Tricks of the Trade: How to think about your research while you’re doing it – Imagery (Chapter 2) and Sampling (Chapter 3)

Text Exploration

Imagery

In this text, the author provides “tricks”—ways of thinking about a process of research—to help researchers remember what makes social research effective and different than other forms of research. Chapter two emphasizes ways to construct mental imagery of research data.

The basic way of studying society is to “start with images and end with them” in order to produce an image of what is being studied. A small amount of data leads to the production of a rich and compelling story of what was studied, and along the way, the researcher invents details. This is built on data, but also stereotypes. As we collect data, we attribute a perspective and motives to the people who are involved in the data. It’s recognized that this is dangerous, because we aren’t those people and we don’t live in their circumstances. This leads to misunderstanding, particularly when the imagery that is constructed becomes rich and believable: it “enters our heads as the residue of our everyday experiences.” To compensate for this, social scientists often feel that they need more data, as if quantity will alleviate these problems; the author feels this is incorrect.

There are several types of imagery that are produced from research. One is professional imagery, or imagery that is shared by “professionals” who study the same topic. This is manifested in stories about how events and people become the way they are, and can be thought of as a scientific theory. This means that it has to be coherent and realistic, with a reasonable set of connections (or congruency), and it has an internal logic to itself. But if we can’t resolve inconsistencies, we change the logic. This is often provoked by having “lots of discrete facts” about the topic. Professional imagery is related to “the kind of causality we think might be operating.”

One way to explore this imagery is to think about how things would look if they “were a certain way we’re pretty sure they aren’t.” The author views this as a null hypothesis. Constraints are a large part of what social science studies, but exploring a null hypothesis requires thinking of unlikely possibilities, which means shifting or ignoring those constraints during analysis.

Another way of exploring imagery is by considering the idea of coincidence. Things seem coincidental when told in retrospect, as one thing led to another with a huge degree of improbability. This is often called “process” (which “could just as well be called stories.”) Things depend on one-another, and one way to think of these dependencies is as contingencies; events are contingent on other events, but not caused by other events.

Society can be thought of as an organism made up of social organizations, which are situations “in which most people do pretty much the same things in pretty much the same way most of the time.” But the repetition is less important as is the connectedness of the people and activities involved in the repetition, which indicates that society is acting as an organism. Looking at activities, considering people as activities, is the key. This means studying, for example, addictive behavior instead of addicts; it forces a consideration that people are not static and defined entities. Objects are the “embodied residue of people’s activities” and can be thought of as “social agreements, or rather, congealed moments in the history of people acting together.”

Effective imagery is produced when looking at specifics; there is no “social setting,” but instead, “this social setting.” When analyzing data, “you include anything that tells you it can’t be left out by sticking its nose up so that it can’t be ignored.” This means that anomalies or eccentricities become a major part of the story, and should be considered as normal, in that one specific circumstance.

Narrative is effective, and often points to a history and story of things that happened and a sequence in which they happened. This is a process, where something initiated it and then the other things happened. It’s tempting to think of this as causality, but instead, it’s related more to the idea of interconnectedness of specifics.

Ultimately, the author calls for a social scientist to be in a rich dialogue with data and thinking about possibilities rather than answers.

Sampling

In this chapter, the author addresses the idea of sampling and generalizability of research data, encouraging a focus on individual anomalous cases described in rich detail rather than broad sampling of data at a succinct level of generalizability.

Researchers can’t study everything, and rely on sampling techniques to try to predict from a small group what a big group will do or like or feel. Implicit here is trying to find an average, but an average may not be what is interesting or part of a research question. Instead, it may be more interesting to understand “what kind of an organization could be the whole of which the thing we have studied is a part,” or identifying the full range of variations in something being explored.

Looking at something in detail raises a question of how much detail; “everything” is unrealistic (and impossible), so instead, researchers can focus on “plain description.” This is observation without interpretation, and the author describes that this is more valuable than any form of interpretative summary; “massive description” is desired.

Since a researcher can’t look at everything or everyone, they should focus on some surprising areas of life. One is to examine in detail things that are considered conventional thinking or everyday knowledge. Another is to focus on cases of things that failed, rather than succeeded. In both cases, description of details is critical in identifying what may have been missed, or what is actually going on. Questioning conventional thinking can be forced by assuming that “nothing that can be imagined is impossible,” and researchers should look for cases that are most likely to challenge existing thinking; the author argues that “we ought to imagine the wildest possibilities and then wonder why they don’t happen.”

Similar to questioning conventional thinking is to challenge ideas that have been “already researched,” as the world is constantly changing. It is contingent on place, and history, and specifics. Things become labeled, and then it is tempting to view things with the same label as the same things, but that trivializes the rich nuance of each individual circumstance.