Numeracy and the Strength of Monetary versus Non-Monetary Incentives on Task Performance

Background: Traditionally, monetary incentives (such as paychecks and bonuses) have been one of the primary methods companies use to show their employees that the work they do is valued (Bonner & Sprinkle, 2002). Generally, past research has found that money tends to result in higher performance than non-monetary, tangible incentives (e.g., a meal, gift, etc.). More recent research has found that in some settings, a monetary incentive is less motivating to workers’ effort and productivity than a non-monetary incentive of equal value (Heyman & Ariely, 2004). However, there may be reason to believe that non-monetary incentives may not influence everyone equally. This, in part, could be due to objective numeracy, defined as the ability to understand and use probabilistic and other mathematical concepts (measured with a math test; see Peters et al., 2006; Cokley & Kelley, 2009; Pachur & Galesic, 2013). Methods: The proposed study will examine the effects of numeracy and incentive level (low or high) and type (monetary or non-monetary) on effort exerted to perform a task. Specifically, participants will receive either a high or low amount of a monetary (money) or non-monetary (Jelly Belly Jellybeans) incentive. To separate skill from motivation, participants will complete the task, be told what incentive they will receive, and complete the task again. Expected Results: Based on the prior research, we think that the low monetary incentive will be more de-motivating (i.e., people will expend less effort) than the other conditions. This will be especially true for those high versus low in objective numeracy. Conclusions: These findings would suggest that employees in certain vocations that require a higher level of mathematical comprehension, such as accountants and engineers, may be more sensitive to the amount of monetary incentives. All in all, through further research on the relationship between objective numeracy and the dynamics of non-monetary and monetary incentives on effort and performance we will be able to gain greater insight into the most optimal methods for incentivizing individuals with a focus on individual happiness and life satisfaction.OSU Decision Sciences CollaborativeOSU College of Arts and SciencesOSU Department of PsychologyAcademic Major: Psycholog

The numeric understanding measures: Developing and validating adaptive and nonadaptive numeracy scales

19 pagesNumeracy—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/)

Keynote Address: Ability-related polarization in political attitudes: Mechanisms of motivated reasoning

In the United States, political parties are increasingly polarized, with large numbers of people believing that the two parties cannot even agree on basic facts. Partisans also tend to view the other side as unintelligent. Instead, my colleagues and I have found that it is those who are more, rather than less, intelligent who have the most polarized opinions. In particular, although measures of numeric ability, such as objective numeracy, are often used to index ability-related polarization, we have robustly found ideological differences to be more pronounced among those higher in verbal ability. In two large-scale longitudinal datasets (combined N = 5761), we investigated ability-related political polarization in responses to the COVID19 pandemic and documented ability-related polarization emerging over time. Those higher in ability were more polarized in emotional responses, risk perceptions, and product-purchase intentions. This polarization was mediated by selective exposure to partisan media and selective interpretation of numeric information. In a second investigation (N=1,222), we investigated the role of factual information in reducing this ability-based polarization. Once provided information, knowledge increased, but ability-related polarization in political opinions remained despite a coming together on the facts. This persistence of polarized opinions may be explained, at least in part, by participants higher in ability engaging in greater polarized evaluation of the information. Thus, higher-ability partisans appear to engage in selective exposure, interpretation, and evaluation to support and defend their worldviews

Conceptual models used to test competing hypotheses of the depolarizing effect of knowledge (top) vs. the polarizing effect of biased evaluations (bottom)

Polarized evaluations and opinions are tested in these models as interactions with ideology (e.g., the path from verbal ability to polarized opinions is an interaction of ability and ideology such that verbal ability increases ideological polarization).</p

Effect of political ideology, stay-at-home rates, and increased risk taking in Ohio drivers during COVID-19 shutdown

In response to COVID-19, Ohio, along with many other states, enacted a stay-at-home order in March to limit the spread of the pandemic. Crashes appear to have fallen as people stayed home, but fatal crashes did not. We investigated whether increases in speeding, alcohol use, or drug use could have taken place to offset the reduction in traffic. In addition, we examined whether support for President Trump would relate to both stay-at-home compliance and rates of crashes. Stay-at-home compliance predicted lower overall crash rate, particularly for less severe crashes, but not for fatal crashes. We did not find evidence that speeding or drug-related crashes increased during the stay-at-home order, but percentage of speed-related crashes was higher in areas with greater stay-at-home compliance. Alcohol-related crashes were involved in a greater proportion of crashes during the shutdown, and as they are more severe, may explain why fatal crashes did not fall. Support for President Trump was related to lower stay-at-home compliance and increased percentage of alcohol-related crashes controlling for median income, rurality, and Appalachian region. The combination of rejection of recommendations from public health officials and increased rates of alcohol-related crashes may put a particular burden on Republicans