Abstract

The paper presents a new approach to the assessment of personality traits based on the theory and methodology of meaning. Meaning consists of contents and processes involved in the psychological domains of cognition, emotions, personality, behavior and physiology. On the basis of a large body of empirical data, it is defined as a referent-centered pattern of meaning values, whereby the referent is the carrier of meaning and the meaning values are the assigned meanings. Meaning assessment is done in terms of five sets of meaning variables characterizing the contents, relations, structure and mode of expression of the meaning. Any communication or statement can be analyzed in terms of the five sets of meaning variables. The meaning variables characterizing the meaning communications of an individual in response to the stimuli used in the Meaning Test constitute the individual’s meaning profile. The correspondences between the individuals’ meaning profiles and the scores on standard personality questionnaires enable defining the meaning profiles of the personality traits. Each trait corresponds to a unique pattern of meaning variables. Matching the meaning profiles of the individual and of the specific trait provides the individual’s score of the trait even without administering the actual trait questionnaire to the individual. The methodologies of defining the meaning profiles are done on a computer program (Kreitlermeaningsystem.tau.ac.il). The following are the main advantages of the meaning-based trait scores: they are valid; they are correlated significantly with the scores based on standard questionnaires; they are not based on self-report; they provide cheap and easily applied means of scoring; they include a lot of information about the trait beyond the score itself; they provide insight into the manner in which the trait functions; they enable comparing traits, and they provide means for identifying traits and differentiating between traits and other personality tendencies. Future research will focus on improving the precision and range of application of the methodology.

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