A Multidimensional Approach to Human Mate Selection
Dan Conroy-Beam, UC Santa Barbara
Human mating research is largely motivated by an assumption that mate choice is guided by mate preferences. But the field knows little about the psychology responsible for translating preferences into downstream outcomes. Stated differently, what do mate preferences do and how do they do it? I present data from a series of studies exploring these questions using two empirical strategies: agent-based models and research on actual mated couples. First, I use a model of human mate choice evolution to compare the evolvability of several alternative algorithms for integrating mate preferences in mate selection. The findings support a novel hypothesis: human mate preferences are integrated by a Euclidean algorithm that represents preferences and potential mates as points within a common multidimensional preference space. I then apply this novel Euclidean algorithm to test hypotheses concerning a variety mating outcomes—attraction to potential mates, mate selection, and the calibration of mate preferences. Findings reveal that (1) Euclidean distances from ideal mate preferences predict attraction to potential mates, (2) chosen mates tend to fall close to mate preferences in preference space, (3) Euclidean measures of mate value predict people’s ability to fulfill their mate preferences and attract desirable mates, and (4) people calibrate their ideal mate preferences to their mate value as measured by a Euclidean algorithm. These findings highlight the utility of a multidimensional, Euclidean model of mate preference psychology for understanding how human psychology translates mate preferences into downstream mating outcomes.
Monday, November 14, 2016