People vs Things and Data vs Ideas: Trait correlates of the World-of-Work Map

In this study, 400 employed adults made two binary vocational choices, indicating whether they preferred working with People rather than Things and with Ideas rather than Data. Participants also completed measures of personal characteristics, political beliefs, Big Five personality traits, self-monitoring, self-esteem, and emotional labour. The People-Things and Data-Ideas choices were positively correlated, r = .29, indicating that participants preferring People were more likely to prefer Ideas, whereas those preferring Things were more likely to prefer Data. In the binary logistic regression, sex, optimism, Extraversion, and Surface Acting significantly predicted People-Things choice. Religiosity, Agreeableness, Conscientiousness, Emotional Stability, and Openness to Experience significantly predicted Data-Ideas choice, while Deep Acting was at the conventional threshold for statistical significance. Factorial ANOVAs identified significant People-Things main effects for 10 of the 14 continuous outcomes and significant Data-Ideas main effects for five outcomes, with no significant interactions. People-Things differences were generally more prominent, particularly for Extraversion, Surface Acting, and Expression of Naturally Felt Emotions, whereas Openness to Experience was most clearly differentiated by Data-Ideas choice. These findings provide preliminary evidence that two binary questions can capture psychologically meaningful vocational preferences, although further research is required to establish their reliability, validity, and predictive utility.