The legal‐normative conditions of police transparency: A configurational approach to open data adoption using qualitative comparative analysis
研究美国122个警察局开放数据采纳的组态条件，发现三种创新路径：任务驱动、城市利益相关者趋同和网络学习，对政策制定者和公共管理者有参考价值。
In the United States, there is mounting political pressure on public agencies to publish internal data. But transparency policy innovation brings a unique set of legal and normative challenges regarding how sensitive information will be used. It is therefore an open question as to what legal‐normative conditions favour innovation. Are there specific kinds of laws, rules, or normative conditions that are related to adoption of new, potentially risky, transparency policies? In this article, qualitative comparative analysis with secondary data from multiple sources is used to find out what configurations of conditions are associated with open data use in 122 police departments. Results show three different paths to innovation among police departments: mandate driven, city‐stakeholder convergence, and network learning. The findings are examined and developed through interviews with experts from a national police transparency initiative.