Cox proposes that the economic analyses of resource transfers within families can be considerably enhanced by using evolutionary biological theory to generate expectations specific to relevant demographic categorizations of family members. Whereas wholly abstract economic theorizing can lead to surprising, productive insights about actors characterized merely as “person 1 ” and “person 2, ” 1 evolutionary biology offers the possibility of furthering understanding by making specific use of information that “person 1 ” and “person 2 ” are “mother ” and “father, ” “son ” and “daughter”, “biological child ” and “stepchild, ” or even “paternal grandmother ” and “maternal grandmother. ” Evolutionary biological theory and economic theory have historically drawn from one another in the development of theoretical tools, as the enterprises share considerable abstract affinities due to their common preoccupation with the logic of optimization (see, e.g., Gintis 2000). Moreover, family life is one of the areas in which the potential contributions of an evolutionary perspective has seemed strongest, working from the premise that the affective bonds of kin are rooted in genetically-based propensities that evolved by kin selection. In this light, one might wonder why utilization of substantive propositions from evolutionary biology in studying the economics of family life has

The occurrence of cooperation poses a problem for the biological and social sciences. However, many aspects of the biological and social science literatures on this subject have developed relatively independently, with a lack of interaction. This has led to a number of misunderstandings with regard to how natural selection operates, and the conditions under which cooperation can be favoured. Our aim here is to provide an accessible overview of social evolution theory and the evolutionary work on cooperation, emphasising common misconceptions.

Abstract: Theoretical studies suggest that mating and pair formation is not likely to be random. Computer simulations suggested that sex among genetically complex organisms requires mate choice strategies for its evolutionary maintenance, to reduce excessive genetic variance produced by out-crossing. One strategy achieving this aim efficiently in computer simulations is assortative mating modeled as “self seeking like”. Another one is selection of “good genes”. Assortative mating increases the probability of finding a genetically similar mate, without fomenting inbreeding, achieving assortative mating without hindering the working of other mate selection strategies which aim to maximize the search for “good genes”, optimizing the working of sex in evolutionary terms. Here we present indirect evidence that in a significant proportion of human reproductive couples, the partners show much higher facial resemblances than can be expected by random pair formation, or as the outcome of “matching for attractiveness ” or the outcome of competition for the most attractive partner accessible, as had been previously assumed. The data presented is compatible with the hypothesis derived from computer simulations, that human mate selection strategies achieve various aims: “self seeking like ” (including matching for attractiveness) and mating with the best available genes.