Applause Culture in Symphonic Concert Audiences

Niels Christian Hansen, assistant professor, Interacting Minds Centre, Aarhus University

Abstract: Applause is a mysterious, social phenomenon entailing spontaneous, ritualised expression of enthusiasm in response to exhibits of impressive skill in temporal arts such as theatre, acrobatics, and musical concerts. Although clapping behaviours arise universally in infants, the exact modes of expressing enthusiasm vary widely across cultures. For example, folk beliefs amongst classical music fans suggest that standing ovations arise especially frequently in North America, that synchronised clapping emerges more easily in Scandinavia, and that loud vocalisations are a more common part of Mediterranean audience behaviour. This survey study conducted on frequent attendees of symphony concerts in Denmark, Italy, and the United States provides the first-ever empirical test of anecdotal knowledge relating to applause culture in classical music. The outcomes of this seed project will contribute towards ensuring funding for a larger-scale research agenda with the goal of promoting data-based artistic and business-related decision-making within the creative and cultural sector.

Collaborating with Large Language Models: Prompting and the Future of Computational Thinking

Rebekah Baglini, associate professor, Department of Linguistics, Cognitive Science and Semiotics, Aarhus University; Center for Humanities Computing, Aarhus University
Arthur Hjorth, assistant professor, Department of Management, Aarhus University

Abstract: This project will investigate prompt engineering around large language models (LLMs) and the skills required to execute the prompt engineering process. The project will focus on designing a web interface, creating LLM challenges, and recruiting ML experts and novices as participants for observational and think-aloud protocol data collection. The data will be analyzed to identify prompt engineering process components, debugging approaches, perceived difficulties, and prior knowledge used to make sense of the process. The outcomes of the project will form the foundation for larger research instruments and grant applications. The interdisciplinary nature of the project draws on expertise from several different disciplines, including natural language processing, machine learning/engineering, learning sciences and education, and linguistics.

Discriminating eyes: Exploring selection biases in visual processing of resumes

Caroline Kjær Børsing, PhD student, Department of Management, Aarhus University

Abstract: Discrimination in hiring can have detrimental consequences for underrepresented groups’ access to employment, but the mechanisms behind such discrimination are not well understood. Previous research has not been able to provide a clear account of how screeners visually process resume information, and whether this differs across candidate attributes and screener motivations. Research on selective attention suggests that people are skilled at navigating their visual environment and avoiding information that conflicts with their values or beliefs, if the information appearance is predictable. Building on this, we will investigate how screeners visually process resumes when resume appearance is predictable vs. unpredictable, and whether this leads to more diverse hires. We will test this in the lab using eye-tracking and by utilizing a more naturalistic resume construction. After assessing 100 fictious resumes for an entry-level clerk position, screeners will complete a questionnaire to assess 1) how their gaze patterns match current beliefs about what a good candidate is, and 2) whether they engage in injurious behavior without realizing it. The proposed experimental design allows for insigths into elicited implicit biases in screeners’ processing of resumes, and a comparison between screeners’ visual biases and their final assessment of candidates and self-awareness of their own biases. Understanding the underlying foundations of discrimination is expected to inform efforts to reduce discrimination in the hiring.

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