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Judges Are from Mars, Pro Se Litigants Are from Venus: Predicting Decisions from Lay Text

机译:法官来自火星,Pro SE诉讼孩来自金星:预测来自店铺的决定

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Access to justice could be significantly expanded if decision support systems were able to accurately interpret statements of fact by pro se (self-represented) litigants. Prior research, which has demonstrated that case decisions can often be predicted by machine-learning models trained on judges' statements of facts, suggests the hypothesis that these same learning algorithms could be effectively applied to pro se litigants' fact statements. However, there has been a dearth of corpora on which to test this hypothesis. This paper describes an experiment testing the ability to predict the outcome of pro se litigants' complaints on a corpus of 5,842 cases initiated by citizen complaints. The results of this experiment were strikingly negative, suggesting that fact statements by unguided pro se litigants are far less amenable to simple machine-learning techniques than judges' texts and appearing to disconfirm the hypothesis above.
机译:如果决策支持系统能够通过Pro SE(自代表)诉讼当事人准确地解释事实的陈述,可以大大扩展司法。 现有研究证明,案例决策通常可以通过在法官对事实陈述的机器学习模型中预测,表明这些相同的学习算法可以有效地应用于Pro SE诉讼的事实陈述的假设。 然而,有一个关于测试这一假设的荒谬。 本文介绍了一个实验,测试了预测Pro SE诉讼人的结果对由公民投诉发起的5,842例案件的诉讼结果的能力。 这种实验的结果非常消极,暗示通过守惑的专业诉讼剂的事实陈述比法官的文本更少,并且出现在上面的假设中,对简单的机器学习技术较小。

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