Qualitative_data_analysis

INTRODUCTION 7
First of all, I take a rather eclectic view of the sources of qualitative data. The
association of qualitative data with unstructured methods is one which I challenge in
the following chapter. Problems of conceptualization are as important in surveys as
in any other research methods, and problems of interpretation and classification are
as important to survey data as in any other context (Marsh 1982).
Secondly, I take a similarly eclectic view of qualitative analysis. Analysis aimed at
describing situations or informing policy seems to me no less legitimate and
worthwhile than analysis geared to generating theory. I also assume that we may be
as interested in identifying and describing ‘singularities’, in the sense of unique
events or cases, as in identifying and explaining regularities and variations in our
data. Throughout the book, I assume that qualitative analysis requires a dialectic
between ideas and data. We cannot analyse the data without ideas, but our ideas must
be shaped and tested by the data we are analysing. In my view this dialectic informs
qualitative analysis from the outset, making debates about whether to base analysis
primarily on ideas (through deduction) or on the data (through induction) rather
sterile (Chapter 5). This dialectic may be less disciplined than in the natural
sciences, where experiment and quantitative measurement provide a firmer basis for
examining evidence; but the search for corroborating evidence is nevertheless a
crucial feature of qualitative analysis (Chapter 14). It is also a vital element in
producing an adequate as well as an accessible account (Chapter 15).
Thirdly, I take a pragmatic view of analytic procedures (cf. Giarelli 1988). My
main aim is to give a practical introduction to analytic procedures. The book
describes a range of procedures we can follow for managing data (Chapter 6),
reading and annotating (Chapter 7), categorizing (Chapters 8, 9 and 10), linking
data (Chapter 11), connecting categories (Chapter 12) and using maps and matrices
(Chapter 13). While these procedures are presented sequentially, in practice the mix
and order of procedures adopted in qualitative analysis will vary. The choice of any
particular permutation of procedures depends upon factors like the characteristics of
the data, the objectives of the project, the predilections of the researchers, and the
time and resources available to them.
If we consider qualitative data analysis (somewhat misleadingly) in terms of a
logical succession of steps leading from our first encounters with the data through to
the production of an account, then the various steps considered in this book can be
depicted as in Figure 1.1. Because of its importance in conceptualizing data, three
chapters are devoted to the tasks of categorizing, and a further two chapters to ways
of making connections between categories. The intervening step (Chapter 11) is
concerned with linking data, as an innovative technique for overcoming the
fragmentation of data produced by categorization, and providing a firm basis for
identifying conceptual connections between categories.