Abstract des Autors

Serial evaluations are the basis of many judgment and decision processes (e.g., in sports, talent shows, or academic examinations). We address the advantages and disadvantages of being in the beginning or the end of such evaluation series. We propose that for serial evaluations, people must calibrate a transformation function that translates observable stimulus input (e.g., performances) into available judgment categories (e.g., “pass” or “fail”). Until this function is calibrated, people are motivated to avoid extreme categories. Therefore, being good in the beginning is disadvantageous because one is more likely to be categorized as “average” than “good,” whereas being bad is advantageous because one is more likely to be categorized “average” than “bad.” We present real-life and laboratory examples of the proposed calibration effects and compare the calibration explanation with other accounts of serial position effects. Based on these theoretical considerations, we suggest possible ways to avoid these position effects in serial evaluations.