Google Search is an important way that people seek information about politics, and Google states that it is ``committed to providing timely and authoritative information on Google Search to help voters understand, navigate, and participate in democratic processes.'' This paper studies the extent to which government-maintained web domains are represented in the online electoral information environment, as captured through 3.45 Google Search result pages collected during the 2022 US midterm elections for 786 locations across the United States. Focusing on state, county, and local government domains that provide locality-specific information, we study not only the extent to which these sources appear in organic search results, but also the extent to which these sources are correctly targeted to their respective constituents. We label misalignment between the geographic area that non-federal domains serve and the locations for which they appear in search results as algorithmic mistargeting, a subtype of algorithmic misjudgement in which the search algorithm targets locality-specific information to users in different (incorrect) locations. In the context of the 2022 US midterm elections, we find that 71% of all occurrences of state, county, and local government sources were mistargeted, with some domains appearing disproportionately often among organic results despite providing locality-specific information that may not be relevant to all voters. However, we also find that mistargeting often occurs in low ranks. We conclude by considering the potential consequences of extensive mistargeting of non-federal government sources and argue that ensuring the correct targeting of these sources to their respective constituents is a critical part of Google's role in facilitating access to authoritative and locally-relevant electoral information.

翻译：谷歌搜索是人们获取政治信息的重要途径，谷歌公司宣称其"致力于通过谷歌搜索提供及时、权威的信息，以帮助选民理解、参与民主进程并顺利行使投票权"。本文通过分析2022年美国中期选举期间针对全美786个地区采集的3.45万页谷歌搜索结果，研究了政府运营网站在线选举信息环境中的呈现程度。聚焦于提供地域特定信息的州、县及地方政府网站，我们不仅考察了这些信源在自然搜索结果中的出现频率，更深入分析了它们是否准确匹配对应选区的选民需求。我们将非联邦政府网站服务地域与其实际出现搜索结果的地理区域之间的错配现象定义为算法误靶——这是算法误判的一种子类型，表现为搜索引擎算法将地域特定信息错误地推送给不同（非对应）地区的用户。在2022年美国中期选举的实证研究中，我们发现71%的州、县及地方政府信源呈现存在误靶现象，部分网站尽管提供的地域信息可能不适用于所有选民，却在自然搜索结果中呈现比例异常偏高。但研究同时表明，误靶现象多集中于搜索结果靠后的低排名位置。最后，本文探讨了非联邦政府信源大规模误靶可能引发的后果，并论证确保这些信源准确匹配对应选区选民，是谷歌在促进权威性、地域相关性选举信息获取过程中应当承担的关键责任。