Objective: This study seeks to gain initial insight into what is talked about and whose voices are heard at Medical Library Association (MLA) annual meetings. Methods: Meeting abstracts were downloaded from the MLA website and converted to comma-separated values (CSV) format. Descriptive analysis in Python identified the number of presentations, disambiguated authors, author collaboration, institutional affiliation type, and geographic affiliation. Topics were generated using Mallet's Latent Dirichlet Allocation algorithm for topic modeling. Results: There were 5,781 presentations at MLA annual meetings from 2001–2019. Author disambiguation resulted in approximately 5,680 unique authors. One thousand ninety-three records included a hospital-related keyword in the author field, and 4,517 records included an academic-related keyword. There were 438 presentations with at least 1 international author. The topic model identified 16 topics in the MLA abstract corpus: events, electronic resources, publications, evidence-based practice, collections, academic instruction, librarian roles and relationships, technical systems, special collections, general instruction, literature searching, surveys, research support, community outreach, patient education, and library services. Conclusions: Academic librarians presented more frequently than hospital librarians, though more research should be done to determine if this discrepancy was disproportionate to hospital librarians' representation in MLA. Geographic affiliation was concentrated in the United States and appeared to be related to population density. Health sciences librarians in the early twenty-first century are spending more time at MLA annual meetings talking about communities, relationships, and visible services, and less time talking about library collections and operations. Further research will be needed to boost the participation of underrepresented members.

中文翻译：

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当我们谈论医学图书馆事业时，我们在谈论什么：医学图书馆协会年会摘要分析，2001-2019。

目的：本研究旨在初步了解医学图书馆协会 (MLA) 年会上讨论的内容和听到的声音。方法：会议摘要从 MLA 网站下载并转换为逗号分隔值 (CSV) 格式。Python 中的描述性分析确定了演示文稿的数量、明确的作者、作者合作、机构隶属类型和地理隶属关系。主题是使用 Mallet 的潜在狄利克雷分配算法生成的，用于主题建模。结果：从 2001 年到 2019 年，MLA 年会上共有 5,781 场演讲。作者消歧产生了大约 5,680 个独特的作者。193 条记录在作者字段中包含与医院相关的关键字，4,517 条记录包含与学术相关的关键字。至少有 1 位国际作者参加了 438 场演讲。主题模型确定了 MLA 抽象语料库中的 16 个主题：事件、电子资源、出版物、循证实践、馆藏、学术指导、图书馆员的角色和关系、技术系统、特殊馆藏、一般指导、文献检索、调查、研究支持、社区外展、患者教育和图书馆服务。结论：学术图书馆员比医院图书馆员更频繁地出现，尽管应该做更多的研究来确定这种差异是否与医院图书馆员在 MLA 中的代表性不成比例。地理归属集中在美国，似乎与人口密度有关。21 世纪初的健康科学图书馆员在 MLA 年会上花费更多时间讨论社区、关系和可见服务，而较少时间讨论图书馆馆藏和运营。需要进一步研究以促进代表性不足的成员的参与。