Two rational, a priori strategies for dealing with intentional distortion of self-descriptions were developed and evaluated according to their (a) impact on criterion-related validity, (b) effect on scale score means for the total group as well as women and minorities, and (c) impact on who specifically is hired. One strategy involves correcting an individual's content scale scores based on the individual's score on an Unlikely Virtues (UV) scale. A second strategy involves removing people from the applicant pool because their scores on an UV scale suggest they are presenting themselves in an overly favorable way. Incumbent and applicant data from three large studies were used to evaluate the two strategies. The data suggest that (a) neither strategy affects criterion-related validities, (b) both strategies produce applicant mean scores for content scales that are closer to incumbent mean scores, (c) men, women, Whites, and minorities are not differentially affected, and (d) both strategies result in a subset of people who are not hired who would otherwise have been hired. If one's goal is to reduce the impact of intentional distortion on hiring decisions, both strategies appear reasonably effective.