Judgements about others' behavior is often made based on the relative rank of that behavior. We investigated this in the new domain of pro-environmental behavior, specifically for the categories of energy and water consumption, food (meat) consumption and transport choice. Using unimodal and bimodal distributions, we experimentally manipulated three fictional individuals' (common points) rank positions while keeping their absolute frequency of behaviors constant. Consistent with previous literature, participants' judgements about these people's pro-environmental behavior differed based on their rank position. Rank effects were not moderated by the perceived Importance of others' behavior, the perceived Visibility of the behavior, or the perceived level of Control. The results of this experiment are in line with a Decision by Sampling account of judgments of pro-environmental behavior, and set a foundation for future research seeking to conduct behavioral interventions (such as rank-based nudges) within this domain. Prior to this, however, future studies should investigate whether the smaller effect sizes found in this experiment, compared to those seen in previous research, are attributable to methodological differences, or the domain itself.

Decisions about extinction risks are ubiquitous in everyday life and for our continued existence as a species. We introduce a new risky-choice task that can be used to study this topic: The Extinction Gambling Task. Here, we investigate two versions of this task: a Keep variant, where participants cannot accumulate any more earnings after the extinction event, and a Lose variant, where extinction also wipes out all previous earnings. We derive optimal solutions for both variants and compare them to behavioural data. Our findings suggest that people understand the difference between the two variants and their behaviour is qualitatively in line with the optimal solution. Further, we find evidence for risk-aversion in the Keep condition but not in the Lose condition. We hope that this task can facilitate further research on this vital topic.

The studies apply a Bayesian source credibility model to a legal setting to test epistemic influence of witnesstestimonies. The model amalgamates perceived witness trustworthiness and access to accurate information as independentelements that describe and predict the impact of the testimony of that particular witness.Across two studies, the model enjoys a good fit with observed posterior ratings of the likelihood of guilt (study 1: R2 = .867,study 2: R2 = .701). Study 1 (n = 101) employs different witness types and reports whilst study 2 (n = 102) employs differentwitness types, access to accurate information, and reports.The studies suggest the applicability of a Bayesian source credibility model in a legal setting to account for the impactof different witness types. We show that participants are sensitive to the type of witness and that different witnesses have apredictable impact on the perception of the testimony.

A commonly suggested solution to reduce misinterpretations of verbal probability expressions in risk communications is to use a verbal-numerical (mixed format) approach, but it is not known whether this increases understanding over and above a purely numerical format. Using the ‘which outcome’ methodology (Teigen & Filkuková, 2013), we examined the effect of using verbal, numerical and mixed communication formats, as well as investigating whether marking outcomes as salient would alter the outcomes people perceived as ‘unlikely’ or having a 20% chance of occurring. We observed no effect of saliency, but replicated previous findings, with general preference for values at the high end of a distribution (including maximum/above maximum values) present in both verbal and mixed communication formats. This demonstrates the relevance of these findings for real-world consequential risk communication. Whilst the estimates differed between the mixed and numerical formats, we found that the mixed format yielded the more accurate estimates.