Objective: We examined how probability of conviction affects the maximum plea sentence mock defendants will accept. Hypothesis: Relying on Prospect Theory (Kahneman & Tversky, 1979), we hypothesized that, relative to the expected value of trial, participants would need increasingly better sentences as conviction probability increased and would settle for sentences worse than the expected value of trial when probability was very low. Method: We manipulated conviction probability and potential trial sentence in a series of three between-subjects experiments, with Amazon Mechanical Turk participants assigned to the role of guilty defendants. Participants were majority White (75-82%) and non-Hispanic (92-94%); approximately half (45-51%) identified as female. Study 1 (N = 681) explored the effects of conviction probability (.05, .15, .50, .85, .90) and potential trial sentence (5, 20 years) on the maximum sentence accepted in exchange for a plea. Study 2 (N = 343; X¯age = 37.5) clarified results of Study 1 for the upper range of probabilities for two potential trial sentences (5, 10 years). Study 3 (N = 1,035; X¯age = 37.6) replicated the effects of probability (.05, .10, .15, .50, .85, .90) and potential trial sentence (5, 10 years). Results: Across all three studies, participants wanted increasingly better deals (relative to the expected value of trial) as conviction probability increased. For example, in Study 3, when probability of conviction was 0.90, plea sentences were, on average, 58% better than the expected value of trial; in contrast, when the probability was 0.05, sentences that were nearly 4 times the expected value of trial were acceptable. Conclusions: The most commonly used model of plea decision-making, Shadow of the Trial (SOT) (Mnookin & Kornhauser, 1979), assumes a direct and constant linear relationship between conviction probability and plea sentence. In contrast, our data suggest that the way conviction probability affects mock defendants' appraisals of plea offers may change across the probability spectrum. These results can facilitate development of a more comprehensive model of plea decision-making. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

中文翻译：

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定罪概率的悖论：随着定罪风险的增加，模拟被告希望获得更好的交易。

目的：我们研究了定罪的概率如何影响模拟被告接受的最大认罪判决。假设：基于预期理论（Kahneman＆Tversky，1979），我们假设，相对于审判的期望值，随着定罪概率的增加，参与者将需要越来越多的句子，并且当概率降低时，与判决的期望值相比，判决的结果会更差。非常低。方法：我们在一系列三个受试者之间的实验中操纵了定罪概率和可能的审判句子，其中将Amazon Mechanical Turk的参与者指定为有罪的被告。参加者为白人（75-82％）和非西班牙裔（92-94％）。大约一半（45-51％）被确定为女性。研究1（N = 681）探索了定罪概率的影响（.05，.15，.50，.85，。90）以及潜在的审判判决（5年，20年），以换取辩护的最高刑期。研究2（N = 343； Xage = 37.5）澄清了研究1中两个潜在审判句子（5，10年）的较高概率范围的结果。研究3（N = 1,035； Xage = 37.6）复制了概率（.05，.10，.15，.50，.85，.90）和潜在审判判决（5年，10年）的影响。结果：在所有这三项研究中，随着定罪概率的增加，参与者希望获得越来越多的优惠（相对于审判的预期价值）。例如，在研究3中，当定罪概率为0.90时，认罪判决平均比审判的预期价值高58％；相反，当概率为0.05时，可接受接近审判预期值4倍的句子。结论：辩诉决策最常用的模型是“审判的阴影”（SOT）（Mnookin＆Kornhauser，1979），它假定定罪概率与辩诉句之间存在直接且恒定的线性关系。相反，我们的数据表明，定罪概率影响模拟被告对认罪提议评估的方式可能会在整个概率谱中发生变化。这些结果可以促进开发更全面的辩诉决策模型。（PsycInfo数据库记录（c）2021 APA，保留所有权利）。对辩护要约的评估可能会在整个概率范围内发生变化。这些结果可以促进开发更全面的辩诉决策模型。（PsycInfo数据库记录（c）2021 APA，保留所有权利）。对辩护要约的评估可能会在整个概率范围内发生变化。这些结果可以促进开发更全面的辩诉决策模型。（PsycInfo数据库记录（c）2021 APA，保留所有权利）。