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 12.15.
Exceptions: There is no Brown Bag Seminar on vappuaatto, 30.4. – have a great Vappu and see you on the 7th of May!
You are welcome to join us at seminar room 524, Fabianinkatu 24 A (access via door, not courtyard), 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.
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The talk will present fresh-from-the-oven findings from a new research setting. The main objective of the CoTeachMath project is to investigate co-teachers’ professional vision through teachers’ visual attention and its relation to adapted instruction in co-taught elementary classrooms.
To ensure students’ effective learning, teachers must continuously adapt their instruction according to students’ needs. Effective teaching requires not only pedagogical but also attentional and reflective skills. To understand how the situational teacher-student or teacher-teacher interaction is constructed in authentic lessons, we need innovative but valid methods to utilize multimodal research data.
The multimodal data consists of eye-tracking recordings, classroom videos, and teachers’ stimulated recall interviews that are synchronized and analyzed by combining qualitative and statistical approaches.
Additionally the talk will present methodological implications of Haataja’s research on teachers’ visual attention and teacher-student eye contact interaction. The talk will introduce ideas that may help the researchers in planning valid and sustainable data collections with eye tracking in authentic settings.
Eeva Haataja works as a university lecturer in the Faculty of Educational Sciences in UH. She teaches math education to teacher students and supervises teaching practices and master’s and PhD students. Her main research interest is situational multimodal teacher-student interaction in mathematics education, and her research approach complements eye-tracking data, video recordings and interviews by combining statistical and qualitative analyses.
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Persons with a serious mental illness are overrepresented in prisons in many countries. Despite the advantages of a Nordic welfare state and comparatively low crime rate, overlapping problems of mental illness, substance abuse, and criminal offending are enduring problems in Finland. At the same time, because of its universal healthcare system and associated data sources, Finland affords unique opportunities to examine processes surrounding criminal offending among persons with mental illness. In this presentation, Professor Markowitz will discuss comparisons between the U.S. and Finland, his research on mental illness and crime, and then present findings from his recent collaborative project on social embeddedness and offending in Finland using population registry data. The study looks at whether persons' labor market status and living situations are associated with criminal offending in the same ways for those with and without a mental illness diagnosis.
Fred Markowitz is Professor of Sociology and Criminology at Northern Illinois University and holds the title of Dosentti at University of Helsinki. Previously, he was a National Institute of Mental Health Postdoctoral Fellow at the University of Wisconsin at Madison. His research is in the areas of crime, mental illness, homelessness, and stigma. His interdisciplinary work has been published in journals such as the American Journal of Sociology, Criminology, Journal of Health and Social Behavior, Social Psychology Quarterly, Aggression and Violent Behavior, Society and Mental Health, International Criminology, Advances in Criminological Theory, Military Psychology, Schizophrenia Bulletin, and Nordic Journal of Criminology. Professor Markowitz was a Fellow of the American Scandinavian Foundation and a Fulbright Finland Scholar at the University of Helsinki’s Institute of Criminology and Legal Policy. He is the Editor of Society and Mental Health, a journal of the American Sociological Association’s Section on Sociology of Mental Health.
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The digitisation of historical documents has provided historians with unprecedented research opportunities. Yet, the conventional approach to analysing historical documents involves converting them from images to text using OCR, a process that overlooks the potential benefits of treating them as images and introduces high levels of noise. To bridge this gap, we take advantage of recent advancements in pixel-based language models trained to reconstruct masked patches of pixels instead of predicting token distributions. Due to the scarcity of real historical scans, we propose a novel method for generating synthetic scans to resemble real historical documents. We then pre-train our model, PHD, on a combination of synthetic scans and real historical newspapers from the 1700-1900 period. Through our experiments, we demonstrate that PHD exhibits high proficiency in reconstructing masked image patches and provide evidence of our model’s noteworthy language understanding capabilities. Notably, we successfully apply our model to a historical QA task, highlighting its usefulness in this domain.
Desmond Elliot is an Associate Professor and a Villum Young Investigator at the University of Copenhagen. His group currently focuses on tokenization-free language modelling, and multilingual and multimodal processing. his research output includes widely used resources and tools such as the multilingual image description dataset (multi30K), the multimodal language understanding dataset (How2), and the pixel-based language model PIXEL.
Click here for practical information on the Brown Bag Seminar events.