In this case study, we reflect on our journey through a major revision of our streaming video reserve guidelines, informed by an environmental scan of comparable library services and current copyright best practices. Once the guidelines were revised, we developed an implementation plan for communicating changes and developing training materials to both instructors and internal library staff. We share our navigation strategies, obstacles faced, lessons learned, and ongoing challenges. Finally, we map out some of our future directions for improving and streamlining our services.
Although they have distinct missions, public libraries and academic libraries serve overlapping populations and can leverage their institutional strengths through collaboration. These diverse partnerships include sharing resources through consortia, joint-use libraries, and shared programming, such as introducing students to public library collections as resources for theses. For the scholarly communication librarian, collaborating with public libraries provides opportunities to educate about the ethical and legal use of information, advocate for the promotion and use of open resources and pedagogies, and interact with communities, particularly in rural areas, that are traditionally underserved by academic libraries. We’ll share two personal examples of the intersection between scholarly communication and public libraries.
‘Describing at Large Their True and Lively Figure, their several Names, Conditions, Kinds, Virtues (both Natural and Fanciful), Countries of their Species, their Love and Hatred to Humankind, and the wonderful work of Natural Selection in their Evolution, Preservation, and Destruction.
Interwoven with curious variety of Creative Narrations out of Academic Literatures, Scholars, Artists, Scientists, and Poets. Illustrated with diverse Graphics and Emblems both pleasant and profitable for Students of all Faculties and Professions.’
The importance of nonverbal communication has been well established through several theories including Albert Mehrabian's 7-38-55 rule that proposes the respective importance of semantics, tonality and facial expressions in communication. Although several studies have examined how emotions are expressed and preceived in communication, there is limited research investigating the relationship between how emotions are expressed through semantics and facial expressions. Using a facial expression analysis software to deconstruct facial expressions into features and a K-Nearest-Neighbor (KNN) machine learning classifier, we explored if facial expressions can be clustered based on semantics. Our findings indicate that facial expressions can be clustered based on semantics and that there is an inherent congruence between facial expressions and semantics. These results are novel and significant in the context of nonverbal communication and are applicable to several areas of research including the vast field of emotion AI and machine emotional communication.