Guiding jurors’ damage award decisions: Experimental investigations of approaches based on theory and practice.

Abstract

Theory and practitioner “scaling” advice informed hypotheses that guidance to mock jurors should (a) increase validity (vertical equity), decrease variability (reliability), and improve coherence in awards; (b) improve subjective experience of jurors’ decision-making (rated helpfulness, confidence, and difficulty); and (c) have the greatest impact when it includes both verbal and numerical benchmarks. Three mock juror experiments (N = 197 students, N = 476 Amazon Mechanical Turk workers, and N = 391 students) tested novel scaling approaches and predictions from the Hans-Reyna model of damage award decision-making. Jurors reviewed a legal case and provided a dollar award to compensate plaintiffs for pain and suffering following concussions. Experiments varied injury severity (low vs. high) and the plaintiff attorney’s guidance (no guidance, verbal guidance, numerical guidance, and verbal-plus-numerical guidance) between subjects. Results support predictions that, even without guidance, mock jurors appropriately categorize the gist of injuries as low or high severity, and dollar awards reflect that gist. Participants gave a higher award for more severe injuries, indicating that they extracted the qualitative gist of damages. Also, as expected, guidance, particularly verbal-plus-numerical guidance, had beneficial effects on jurors’ subjective experience, with participants reporting that it was a helpful aid in decision-making. Numerical guidance, both with and without verbal guidance, reduced award variability in severe injury cases in all three experiments. Scaling guidance did not improve the already strong gist-verbatim correspondence or award validity. Both grasping the gist of damages and mapping that gist onto numbers are important, but jurors appear to benefit from assistance with numerical mapping.

Alternative punishments: How laypeople and judges impose alternative noncarceral sanctions.

“…Laypeople showed substantial uncertainty about the precise amount of these sanctions to impose, as reflected in Figure 4, with values stretching many orders of magnitude. This finding is consistent with research into jury damage awards for emotional damages, which show substantial variance unless guided by anchors and instructions (Hans et al, 2022). However, lay participants broadly agreed that the value should be above zero, which is where the quantities imposed in real sentences cluster.…”

Adaptive lie detection and perceived prevalence of false reports in evaluation of sexual offense allegations.

“…These results suggest that it is the gist of information on prevalence, rather than verbatim information (precise prevalence estimates) that is relied on and reflected in legal lie detection judgements (although absent interference gist judgements are likely to correspond well to verbatim judgements; see Hans et al, 2022). In fact, while changing gists influenced judgements (discussed above), exploratory analyses showed that relationships between precise prevalence estimates and lie detector judgements were nonsignificant where information on prevalence framed to emphasize a particular gist was given.…”

“…Gist extracted from information often corresponds with verbatim information (e.g., a higher verbatim number is more likely to be encoded as “high” than a lower verbatim number; see Hans et al, 2022). As a result, errors in verbatim representations are likely to correspond with inappropriately assigned gist (gist assigned based on misunderstanding).…”

The power of meaningful numbers: Attorney guidance and jury deliberation improve the reliability and gist validity of damage awards.

“…Prior research focused on assisting jurors in translating their qualitative gist into a quantitative award for the case as a whole. In other words, both the anchor provided by the foreperson (Hans et al, 2018; Reyna et al, 2015) and the scaling guidance (Hans et al, 2022) had jurors focus on the value of the whole case. However, research on numerical cognition suggests that people struggle with discriminating among large numbers (Landy et al, 2013; Reyna & Brainerd, 2023).…”