RLMgB612 Cross-cultural research based on existing data

Faculty of Arts
Autumn 2025
Extent and Intensity
1/1/0. 5 credit(s). Type of Completion: k (colloquium).
Teacher(s)
Mgr. et Mgr. Eva Kundtová Klocová, Ph.D. (lecturer)
Mgr. Radim Chvaja, Ph.D. (lecturer)
Mgr. et Mgr. Radek Kundt, Ph.D. (lecturer)
Guaranteed by
Mgr. et Mgr. Eva Kundtová Klocová, Ph.D.
Department for the Study of Religions – Faculty of Arts
Contact Person: Mgr. Kristýna Čižmářová
Supplier department: Department for the Study of Religions – Faculty of Arts
Timetable
each even Wednesday 16:00–17:40 C42
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 30 student(s).
Current registration and enrolment status: enrolled: 9/30, only registered: 0/30, only registered with preference (fields directly associated with the programme): 0/30
fields of study / plans the course is directly associated with
Course objectives
How did the ideas about the afterlife among the indigenous peoples of Australia differ from those of the Aztecs? Do religious specialists across cultures have similar characteristics? Is the strict requirement of ritual purity related to the ecological conditions of a given religious tradition? Although the enormous diversity of religious phenomena might suggest the uniqueness of each religious system, there are basic mechanisms that stem from the common foundations of human existence. Studying and comparing cross-cultural material related to religious manifestations helps to reveal non-random patterns of human behavior and thinking. The course introduces the basic principles, methods, and sources for this type of research and focuses in particular on the use of existing data sets from anthropological, archaeological, and sociological databases (HRAF, DRH, SCCS, DPLACE, WVS, PEW, EVS). Students will learn how data obtained from these sources can help clarify ambiguities regarding the origins of specific religious traditions, their influence on other areas of human activity, or their interaction with the natural and social environment. The course is designed to provide students with an understanding of the principles, procedures, and obstacles associated with cross-cultural research, as well as the practical skills needed to perform meaningful analyses using existing data. Thanks to a combination of theoretical lectures and practical exercises, students will be prepared to critically evaluate the input and output parameters of cross-cultural research and at the same time contribute constructively to the development of knowledge in this area.
Learning outcomes
Course graduates will gain:
  • an overview of basic data sources for comparative cross-cultural research;
  • the ability to critically reflect on cross-cultural research data sources in terms of their origins and form;
  • the ability to search for, select, and process data needed to test proposed models and hypotheses;
  • basic skills in processing cross-cultural data, analyzing it, and presenting the results.
    • Syllabus
    • Introduction to the course, intercultural comparisons, universals, patterns, anthropological databases
    • Own creative/research activity: information retrieval (DPLACE, DRH)
    • Emic and ethic, context, reduction, classification, and quantification
    • Own creative/research activity: visualization (DRH, SCCS, DPLACE)
    • Types of questions, hypotheses, variables, coding
    • Own creative/research activity: coding (HRAF)
    • History of anthropological databases, critical evaluation of sources, reliability and uncertainty
    • Own creative/research activity: critical evaluation of sources (HRAF, DRH, Seshat)
    • Sociological datasets (WVS, PEW, EVS), cultural proximity (CD)
    • Own creative/research activity: Analysis of coding agreement
    • Time-oriented analysis, Galton's problem, causality, phylogenetic methods
    • Own creative/research activity: Analysis of own project
    Literature
      recommended literature
    • Muthukrishna, M., Bell, A. V., Henrich, J., Curtin, C. M., Gedranovich, A., McInerney, J., & Thue, B. (2020). Beyond Western, Educated, Industrial, Rich, and Democratic (WEIRD) psychology: Measuring and mapping scales of cultural and psychological distan
    • Watts, J., Jackson, J. C., Arnison, C., Hamerslag, E. M., Shaver, J. H., & Purzycki, B. G. (2021). Building Quantitative Cross-Cultural Databases From Ethnographic Records: Promise, Problems and Principles. Cross-Cultural Research, 56(December), 10693971
    • Ember, C. R., & Ember, M. (2009). Cross-Cultural Research Methods. AltaMira Press.
    • Ember, C. R. (2007). Using the HRAF Collection of Ethnography in Conjunction With the Standard Cross-Cultural Sample and the Ethnographic Atlas. Cross-Cultural Research, 41(4), 396–427. https://doi.org/10.1177/1069397107306593
    • Slingerland, E., Atkinson, Q. D., Ember, C. R., Sheehan, O., Muthukrishna, M., Bulbulia, J., & Gray, R. D. (2020). Coding Culture: Challenges and Recommendations for Comparative Cultural Databases. Evolutionary Human Sciences, 53(9), 1–20. https://doi.or
    Teaching methods
    A combination of lectures with discussions, practical seminars, and independent research. The seminars involve working on your own laptop. If you do not have one available, it is possible to borrow one after consulting with the instructor.
    Assessment methods
  • Conducting research on a pre-selected topic from a defined range of options, with a focus on analysis and presentation of results
  • Oral presentation and defense of a research project.
  • Attendance at classes, active participation in discussions and group seminar tasks
  • Independent creative/research activity (micro-tasks)
    • Language of instruction
    Czech
    Further comments (probably available only in Czech)
    Study Materials
    The course is taught once in two years.
    Information on course enrolment limitations: Zápis mimo religionistiku je podmíněn souhlasem vyučujících.
    Teacher's information
    No prior knowledge of statistics or data visualization is required – statistical inference will be covered in the basic terms necessary to understand publicly presented statistical inferences. Similarly, no knowledge of software for statistical data analysis and visualization of results is required – the basics of working with this software will be covered in seminars.
    • Enrolment Statistics (recent)
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