On Fair Person Classification Based on Efficient Factor Score Estimates in the Multidimensional Factor Analysis Model

Since Hooker, Finkelman and Schwartzman (Psychometrika 74(3): 419–442, 2009) it is known that person parameter estimates from multidimensional latent variable models can induce unfair classifications via paradoxical scoring effects. The open question as to whether there is a fair and at the same time multidimensional scoring scheme with adequate statistical properties is addressed in this paper. We develop a theorem on the existence of a fair, multidimensional classification scheme in the context of the classical linear factor analysis model and show how the computation of the scoring scheme can be embedded in the context of linear programming. The procedure is illustrated in the framework of scoring the Wechsler Adult Intelligence Scale (WAIS-IV).     

Forgive them for I have sinned: The relationship between guilt and forgiveness of others' transgressions

We propose that guilt leads to forgiveness of others' transgressions. In Study 1, people prone to experience guilt (but not shame) were also prone to forgive others for past misdeeds. In Study 2, we manipulated harm‐ and inequity‐based guilt; both increased forgiveness of others' transgressions. Further, the effect of guilt on forgiveness was mediated by identification with the transgressor. In Study 3, we replicated the guilt–forgiveness relationship and examined three other plausible mediators: capability for similar wrongdoing, empathic understanding, and general identification; only identification with the transgressor satisfied the criteria for mediation. In Study 4, we induced guilt by asking participants to harm a friend or stranger. Guilt induced by harming a friend led to greater forgiveness of third‐party transgressors, and again, identification with the transgressor mediated the effect. We discuss the implications of these results for understanding how the prosocial effects of guilt extend beyond the boundaries of a single interpersonal relationship.     

Spatial updating relies on an egocentric representation of space: Effects of the number of objects

Models of spatial updating attempt to explain how representations of spatial relationships between the actor and objects in the environment change as the actor moves. In allocentric models, object locations are encoded in an external reference frame, and only the actor’s position and orientation in that reference frame need to be updated. Thus, spatial updating should be independent of the number of objects in the environment (set size). In egocentric updating models, object locations are encoded relative to the actor, so the location of each object relative to the actor must be updated as the actor moves. Thus, spatial updating efficiency should depend on set size. We examined which model better accounts for human spatial updating by having people reconstruct the locations of varying numbers of virtual objects either from the original study position or from a changed viewing position. In consistency with the egocentric updating model, object localization following a viewpoint change was affected by the number of objects in the environment.