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Abstract Innumeracy (lack of math skills) among nonscientists often leads climate scientists and others to avoid communicating numbers due to concerns that the public will not understand them and may disengage. However, people often report preferring to receive numbers; providing them also can improve decisions. Here, we demonstrated that the presence vs. absence of at least one Arabic integer in climate-related social-media posts increased sharing up to 31.7% but, counter to hypothesis, decreased liking of messages 5.2% in two preregistered observational studies (climate scientists on Twitter, N  > 8 million Tweets; climate subreddit, N  > 17,000 posts and comments). We speculated that the decreased liking was due, not to reduced engagement, but to more negative feelings towards climate-related content described with numeric precision. A preregistered within-participant experiment (N = 212) then varied whether climate consequences were described using Arabic integers (e.g. “90%”) or another format (e.g. verbal terms, “almost all”). The presence of Arabic integers about consequences led to more sharing, wanting to find out more, and greater trust and perceptions of an expert messenger; perceived trust and expertise appeared to mediate effects on sharing and wanting to find out more. Arabic integers about consequences again led to more negative feelings about the Tweets as if numbers clarified the dismaying magnitude of climate threats. Our results indicate that harnessing the power of numbers could increase public trust and concern regarding this defining issue of our time. Communicators, however, should also consider counteracting associated negative feelings—that could halt action—by providing feasible solutions to increase people's self-efficacy. 

Abstract Numeracy—the ability to understand and use numeric information—is linked to good decision-making. Several problems exist with current numeracy measures, however. Depending on the participant sample, some existing measures are too easy or too hard; also, established measures often contain items well-known to participants. The current article aimed to develop new numeric understanding measures (NUMs) including a 1-item (1-NUM), 4-item (4-NUM), and 4-item adaptive measure (A-NUM). In a calibration study, 2 participant samples (n = 226 and 264 from Amazon’s Mechanical Turk [MTurk]) each responded to half of 84 novel numeracy items. We calibrated items using 2-parameter logistic item response theory (IRT) models. Based on item parameters, we developed the 3 new numeracy measures. In a subsequent validation study, 600 MTurk participants completed the new numeracy measures, the adaptive Berlin Numeracy Test, and the Weller Rasch-Based Numeracy Test, in randomized order. To establish predictive and convergent validities, participants also completed judgment and decision tasks, Raven’s progressive matrices, a vocabulary test, and demographics. Confirmatory factor analyses suggested that the 1-NUM, 4-NUM, and A-NUM load onto the same factor as existing measures. The NUM scales also showed similar association patterns to subjective numeracy and cognitive ability measures as established measures. Finally, they effectively predicted classic numeracy effects. In fact, based on power analyses, the A-NUM and 4-NUM appeared to confer more power to detect effects than existing measures. Thus, using IRT, we developed 3 brief numeracy measures, using novel items and without sacrificing construct scope. The measures can be downloaded as Qualtrics files (https://osf.io/pcegz/). 

Park and Brannon (2013, https://doi.org/10.1177/0956797613482944) found that practicing non-symbolic approximate arithmetic increased performance on an objective numeracy task, specifically symbolic arithmetic. Manipulating objective numeracy would be useful for many researchers, particularly those who wish to investigate causal effects of objective numeracy on performance. Objective numeracy has been linked to performance in multiple areas, such as judgment-and-decision-making (JDM) competence, but most existing studies are correlational. Here, we expanded upon Park and Brannon’s method to experimentally manipulate objective numeracy and we investigated whether numeracy’s link with JDM performance was causal. Experimental participants drawn from a diverse internet sample trained on approximate-arithmetic tasks whereas active control participants trained on a spatial working-memory task. Numeracy training followed a 2 × 2 design: Experimental participants quickly estimated the sum of OR difference between presented numeric stimuli, using symbolic numbers (i.e., Arabic numbers) OR non-symbolic numeric stimuli (i.e., dot arrays). We partially replicated Park and Brannon’s findings: The numeracy training improved objective-numeracy performance more than control training, but this improvement was evidenced by performance on the Objective Numeracy Scale, not the symbolic arithmetic task. Subsequently, we found that experimental participants also perceived risks more consistently than active control participants, and this risk-consistency benefit was mediated by objective numeracy. These results provide the first known experimental evidence of a causal link between objective numeracy and the consistency of risk judgments. 

Communities often unite during a crisis, though some cope by ascribing blame or stigmas to those who might be linked to distressing life events. In a preregistered two-wave survey, we evaluated the dehumanization of Asians and Asian Americans during the COVID-19 pandemic. Our first wave (March 26–April 2, 2020; N = 917) revealed dehumanization was prevalent, between 6.1% and 39% of our sample depending on measurement. Compared to non-dehumanizers, people who dehumanized also perceived the virus as less risky to human health and caused less severe consequences for infected people. They were more likely to be ideologically Conservative and believe in conspiracy theories about the virus. We largely replicated the results 1 month later in our second wave (May 6–May 13, 2020; N = 723). Together, many Americans dehumanize Asians and Asian Americans during the COVID-19 pandemic with related perceptions that the virus is less problematic. Implications and applications for dehumanization theory are discussed.