论文标题
法律和政治立场检测SCOTUS语言
Legal and Political Stance Detection of SCOTUS Language
论文作者
论文摘要
我们使用自动立场检测分析了美国最高法院的公开文件。在工作的第一阶段，我们研究了法院面向公共的语言是政治性的程度。我们使用口头参数转录本提出并计算SCOTUS法官的两个不同的意识形态指标。然后，我们将这些基于语言的指标与最高法院和公众意识形态的现有社会科学措施进行比较。通过这种跨学科分析，我们发现对公众舆论更敏感的大法官倾向于在口头论据中表达其意识形态。该观察结果提供了一种新的证据，以支持最高法院司法行为的态度变化假设。作为这种政治立场检测的自然扩展，我们建议使用新的数据集SC-Stance提出更专业的法律立场检测任务，该任务将书面意见与法律问题相匹配。我们使用对法律文件培训的语言适配器在此数据集上发现竞争性能。
We analyze publicly available US Supreme Court documents using automated stance detection. In the first phase of our work, we investigate the extent to which the Court's public-facing language is political. We propose and calculate two distinct ideology metrics of SCOTUS justices using oral argument transcripts. We then compare these language-based metrics to existing social scientific measures of the ideology of the Supreme Court and the public. Through this cross-disciplinary analysis, we find that justices who are more responsive to public opinion tend to express their ideology during oral arguments. This observation provides a new kind of evidence in favor of the attitudinal change hypothesis of Supreme Court justice behavior. As a natural extension of this political stance detection, we propose the more specialized task of legal stance detection with our new dataset SC-stance, which matches written opinions to legal questions. We find competitive performance on this dataset using language adapters trained on legal documents.
