Short Courses on Research Methods (SCRM)
Supported by the National Science Foundation
Now in its twelfth year, the SCRM (Short Courses on Research Methods) program is for cultural anthropologists who already have the Ph.D. Three, five-day courses are offered during summer 2016 at the University of Florida, in Gainesville, FL. This year’s courses are: Text Analysis (July 11-15), Statistics in Ethnographic Research (July 18-22), and Cultural Domain Analysis (July 25-29). Apply by March 1, 2016.
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 2016 Course Offerings
Text Analysis (July 11-15, 2016)
This five-day course for professional anthropologists lays out a broad range of systematic methods for analyzing qualitative data (e.g., text and images) and provides guidance on when the methods should be used. We will cover the basics of qualitative research, including: techniques for identifying themes, tips for developing and using codebooks, and suggestions on how to produce qualitative descriptions, make systematic comparisons, and build and formally test models. The course will concentrate on three major traditions of analysis: grounded theory, content analysis, and semantic network and word-based analysis.
We will emphasize hands-on data analysis exercises to illustrate the complementary strengths of different methods for analyzing qualitative data. Some, but not all, of the methods we cover require computer-based methods. Where appropriate, we will show participants how recent advances in hardware and software can facilitate the recording and transcribing of text and how software can be used to facilitate the analysis of qualitative data. We will focus in particular on working with MAXQDAsoftware. Participants will receive an extended trial version of the software for use in the workshop.
Classes will be divided between lectures and labs where participants will analyze real data. At the end of the course, participants should be able to use the various methods presented in the analysis of their own data and to demonstrate the methods to their students and colleagues.
Statistics in Ethnographic Research (July 18-22, 2016)
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, and analysis of real data 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.
Cultural Domain Analysis (July 25-29, 2016)
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).