Sunday, April 20, 2014

Short Courses on Research Methods (SCRM)

Supported by the National Science Foundation

Now in its tenth year, the SCRM offers a program of intensive, five-day courses on research methods in cultural anthropology. The program is directed by H. Russell Bernard and a board of advisors, including Jean Ensminger, Jeffrey Johnson, Carmella Moore, Eric Smith, and Susan Weller, with support from the National Science Foundation. The SCRM courses are held at the Duke University Marine Laboratories in Beaufort, North Carolina.

Since 1999, the Duke Marine Lab has hosted the NSF-supported Summer Institute on Research Design in Cultural Anthropology (SIRD), for graduate students in cultural anthropology, directed by Jeffrey Johnson and East Carolina University, with Susan Weller and H. Russell Bernard as co-directors. That three-week program on research design, now in its 19th year, is only for Ph.D. students in cultural anthropology.

The SCRM program is for colleagues who already have the Ph.D. in anthropology and who want to broaden or improve their skills. Because the program is supported by the U.S. National Science Foundation, eligibility is restricted to colleagues working in the U.S. (regardless of citizenship) or to U.S. citizens working abroad. The program covers room, board, and tuition. Participants are responsible for costs associated with travel to and from the Institute and required textbooks.

SCRM Summer 2014 Course Offerings

Cultural Domain Analysis (July 21-25, 2014)

H. Russell Bernard and Rosalyn Negrón

Cultural domain analysis (CDA) is the study of how people in a group think about lists of things that somehow go together. These can be physical, observable things—kinds of wine, kinds of music, rock singers, foods that are appropriate for dessert, medicinal plants, medicinal plants, ice cream flavors, animals you can keep at home, horror movies, symptoms of illness—or conceptual things like occupations, roles, emotions, things to do on vacation, things you can do to help the environment, and so on. The method comes from work in cognitive anthropology but it has since been picked up in fields such as marketing, product development, and product usability studies. CDA involves systematic interviewing to get lists of items that comprise a coherent cognitive domain.

The data collection methods covered in this five-day course include: free lists, pile sorts, triad tests, paired comparisons, ratings, and rankings. The data analysis methods include: multidimensional scaling, hierarchical clustering, property fitting (PROFIT), quadratic assignment procedure (QAP), and consensus analysis.

The methods covered in this course are based on the analysis of profile matrices and similarity matrices. The class begins with a discussion of the theory behind these matrices and how they can be used in many different areas of research, including the analysis of qualitative data (like text and images).

Statistics in Ethnographic Research (July 28-August 1, 2014)

Daniel Hruschka and David Nolin

This five-day course covers the concepts and skills needed for analyzing and interpreting quantitative data collected as part of ethnographic field research. Researchers will learn how to: (1) develop quantitative measures of behaviors, attitudes, and material objects; (2) provide group-level summaries of quantitative data; (3) frame expectations about group differences and relationships between variables; (4) test those expectations with quantitative data; and (5) justify why a specific test is appropriate for a given kind of data.

In addition to lectures, the course involves class activities, visualizations, analysis of real data, and a group project to illustrate the main concepts and skills and to walk participants through the steps of quantitative data collection and analysis.

Skills covered in the class include scale construction, summarizing and graphing quantitative data, visual data exploration, testing hypothesis about group differences and statistical relationships, basic linear regression, identifying statistical confounding, and assessing the assumptions underlying a given test. In addition to these basic skills, participants will be given a roadmap to more complex models and tests which they may encounter in their research, including logistic regression, repeated measures, and statistical interactions.