A scalability approach to the assessment of individual differences in consistency is proposed. For a given trait, a person is scalable to the extent that his or her behavior parallels the evocativeness or difficulty level of situations or test items. Scalability can be assessed on a wide variety of data sets; measures of scalability are not formally entailed by traditional summary measures. In an empirical investigation, several measures of scalability are found to be reliable and to contribute uniquely, although modestly, to prediction. In light of both theoretical and empirical considerations, continued investigation of the scalability method is warranted; measures of scalability may fill a unique role in basic personality research.In the 1937 classic, Personality: A Psychological Interpretation, Gordon Allport denned trait as "a generalized and focalized neuropsychic system (peculiar to the individual), with the capacity to render many stimuli functionally equivalent, and to initiate and guide consistent [italics added] (equivalent) forms of adaptive and expressive behavior" (p. 295).Traits give rise to consistent behavior; consistency is a necessary (although not necessarily sufficient) empirical indicator of a trait. The development of a sound method for assessing individual differences in consistency is the first step toward reconciling Allport's (1937) psychology of the individual with contemporary personality assessment. Consistency Versus RigidityIn recent years, a number of methods for the measurement of consistency have been proposed (e.g.,

Shame, guilt, and ego development are conceptually interrelated constructs, yet their empirical relations have not yet been examined. Further, these constructs have not yet been mapped onto the widely used Five-Factor Model. In Study 1, relations were examined between these three domains within a sample of Australian university students. Two types of guilt were distinguished, Empathic Guilt (associated with Agreeableness) and Anxious Guilt (associated with Neuroticism). The relationship between Shame and Ego Level was found to be curvilinear, with Shame greatest for persons at intermediate stages of ego development. In Study 2, relations between ego development and the Five-Factor Model were further examined. Across both studies, Ego Level was best predicted from Conscientiousness among men and from Openness among women. Relations between Ego Level, proneness to shame and guilt, and the five factors were typically modest, suggesting that these represent complementary approaches to the study of personality.

The dimensionality of personality ratings on the California Adult Q-set (CAQ) is examined in a sample of 940 subjects. Solutions of between 5 and 15 factors are examined; interrater agreement is assessed for items, factors, and items partialing factors. Results suggest that the 5 personality factors are important yet not exhaustive in accounting for common factor variance in the CAQ. Furthermore, interjudge agreement extends beyond the 5 dimensions. Likely explanations for these results are considered, and implications are addressed.

To forecast four-year, two-year, and single-course grades in college, a California Psychological Inventory (CPI) equation (30.60 - .26Wb + .35Re -. l9Gi + .39Ai + .22Ie + .36Py) was developed. Cross-validational coefficients for scores on the equation were .38 for 326 males and .36 for 570 females.

Personality psychology has long been grounded in data typologies, particularly in the delineation of behavioural, life outcome, informant‐report, and self‐report sources of data from one another. Such data typologies are becoming obsolete in the face of new methods, technologies, and data philosophies. In this article, we discuss personality psychology's historical thinking about data, modern data theory's place in personality psychology, and several qualities of big data that urge a rethinking of personality itself. We call for a move away from self‐report questionnaires and a reprioritization of the study of behaviour within personality science. With big data and behavioural assessment, we have the potential to witness the confluence of situated, seamlessly interacting psychological processes, forming an inclusive, dynamic, multiangle view of personality. However, big behavioural data come hand in hand with important ethical considerations, and our emerging ability to create a ‘personality panopticon’ requires careful and thoughtful navigation. For our research to improve and thrive in partnership with new technologies, we must not only wield our new tools thoughtfully, but humanely. Through discourse and collaboration with other disciplines and the general public, we can foster mutual growth and ensure that humanity's burgeoning technological capabilities serve, rather than control, the public interest. © 2020 European Association of Personality Psychology