In studies of social inference and human mate preference, a wide but inconsistent array of tools for computing facial masculinity has been devised. Several of these approaches implicitly assumed that the individual expression of sexually dimorphic shape features, which we refer to as maleness, resembles facial shape features perceived as masculine. We outline a morphometric strategy for estimating separately the face shape patterns that underlie perceived masculinity and maleness, and for computing individual scores for these shape patterns. We further show how faces with different degrees of masculinity or maleness can be constructed in a geometric morphometric framework. In an application of these methods to a set of human facial photographs, we found that shape features typically perceived as masculine are wide faces with a wide inter-orbital distance, a wide nose, thin lips, and a large and massive lower face. The individual expressions of this combination of shape features—the masculinity shape scores—were the best predictor of rated masculinity among the compared methods (r = 0.5). The shape features perceived as masculine only partly resembled the average face shape difference between males and females (sexual dimorphism). Discriminant functions and Procrustes distances to the female mean shape were poor predictors of perceived masculinity.

Landmarks, stature, and masculinity ratings for 45 human facesFemales_21_70lms.txt: x and y coordinates of 70 landmarks measured on 21 female faces (21x140 data matrix) Males_24_70lms: x and y coordinates of 70 landmarks measured on 24 male faces (24x140 data matrix) Scale_factor_females.txt: scale factor of landmark coordinates for the female faces. Scale_factor_males.txt: scale factor of landmark coordinates for the male faces. Body_height_males_cm.txt: Measures of stature for the 24 male individuals (in cm). Perceived_masculinity.txt: Average masculinity ratings for the 24 male faces (range from 0 to 80).Landmarks_stature_rating.zip