This research note addresses a gap in the public administration literature by arguing that a political Darwinism was present in the intellectual origins of American administrative theory. By examining the arguments of Woodrow Wilson, this article demonstrates that Darwinism complemented the German political thought that contributed to the establishment of America’s administrative state. The application of Darwinian evolutionary biology to politics was a vital element of Wilson’s reconceptualization of the state as a living organism. Darwinism was a key rhetorical tool employed by Wilson in his argument against the Constitution’s separation of powers. This note finds that Darwinism was present in the early stages of public administration theory in Wilson’s argumentation and persists today in the public administration literature. It concludes by sketching out an agenda for further research on Darwinism’s influence on public administration.

Scholars increasingly use Twitter data to study the life sciences and politics. However, Twitter data collection tools often pose challenges for scholars who are unfamiliar with their operation. Equally important, although many tools indicate that they offer representative samples of the full Twitter archive, little is known about whether the samples are indeed representative of the targeted population of tweets. This article evaluates such tools in terms of costs, training, and data quality as a means to introduce Twitter data as a research tool. Further, using an analysis of COVID-19 and moral foundations theory as an example, we compared the distributions of moral discussions from two commonly used tools for accessing Twitter data (Twitter’s standard APIs and third-party access) to the ground truth, the Twitter full archive. Our results highlight the importance of assessing the comparability of data sources to improve confidence in findings based on Twitter data. We also review the major new features of Twitter’s API version 2.

We introduce cognitive-affective maps (CAMs) as a novel tool to assess individual experiences and belief systems. CAMs were first presented by the cognitive scientist and philosopher Paul Thagard as a graphical representation of a mental network, visualizing attitudes, thoughts, and affective connotations toward the topic of interest. While CAMs were originally used primarily to visualize existing data, the recent release of the new software tool Valence has facilitated the applicability of CAMs for empirical data collection. In this article, we explain the concept and the theoretical background of CAMs. We exemplify how CAMs can be applied in research practice, including different options for analysis. We propose CAMs as a user-friendly and versatile methodological bridge between qualitative and quantitative research approaches and encourage incorporating the method into studies to access and visualize human attitudes and experience.

Tasks driven by artificial intelligence (AI), such as evaluating video job interviews, rely on facial recognition systems for decision-making. Therefore, it is extremely important that the science behind this technology is continually advancing. If not, visual stereotypes, such as those associated with facial age and gender, will lead to dangerous misapplications of AI.