still photos;
film;
home videos.
The most common form of qualitative data used in analysis is text; this can either be a transcription from interviews or field notes from ethnographic work or other kinds of documents. Most audio and video data are transformed into text to be analyzed. The reason for this is that text is an easy form of recording that can be dealt with using the ‘office’ techniques mentioned above. However, with the development of digital audio and video recordings and the availability of software to sort, index and retrieve them, the need and desire to transcribe might be reduced in the future. Moreover, using video data preserves some of the visual aspects of the data that are often lost when conversations are transcribed. Nevertheless, when it comes to the fluent, rapid and accurate examination of qualitative data, most of us still find it easiest when dealing with textual data.
Practicalities of qualitative analysis
Qualitative analysis involves two activities: first developing an awareness of the kinds of data that can be examined and how they can be described and explained, and, second, a number of practical activities that assist with the kinds of data and the large amounts of it that need to be examined. The latter are what I refer to as the practicalities of qualitative analysis. I will discuss these more in the rest of the book, but two of them distinguish qualitative analysis from other approaches
Merging collection and analysis
In some kinds of social research you are encouraged to collect all your data before you start any kind of analysis. Qualitative research is different from this because there is no separation of data collection and data analysis. Analysis can, and should start in the field. As you collect your data by interviewing, taking field notes, acquiring documents and so on, you can start your analysis. I examine these issues in more detail in Chapter 3, but things like keeping field notes and a research diary are both ways to collect data and ways to begin its analysis. You don’t even need to wait till your first interviews or field trips to start analysis. There is often plenty of data you can examine, in existing documents as well as in previous studies.
In fact, not only is concurrent analysis and data collection possible, but it can actually be good practice too. You should use the analysis of your early data as a way of raising new research issues and questions. To that extent qualitative research is flexible. Research questions can be decided late in the study; for instance, if the original questions make little sense in the light of the perspectives of those you have studied.
Expanding the volume of data not reducing it
A further key difference between the procedures of qualitative and quantitative analysis is that the former does not seek to reduce or condense the data; for example, to summaries or to statistics. Qualitative data analysis often involves dealing with large volumes of data (transcripts, recordings, notes, etc.). Most analysis simply adds to this volume even though, at the final stage of reporting about the research, the analyst may have to select summaries and examples from the data.
Thus qualitative analysis usually seeks to enhance the data, to increase its bulk, density and complexity. In particular, many of the analytic approaches involve creating more texts in the form of things like summaries, précis, memos, notes and drafts. Many of the techniques of qualitative analysis are concerned with ways to deal with this large volume of data. This is particularly the case with coding. Whereas coding in quantitative analysis is for the explicit purpose of reducing the data to a few ‘types’ in order that they can be counted, coding in qualitative analysis is a way of organizing or managing the data. All the original data are preserved. Codes (and their associated analytic documents) add interpretation and theory to the data. In fact, typically, text may be densely coded; not only will most text be assigned a code but much will have more than one code attached to it.
Methodology
The second activity that qualitative analysis involves is an awareness of the kinds of things that can be found in qualitative data and how they can be analyzed. There is a wide range of these ways of looking at the data, and qualitative analysts have adopted a variety of methodologically based analytic styles to do so. Consequently, there are still various contested views about methodology.
Rich description
A major concern of qualitative analysis is to describe what is happening, to answer the question ‘What is going on here?’. This is because very often what is described is novel or at least forgotten or ignored. The description is detailed and contributes to an understanding and eventual analysis of the setting studied. In particular, the focus is on giving a ‘thick’ description, a term popularized by Geertz (1975) (see also Mason, 2002). This is one that demonstrates the richness of what is happening and emphasizes the way that it involves peoples’ intentions and strategies. From such a ‘thick’ description it is possible to go one stage further and offer an explanation for what is happening.
Induction, deduction and abduction
One of the functions of qualitative analysis is to find patterns and produce explanations. There are two contrasting logics of explanation, induction and deduction, and qualitative research actually uses both.
Induction is the generation and justification of a general explanation based on the accumulation of lots of particular, but similar circumstances. Thus repeated, particular observations that fans of football clubs that are doing well, or fans of those that are doing very badly, are more ardent supporters than those of clubs that languish in the middle of their league, sustain the general statement that the fervour of fans’ support is greatest when their clubs are at the extremes of success.
Deductive explanation moves in the opposite direction, in that a particular situation is explained by deduction from a general statement about the circumstances. For example, we know that as people get older their reaction times slow down, so we could deduce that Jennifer’s reaction times are slow because she is over 80 years old. Much quantitative research is deductive in approach. A hypothesis is deduced from a general law and this is tested against reality by looking for circumstances that confirm or disconfirm it.
An important development of this deductive approach is the hypothetico-deductive model developed by the philosopher Karl Popper (1989). In this model, the scientist (or the social scientist) makes a bold conjecture or hypothesis deduced from what they believe is the correct theory. This is then tested by empirical examination. But it leaves it to the genius and imagination of the researcher to come up with the putative theory. Actually, as other philosophers have pointed out (Peirce, 1958), in ordinary life (and qualitative researchers do this too) we often come up with general theories to explain the phenomena we experience. What we do combines aspects of deduction and induction and is called abduction or retroduction.
An abductive argument is one in which an explanation is proposed to account for an observed fact or group of facts. This is not deduction because we do not start with our general theory, but rather with the phenomena we experience, the facts. It is not induction as we do not generalize from a large number of similar observations. For example, we might notice in a group of young people, that those who come from low-income families have lower levels of educational achievement. We might then offer the explanation that low-income families are unable to afford
