Doing Field Projects. John Forrest. Читать онлайн. Newlib. NEWLIB.NET

Автор: John Forrest
Издательство: John Wiley & Sons Limited
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Жанр произведения: Культурология
Год издания: 0
isbn: 9781119734628
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map, and the methods used to carry out these projects are fundamentally different also. There is no one-size-fits-all model for research design in qualitative fieldwork. Nevertheless, there are certain guidelines that apply to most situations. To begin, field research must be driven by a research question. How to arrive at a research question is often a complicated matter, as is the nature of research questions themselves, but going into a fieldwork project, large or small, without some kind of research question, even a vague one, is potentially a recipe for disaster.

      No matter how simple or rough your research design is, you should start a field project with a reason that is more than “I’d like to know something about this.” Certainly, that kind of loose pondering can be your initial jumping off point, but you have to make your purpose for inquiry much more explicit before you commence your actual fieldwork on a specific project.

      Formulating a Research Question

      To narrow your focus you need to move beyond simple curiosity and key in on elements that stand out to you. You must start to ask Why? questions. For instance, after your first tai chi lesson you might ask: Why do people practice tai chi? Why do some people choose to teach tai chi? Do people have different motivations, and why? Such questions can provide the initial framework for fieldwork, but they are only a beginning. These questions are still much too general by themselves to provide more than general answers, and, in many cases, the answers will be obvious. Your job is to dig deeper than the obvious. Some people do tai chi for health and fitness reasons, some because they like the calm atmosphere, some because their friends do it, and so on. There may not be a single thread uniting everyone. In such a case, you may have to cast a wider net, or develop an entirely new question. Here is where the iterative process kicks in.

      After the first lesson and initial questions to participants and the instructor, you might return home and do some independent research on the history and philosophy of tai chi. You may be surprised to discover that tai chi is considered a martial art, even though what you saw at your lesson was not aggressive at all (very slow and graceful), and that the practice has a large number of forms in the modern world, including genuine sparring with partners. You may also learn that tai chi incorporates components of Taoist, Confucian, and Buddhist philosophies. Armed with this information you can formulate some new questions: “What worldviews, if any, do students share, and what are they? Why?” “Are participants more interested in the health benefits or spiritual aspects of tai chi? Why?” Are there other factors that motivate participation, such as cultural expectations, power dynamics, ethnic identity, political persuasion etc.? Why? Are participants with certain ethnic or religious identities more likely to participate than others? Why or why not? These questions provide new answers which, in turn, prompt new questions.

      It is important to note, however, that even seemingly excellent research questions may need to be modified throughout the course of fieldwork. All manner of things can go wrong with your research questions once you get into a project. Indeed, many professional anthropologists are likely to admit that their research questions, posed in the comfort of their universities before embarking on fieldwork, satisfied their doctoral committees, or got them research grants, but had to be revised or scrapped completely when they got into the nitty-gritty of fieldwork. This certainly was the case for me and many others I know. The point is that your research question opens the very beginning of a path through what can be a jungle of data.

      In the physical sciences, hypothesis formation is the common standard for advancing research beyond simple curiosity because these sciences are generally founded on what is called the “hypothetico-deductive model” – at least, in theory. In very general terms, this approach involves surveying the data that already exists, asking why it is the way that it is (especially if there is a discernible pattern), formulating a working hypothesis to explain the data, coming up with predictions based on the hypothesis, conducting experiments to test the predictions, modifying the hypothesis if necessary based on experimental results, and so on.

      Qualitative fieldwork is not an experimental science, so the model is not fully applicable, and it has its flaws and critics, even within experimental science. Development of the kind of hypothesis found in the natural sciences is not usually relevant for qualitative research because cultural anthropologists don’t build hypotheses in order to rigorously test them to derive grand, generalizable theories. Cultural anthropology today is not a predictive science in this way. Instead, cultural anthropologists seek to understand the larger political, economic, historical, cultural factors that shape microsocial phenomena by looking for patterns in social life. Nevertheless, elements of the model are useful when it comes to developing a research design.

      If we think of “hypothesis” in a looser way, as an interpretation or an explanation of the data derived from a research question, then the iterative process of asking a research question, seeing if there are any patterns or regularities, refining the question, and so on, resembles the scientific method in some respects. This is because cultural anthropologists do not simply gather information randomly: we have a purpose in mind. Thus, when you ask a research question, at the outset you can consider what kinds of answers you might expect, and if the answers that you ultimately receive are quite different from what you expected, then you can consider why this is the case.

      Identifying a Unit of Analysis