Sitting in Judgment: The Working Lives of Judges

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Sitting in Judgment: The Working Lives of Judges

Sitting in Judgment: The Working Lives of Judges

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Machotka, P. Body Movement as Communication. Dialogues Behav. Sci. Res. 1965, 2, 33–66. [ Google Scholar]

Faul, F.; Erdfelder, E.; Lang, A.-G.; Buchner, A. G* Power 3: A Flexible Statistical Power Analysis Program for the Social, Behavioral, and Biomedical Sciences. Behav. Res. Methods 2007, 39, 175–191. [ Google Scholar] [ CrossRef] Matsumoto, D.; Hwang, H.C.; Skinner, L.G.; Frank, M.G. Positive Effects in Detecting Lies from Training to Recognize Behavioral Anomalies. J. Police Crim. Psychol. 2014, 29, 28–35. [ Google Scholar] [ CrossRef] Simmons, J.P.; Simonsohn, U. Power Posing: P-Curving the Evidence. Psychol. Sci. 2017, 28, 687–693. [ Google Scholar] [ CrossRef][ Green Version]Hartwig, M.; Bond, C.F. Lie Detection from Multiple Cues: A Meta-Analysis. Appl. Cogn. Psychol. 2014, 28, 661–676. [ Google Scholar] [ CrossRef] Matsumoto, D.; LeRoux, J.; Wilson-Cohn, C.; Raroque, J.; Kooken, K.; Ekman, P.; Yrizarry, N.; Loewinger, S.; Uchida, H.; Yee, A. A New Test to Measure Emotion Recognition Ability: Matsumoto and Ekman’s Japanese and Caucasian Brief Affect Recognition Test (JACBART). J. Nonverbal. Behav. 2000, 24, 179–209. [ Google Scholar] [ CrossRef] Holm, H.J.; Kawagoe, T. Face-to-Face Lying—An Experimental Study in Sweden and Japan. J. Econ. Psychol. 2010, 31, 310–321. [ Google Scholar] [ CrossRef] Ekman, P. Microexpression Training Tool, Subtle Expression Training Tool; A Human Face: Salt Lake City, UT, USA, 2002. [ Google Scholar]

Masip, J.; Alonso, H.; Garrido, E.; Herrero, C. Training to Detect What? The Biasing Effects of Training on Veracity Judgments. Appl. Cogn. Psychol. 2009, 23, 1282–1296. [ Google Scholar] [ CrossRef] Funk, F.; Todorov, A. Criminal Stereotypes in the Courtroom: Facial Tattoos Affect Guilt and Punishment Differently. Psychol. Public Policy Law 2013, 19, 466–478. [ Google Scholar] [ CrossRef][ Green Version] Zloteanu, M.; Krumhuber, E.G. Expression Authenticity: The Role of Genuine and Deliberate Displays in Emotion Perception. Front. Psychol. 2021, 11, 611248. [ Google Scholar] [ CrossRef] Requires completion of the main quest Here Lies the Abyss, and the Wardens must still be present in Orlais.) Green, D.; Swets, J. Signal Detection Theory and Psychophysics; John Wiley and Sons: New York, NY, USA, 1966; ISBN 0-932146-23-6. [ Google Scholar]Donaldson, W. Measuring Recognition Memory. J. Exp. Psychol. Gen. 1992, 121, 275–277. [ Google Scholar] [ CrossRef] Michalak, J.; Mischnat, J.; Teismann, T. Sitting Posture Makes a Difference-Embodiment Effects on Depressive Memory Bias. Clin. Psychol. Psychother. 2014, 21, 519–524. [ Google Scholar] [ CrossRef] When I was a child, my parents would take me to the planetarium, and we would sit in the dark and it was as if I was on a spaceship, on my way to another world, to meet people on other planets. Gudjonsson, G.H. The Psychology of Interrogations, Confessions and Testimony; John Wiley & Sons: Hoboken, NJ, USA, 1992; ISBN 0-471-92663-9. [ Google Scholar] As the current interest is on how postures can impact the decoding of behavioral cues, we focused on the recognition of brief facial expressions of emotions—microexpressions—proposed in the deception literature as a source of diagnostic information [ 35, 36]. Microexpressions are involuntary full-faced expressions occurring at less than 0.5 of a second, said to reflect the genuine emotional state of the sender [ 35, 37]. It is argued that liars and truth-tellers experience different emotions, which result in differences in the facial expressions each produces [ 35]. Thus, the assumption is that a perceptive judge can utilize these cues to accurately determine the veracity of a sender [ 35].

Price, T.F.; Harmon-Jones, E. The Effect of Embodied Emotive States on Cognitive Categorization. Emotion 2010, 10, 934–938. [ Google Scholar] [ CrossRef][ Green Version] Zloteanu, M. Reconsidering facial expressions and deception detection. In Handbook of Facial Expression of Emotion; Freitas-Magalhaes, A., Borod, J., Eds.; FEELab Science Books & Leya: Porto, Portugal, 2020; Volume 3, pp. 238–284. ISBN 978-84-10-74697-8. [ Google Scholar] When judging the veracity of others, people tend to rely on nonverbal behavior to help make their decisions [ 31, 32]. Several prevalent cross-cultural beliefs exist about cues to detecting deceit, such as liars self-touch, avert their gaze, and fidget more than truth-tellers [ 32]. Regardless of their diagnostic value (which is usually quite poor; [ 33, 34]), people’s beliefs regarding such nonverbal behaviors are strong [ 32]. While she can be recruited as an agent for the Inquisition, she will not appear in the Inquisition perk list. Judgment OptionsDriskell, J.E. Effectiveness of Deception Detection Training: A Meta-Analysis. Psychol. Crime Law 2012, 18, 713–731. [ Google Scholar] [ CrossRef] For the effect of posture on microexpression recognition, the METT scores (%) were to be analyzed using a one-way, between-subjects ANCOVA, with Posture (Open or Closed) as the between-subjects factor and trait Empathy as the covariate. The relationship between deception detection accuracy (overall, lies, and truth) and facial expression recognition are assessed using non-parametric (Spearman’s rho) correlations. Adds Florianne to the throne room as a court jester NPC. She will appear periodically next to the throne. She will make sarcastic remarks if the Inquisitor approaches her.

We used both high-stakes and low-stakes lie videos in this study for two reasons. Stakes are the rewards to the liar for escaping detection and/or the punishment that they would receive for being caught. Stakes make controlling one’s behavior channels more difficult [ 35] and increase the likelihood of displaying unintended behavioral cues associated with lying, both in quantity and intensity [ 36, 65], which can make deception detection easier [ 66, 67]. If the posture manipulation affects the attention judges give to behavioral cues a difference in accuracy should be more pronounced for the high-stake lies. The second benefit is uncovering the stability and generalizability of the posture effect on different lie scenarios. It should be noted that the role of stakes in lie detection is a debated topic. The meta-analysis by DePaulo and colleagues [ 33] reported an effect of motivation (a close proxy to stakes) on the detectability of deception, however, the more recent meta-analysis by Hartwig and Bond [ 34] failed to replicate this finding. Turned herself in after Here Lies the Abyss. Asked to be judged for her crime of murder, (abetting in a blood sacrifice). You must also complete the war table operation ‘Find Crestwood’s Mayor’ before this judgment becomes available. Judgment Options Jordan, S.; Brimbal, L.; Wallace, D.B.; Kassin, S.M.; Hartwig, M.; Street, C.N.H. A Test of the Micro-Expressions Training Tool: Does It Improve Lie Detection? J. Investig. Psychol. Offender Profiling 2019, 16, 222–235. [ Google Scholar] [ CrossRef]Veenstra, L.; Schneider, I.K.; Koole, S.L. Embodied Mood Regulation: The Impact of Body Posture on Mood Recovery, Negative Thoughts, and Mood-Congruent Recall. Cogn. Emot. 2017, 31, 1361–1376. [ Google Scholar] [ CrossRef] Beattie, G.; Shovelton, H. Mapping the Range of Information Contained in the Iconic Hand Gestures That Accompany Spontaneous Speech. J. Lang. Soc. Psychol. 1999, 18, 438–462. [ Google Scholar] [ CrossRef] Aamodt, M.G.; Custer, H. Who Can Best Catch a Liar? Forensic Exam. 2006, 15, 6–11. [ Google Scholar] A repeated-measures ANCOVA was conducted on Posture (Open or Closed) and Stakes (High and Low) while controlling for individual differences in empathy. A marginal main effect of stakes was observed ( F(1, 29) = 4.04, p = 0.053, η P 2 = 0.119) suggesting that the High-Stakes videos ( M = 0.61, SD = 0.16) were easier to classify than the Low-stakes videos ( M = 0.51, SD = 0.21). While judges in the Open posture ( M = 0.59, SD = 0.15) had higher accuracy than judges in the Closed posture ( M = 0.55, SD = 0.11), the difference was not statistically significant ( F< 1, p = 0.335). The Stakes X Posture interaction, while also in the predicted direction—the difference between the Open and Closed posture on accuracy being more pronounced for the High-Stakes videos ( M diff = 5.15%) than the Low-Stakes videos ( M diff = 3.60%)—was not statistically significant ( F< 1, p = 0.948). Empathy was not found to affect the results ( Fs < 1, p = 0.644). Concerning gazing behavior, adopting an open posture resulted in less attention being given to the nonverbal behavior of senders, contrasting what the literature would predict. It was found that judges placed in an open posture spent less time gazing at senders. Specifically, they focused less on the hands of senders. Potentially, open posture judges were faster and/or more efficient at extracting information from nonverbal signals and thus required less time looking at senders, or they relied less on nonverbal information for their veracity judgments.



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