It isn’t unusual to find evolutionary theorists of one sort or another working very hard to tie selective pressure and deterministic genetics to behavior. The strains of evolutionary psychology that attempt to find “the mechanism” behind all our weird forms of modern courtship and mating is a classic example. Another is the crowd that says there must be genes determining how well we perform on something as behaviorally derived and complex as standardized testing.
Over at The Mermaid’s Tale, Anne Buchanan applies some scientific skepticism to explanations for a behavior that is a little more basic–altruism. The standard scientific storytelling (not a slam; narrative is how we derive meaning from results) around altruism is that we cooperate with those who are not our direct descendents because our ancestors who were altruistic increased the reproductive fitness of many of their more distant kin, even as their selflessness may have injured their own reproductive fitness. Thus, they indirectly saw to it that the genes for altruism would be passed on at a greater rate than the genes for selfishness.
Buchanan, however, notes that highly deterministic models comes up short here too. The math just doesn’t work.
This would seem to show clearly that, by itself, Hamilton’s rule simply cannot explain human (or even primate) sociality. In all human societies people routinely help their cousins and other more lineally distant relatives. But primates simply cannot have 8 or more additional children as a result of being helped. So those who have thought about this have had to devise various escape-value explanations to preserve the essence of Hamilton’s rule; one is ‘generalized reciprocity’ the idea that I may help you because some day you may return the favor. But with such escape valves, and the complexity of society, it should long ago have been clear that all bets are off.
In other words, in order to tweak the model to accommodate actual, observed social behavior in primates, it becomes so squishy that it loses its predictive power. That, of course, is where it stops being science. It certainly isn’t impossible that someone will come along and add complexity to the basic model in a way that allows it to become predictive again, but the idea isn’t at that point at the moment.
Beyond that, Buchanan questions the very drive to treat cooperation as an anomaly that must be specifically explained.
Life is about molecules interacting, cell compartments interacting, cells, organs, and organisms interacting. Cooperation means co-operation, and only in some social animal contexts is it about cozy kindly interactions including the sort of interactions referred to as ‘altruism’. If an enzyme and its substrate interact to bring about a reaction, that is cooperation. If one component has the wrong structure or isn’t present when the other is, the interaction doesn’t occur. One can’t just evolve by out-competing the other. Things may arise individually, but in various ways must advance in prevalence by successful interactions. If this is extended to the thousands of interactions in a cell, and among cells in an organism, then why not among organisms in a population?
Sometimes inter-individual competition does certainly occur and sometimes this seems clearly to be related to genetic differences. And even if there may be some elements of competition — in the restricted sense simply of some things proliferating faster than others, that fact doesn’t gainsay the predominance of cooperation as a fundamental part of the road to success. Much more of the time what goes on in life is about successful interactions.
Buchanan presents an interesting perspective on how we determine which scientific questions even are question requiring answers. I recommend heading over and reading the whole thing.
Via the Carnival of Evolution at Synthetic Daisies.