标题： 欧盟立法中监管声明的计算识别 显示英文标题

标题： Computational Identification of Regulatory Statements in EU Legislation

摘要： 识别立法中的监管声明对于制定衡量立法监管密度和严格性的指标很有用。 计算方法对于从不断增长的欧盟立法中扩展此类声明的识别非常有价值，涵盖了1952年至2023年间约180,000项发布的法律行为。 过去关于提取这些声明的工作在定义什么是监管声明的宽容度上各不相同。 在这项工作中，我们基于制度语法工具提供了特定于我们的目的的定义。 我们开发并比较了两种对比的方法来自动识别欧盟立法中的此类声明，一种基于依存句法分析，另一种基于基于变换器的机器学习模型。 我们发现这两种方法表现相似，准确率分别为0.58和0.80。 高准确率和不过高的同意率表明可以结合两种方法的优点。 显示英文摘要

摘要： Identifying regulatory statements in legislation is useful for developing metrics to measure the regulatory density and strictness of legislation. A computational method is valuable for scaling the identification of such statements from a growing body of EU legislation, constituting approximately 180,000 published legal acts between 1952 and 2023. Past work on extraction of these statements varies in the permissiveness of their definitions for what constitutes a regulatory statement. In this work, we provide a specific definition for our purposes based on the institutional grammar tool. We develop and compare two contrasting approaches for automatically identifying such statements in EU legislation, one based on dependency parsing, and the other on a transformer-based machine learning model. We found both approaches performed similarly well with accuracies of 80% and 84% respectively and a K alpha of 0.58. The high accuracies and not exceedingly high agreement suggests potential for combining strengths of both approaches.