研究中国卫生产业政策工具的识别和演变
1School of Economics, Hebei University, Baoding, China.
Frontiers in public health
|March 5, 2024
概括
使用BERT自动识别卫生政策工具提高了准确性. 供给和环境政策比需求政策更为普遍,随着时间的推移,主题焦点不断变化.
科学领域:
- 卫生政策分析 卫生政策分析
- 自然语言处理自然语言处理.
- 计算社会科学 计算社会科学
背景情况:
- 有效的卫生产业政策对于省级发展至关重要.
- 手动确定政策工具是耗时的,缺乏全面性.
- 自动化方法可以提高政策分析的速度和范围.
研究的目的:
- 开发一种自动化方法来识别卫生政策工具,使用双向编码器表示从变压器 (BERT) 模型.
- 分析中国各省政策工具的时间和空间演变.
- 调查卫生政策重点中的专题转变.
主要方法:
- 应用BERT模型用于自动化政策工具分类.
- 利用焦点损失来解决数据集不平衡的问题.
- 基于时间,空间和主题的政策演变分析.
主要成果:
- 伯特模型显著提高了政策工具的分类准确性.
- 供给和环境政策工具被发现比需求侧工具更为普遍.
- 在四个主要经济地区,政策工具表现出类似的组织模式.
- 观察到政策关注从医疗保健,医学和污染到其他主题的逐渐转移.
- 政策重点仍然集中在医疗服务行业,对制造业的关注减少.
结论:
- 通过BERT自动识别政策工具提供了更有效和更全面的方法.
- 了解政策工具的流行和演变有助于基于证据的政策制定.
- 调查结果提供了对中国卫生部门的区域政策变化和主题趋势的见解.
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