RESEARCH METHOD COHEN ok

368 INTERVIEWS
asummarizingorexploratorytone,openingor
closing a line of enquiry)
emphases placed by the speaker
pauses (short to long) and silences (short to
long)
interruptions
the mood of the speaker(s) (e.g. excited, angry,
resigned, bored, enthusiastic, committed,
happy, grudging)
the speed of the talk (fast to slow, hurried or
unhurried, hesitant to confident)
how many people were speaking simultaneously
whether a speaker was speaking continuously
or in short phrases
who is speaking to whom
indecipherable speech
any other events that were taking place at the
same time that the researcher can recall.
If the transcript is of videotape, then this enables
the researcher to comment on all of the non-verbal
communication that was taking place in addition
to the features noted from the audiotape. The issue
here is that it is often inadequate to transcribe only
spoken words; other data are important. Of course,
as soon as other data are noted, this becomes a
matter of interpretation (what is a long pause,
what is a short pause, was the respondent happy
or was it just a ‘front’, what gave rise to suchand-such
a question or response, why did the
speaker suddenly burst into tears). As Kvale (1996:
183) notes, interviewees’ statements are not simply
collected by the interviewer, they are, in reality,
co-authored.
Analysing
Once data from the interview have been collected,
the next stage involves analysing them, often by
some form of coding or scoring. In qualitative
data the data analysis here is almost inevitably
interpretive, hence the data analysis is less a
completely accurate representation (as in the
numerical, positivist tradition) but more of
a reflexive, reactive interaction between the
researcher and the decontextualized data that
are already interpretations of a social encounter.
The great tension in data analysis is between
maintaining a sense of the holism of the
interview and the tendency for analysis to atomize
and fragment the data – to separate them into
constituent elements, thereby losing the synergy
of the whole, and in interviews often the whole is
greater than the sum of the parts. There are several
stages in analysis, for example:
generating natural units of meaning
classifying, categorizing and ordering these
units of meaning
structuring narratives to describe the interview
contents
interpreting the interview data.
These are comparatively generalized stages. Miles
and Huberman (1994) suggest twelve tactics
for generating meaning from transcribed and
interview data:
counting frequencies of occurrence (of ideas,
themes, pieces of data, words)
noting patterns and themes (Gestalts), which
may stem from repeated themes and causes or
explanations or constructs
seeing plausibility: trying to make good sense
of data, using informed intuition to reach
aconclusion
clustering: setting items into categories, types,
behaviours and classifications
making metaphors: using figurative and
connotative language rather than literal
and denotative language, bringing data to
life, thereby reducing data, making patterns,
decentring the data, and connecting data with
theory
splitting variables to elaborate, differentiate
and ‘unpack’ ideas, i.e. to move away from the
drive towards integration and the blurring of
data
subsuming particulars into the general,
akin to Glaser’s (1978) notion of ‘constant
comparison’ (see Chapter 6 in this book) – a
move towards clarifying key concepts