grist for the causal inference mill. I’m going to have a look at Okasha’s 2016 paper applying DAGs to the kin/group question next.