RESEARCH METHOD COHEN ok

PLANNING INTERVIEW-BASED RESEARCH PROCEDURES 369
factoring: bringing a large number of variables
under a smaller number of (frequently)
unobserved hypothetical variables
identifying and noting relations between
variables
finding intervening variables: looking for other
variables that appear to be ‘getting in the way’
of accounting for what one would expect to be
strong relationships between variables
building a logical chain of evidence: noting
causality and making inferences
making conceptual/theoretical coherence:
moving from metaphors to constructs to theories
to explain the phenomena.
This progression, though perhaps positivist in its
tone, is a useful way of moving from the specific
to the general in data analysis. Running through
the suggestions from Miles and Huberman (1994)
is the importance that they attach to coding of
responses in interviews, partially as a way of
reducing what is typically data overload from
qualitative data.
Coding has been defined by Kerlinger (1970)
as the translation of question responses and
respondent information to specific categories for
the purpose of analysis. As we have seen, many
questions are precoded, that is, each response can
be immediately and directly converted into a score
in an objective way. Rating scales and checklists
are examples of precoded questions. Coding is the
ascription of a category label to a piece of data,
with the category label either decided in advance
or in response to the data that have been collected.
We discuss coding more fully in Chapter 23,
and we refer the reader to that discussion.
Content analysis involves reading and judgement;
Brenner et al. (1985)setoutthirteensteps
in undertaking a content analysis of open-ended
data:
1 Briefing: understanding the problem and its
context in detail.
2 Sampling: of people, including the types of
sample sought (see Chapter 4).
3 Associating: with other work that has been
done.
4 Developingahypothesis.
5 Testing the hypothesis.
6 Immersinginthedatacollected,topickupall
the clues.
7 Categorizing: in which the categories and
their labels must reflect the purpose of the
research, be exhaustive and be mutually
exclusive.
8 Incubating:reflectingondataanddeveloping
interpretations and meanings.
9 Synthesizing: involving a review of the
rationale for coding and an identification of
the emerging patterns and themes.
10 Culling: condensing, excising and even
reinterpreting the data so that they can be
written up intelligibly.
11 Interpreting: making meaning of the data.
12 Writing: including giving clear guidance on
the incidence of occurrence; proving an
indication of direction and intentionality of
feelings; being aware of what is not said as well
as what it said – silences; indicating salience
to the readers and respondents (Brenner et al.
1985: 140–3).
13 Rethinking.
This process, Brenner et al. (1985:144)suggest,
requires researchers to address thirteen factors:
1 Understand the researchbrief thoroughly.
2 Evaluate the relevance of the sample for the
research project.
3 Associate their own experiences with the
problem, looking for clues from the past.
4 Develop testable hypotheses as the basis for
the content analysis (the authors name this
the ‘Concept Book’).
5 Test the hypotheses throughout the interviewing
and analysis process.
6 Stay immersed in the data throughout the
study.
7 Categorize the data in the Concept Book,
creating labels and codes.
8 Incubate the databeforewriting up.
9 Synthesize the data in the Concept Book,
looking for key concepts.
10 Cull the data, being selective is important
because it is impossible to report everything
that happened.
Chapter 16