Qualitative_data_analysis

264 QUALITATIVE DATA ANALYSIS
We can do this by demonstrating how the concepts and connections we have
identified are grounded in the data. This involves more than throwing in a few
anecdotes and illustrations to exemplify the meaning of a concept or a connection.
This is not irrelevant, for we do have to show how our account applies to the data.
But it is not enough. We need to be more systematic in considering the fit between
our ideas and our data. We can do this by comparing the criteria we have employed
in categorizing and linking with the data, noting and discussing borderline, extreme
and negative as well as straightforward or typical examples. If the data is at all
voluminous, then we cannot consider every bit of data in detail; but by considering
notable exceptions as well as examples we can provide a more thorough review. As well
as how our ideas apply to the data, we have to consider how far they apply. To do
this, we have to consider frequency as well as content. Have we found one example,
or many? Are examples concentrated in a single case, or spread evenly across cases?
The computer can help us to answer such questions by making it easy to summarize
information about the volume and distribution of our data. While the assumptions
required for statistical analysis may not be satisfied by the way the data has been
collected and analysed, it is still possible to obtain a useful descriptive overview in
summary form.
These comments apply most especially where we claim to identify ‘patterns’
within the data. Where we are dealing with ‘singularities’, frequencies are irrelevant.
However, we can at least improve confidence in the validity of our account by
considering carefully the quality of our sources, and also by cross-referencing our
observations from a range of sources. Otherwise we become unduly dependent on
limited data of doubtful validity, such as Vincent’s account of his relations with
Gauguin or Claire Memling. Here again, our case will be strengthened if we remain
open to different interpretations of the data (e.g. that Vincent has a lively
imagination and a tendency to blame others for his problems) than if we simply
exclude them from consideration.
Let us look at an example. Suppose we want to argue that women tend to be
presented as passive patients, in contrast to the male patients and of course to the
dentists themselves. Is this a valid account? First we can explicate our concept of
passivity by looking at how we have defined the relevant category and some
examples of how we have categorized the relevant data. Then we can look at a
borderline example, and also some negative examples. Finally, we can consider how
far the data supports our analysis.
Woody Allen exploits the vulnerability we feel when ‘trapped’ in the dentist’s
chair. Does he do so in a gender-neutral way, or does his humour betray some
implicit sexual stereotypes? We can examine this question by considering the way he
depicts patient responses to the rather bizarre dental practices which they encounter.
Here we find some striking images, such as that of Mrs Zardis sitting passively in