Power can be gained through appearances: People who exhibit behavioral signals of power are often treated in a way that allows them to actually achieve such power (Ridgeway, Berger, & Smith, 1985; Smith & Galinsky, 2010). In the current article, we examine power signals within interpersonal communication, exploring whether use of concrete versus abstract language is seen as a signal of power. Because power activates abstraction (e.g., Smith & Trope, 2006), perceivers may expect higher power individuals to speak more abstractly and therefore will infer that speakers who use more abstract language have a higher degree of power. Across a variety of contexts and conversational subjects in 7 experiments, participants perceived respondents as more powerful when they used more abstract language (vs. more concrete language). Abstract language use appears to affect perceived power because it seems to reflect both a willingness to judge and a general style of abstract thinking.

The Linguistic Category Model (LCM) was developed as a manual coding scheme for quantifying abstract mindsetsin human language. Previous attempts to computationally automate the LCM have relied primarily on pre-coded semanticfeatures, which fail to incorporate important contextual information integral to the LCM coding scheme. In this paper, weintroduce Syntax-LCM, a novel method for automating LCM coding using syntax and dependency tree features as predictors ofconstrual level. We compare the accuracy of Syntax-LCM to that of two previously used automated methods: LIWC LCM andBrysbaert concreteness ratings. We find support that the Syntax-LCM approximates the hand-coded LCM with higher accuracycompared to both the Brysbaert and the LIWC LCM. We also provide evidence that the syntactic features accounted for bySyntax-LCM mirror the inclusion criteria in the original coding manual and support theoretical relationships between distanceand abstract thinking.

Although research findings are increasingly accessible to the public, people may choose to rely on anecdotal over evidence-based information when making important decisions. Thus, a key challenge facing the scientific community is to develop effective strategies for increasing people’s reliance on research evidence in their decision-making. Focusing on the critical context of cancer-screening decisions, we find that a brief, distance-based intervention can influence people’s intentions to follow evidence-based rather than anecdotal information. Specifically, in a preregistered and well-powered experiment (N = 224), participants who set a screening schedule for the next 10 years before considering a decision for an upcoming appointment were more inclined to follow the implications of evidence-based screening guidelines (vs. an anecdote), compared to participants who only considered the upcoming appointment. The success of this distance-based intervention represents an important first step in translating decades of laboratory research on distance into practical interventions for more complex and consequential decisions.

The commencement of a new editorial tenure within the Journal of Personality and Social Psychology: Attitudes and Social Cognition (JPSP: ASC) provides an opportunity for reflection regarding the journal's core mission. The editors recognize that social psychology is at a crossroads due to competing demands that may have led to reduced submissions and posed challenges for previous editors in filling the journal's pages. Now, JPSP: ASC has been allotted more pages to allow for growth during this editorial term. Although this is desirable for the field, it adds to the pressure of identifying articles for publication given the difficulties filling the pages during previous editorial terms. As the premier outlet of social psychology since 1965, JPSP: ASC will retain its centrality if we increase submissions and publish more articles, while continuing to strive to communicate methodologically trustworthy, intellectually stimulating, and socially relevant research, in a responsible fashion. (PsycInfo Database Record (c) 2024 APA, all rights reserved).