The Methodological Unit organizes a weekly Brown Bag Seminar to highlight novel methodological approaches in humanities and social sciences. The idea of the meetings is to introduce methodological innovations and cutting-edge research in various disciplines in an easily accessible manner and have an interdisciplinary discussion in an easy-going atmosphere over lunch. Bring your own lunch, we bring fresh methodological topics!
Every Wednesday at 12.00.
Please note: Starting on Wednesday 11.2. the seminar is starting and ending 15 minutes earlier – 12.00 (sharp) to 13.00.
Exceptions: There is no Brown Bag Seminar on 18.2. – have a great time skiing!
You are welcome to join us at room 532, Fabianinkatu 24 A, 5th floor, or online via Zoom.
There will be a 20-minute introduction to the methodological theme, followed by an open discussion of 40 minutes. The seminars are open to everybody. We expect a multidisciplinary and methodologically curious audience from different faculties and units of the central campus. The language of the meetings can be Finnish or English.
The most important prerequisite for participation is not methodological expertise, but an open mind towards new methodological innovations and discussion across methodological and disciplinary boundaries.
Scroll down for the upcoming program of Brown Bag Seminars. To get notified on updates sign up for our mailing list or follow us on social media.
Computing is central to academic research, but the growing complexity of software development, the scale of current data sets, and the introduction of AI methods can be overwhelming for many research groups. To address these challenges, a new Research Software Engineering (RSE) group was recently established at University of Helsinki to provide hands-on specialist support for software development, high-performance computing, and data management. We help researchers make software more efficient and reusable, improve reproducibility, and gain confidence with computational methods. In this talk, I will introduce the RSE model, explain how it differs from traditional IT support, and describe the services we offer, including online help sessions, grant consultations and software development projects. RSE at University of Helsinki is still evolving: we invite researchers to help shape our services and tell us what kinds of computing support would benefit their work.
Alan Medlar leads the Research Software Engineering group at University of Helsinki. His research focuses on understanding and improving how people interact with information systems, such as search engines, recommender systems and AI-based applications. Recent work includes critical studies of evaluation practices in the recommender systems research community, and the development of novel interaction techniques to support navigation and increase user engagement in virtual reality.
Conversation Analysis (CA) is an empirical method for investigating social interaction as it unfolds on a turn-by-turn basis. Although the method has its roots in sociology, it has also significantly influenced other disciplines, including linguistics. As an empirical method focusing on the details of interaction, CA imposes specific requirements on the data used: the data should be recorded in authentic interactional situations. Earlier CA studies have typically used audio recordings, such as (landline) telephone conversations; this has generated considerable knowledge about how various linguistic resources and elements contribute to meaning-making in social actions. Recently, however, the focus has expanded from linguistic to other resources, leading to what has been termed an ‘embodied turn’ in CA research. The increasing interest in the embodied and material resources utilized by participants necessitates new data requirements. In this talk, I will briefly present CA’s analytic framework, grounded in the details of interaction, and introduce a new dataset collected for the purposes of multimodal interactional analysis.
Salla Kurhila is a professor in Interactional Linguistics at the University of Helsinki. Her research interests cover both basic and more applied research, ranging from exploring various phenomena in social interaction to developing interventions to enhance language learning.
Henri Schildt (Aalto University), in collaboration with Stine Grodal (Northeastern University)
Technological tools have always shaped research and, in turn, the theories we create. While new artificial intelligence (AI) tools offer powerful affordances for qualitative researchers, their implications for theory development remain unclear. Drawing on technology studies and the distinction between AI automation and augmentation, we recast qualitative inquiry as a socio-technically situated, fundamentally abductive process. We argue that AI should not be treated as a substitute for interpretation, but as a collaborative device that can help research teams expand, align, and justify their emerging understandings. To specify how AI can augment (rather than automate) qualitative theorizing, we unpack the analytic tasks that constitute abductive theory development and consider which may be supported by AI and which must remain human-led. We conceptualize the abductive process as involving cycles of diverging and converging on (1) the puzzle and (2) explanations for the puzzle. We theorize the AI tools to be particularly good for surfacing alternative framings, patterns, and candidate explanations, helping divergent ideas. Humans, in contrast, retain responsibility for convergence: scrutinizing suggestions, exercising judgment, and selecting interpretations that form coherent theoretical contributions.
Henri Schildt is a professor of strategy with a joint appointment at the Aalto School of Business and the School of Science. His research interests span artificial intelligence, strategic change, and social sustainability. His work has been published in leading academic journals, including Organization Studies, Organization Science, and Strategic Management Journal. He is currently co-leading the research project Smarter Work with Generative Artificial Intelligencethat examines how companies are integrating large language models in their internal processes and services. Henri is also the founder of Skimle.com, an AI-native qualitative analysis service.