RESEARCH METHOD COHEN ok

GROUNDED THEORY 491
data, thereby confining the data analysis to the
agenda of the researcher rather than the ‘other’.
In this way it enables pre-existing theory to be
tested. Indeed Mayring (2004: 269) argues that if
the research question is very open or if the study
is exploratory, then more open procedures than
content analysis, e.g. grounded theory, may be
preferable.
However, inductive approaches may be ruled
out of the early stages of a content analysis,
but this does not keep them out of the later
stages, as themes and interpretations may emerge
inductively from the data and the researcher,
rather than only or necessarily from the categories
or pre-existing theories themselves. Hence to
suggest that content analysis denies induction or is
confined to the testing of pre-existing theory (Ezzy
2002: 85) is uncharitable; it is to misrepresent the
flexibility of content analysis. Indeed Flick (1998)
suggests that pre-existing categories may need to
be modified if they do not fit the data.
Grounded theory
Theory generation in qualitative data can be
emergent, and grounded theory is an important
method of theory generation. It is more inductive
than content analysis, as the theories emerge
from, rather than exist before, the data. Strauss
and Corbin (1994: 273) remark: ‘grounded
theory is a general methodology for developing
theory that is grounded in data systematically
gathered and analysed’. For a summary sheet of
grounded theory principles see the accompanying
web site (http://www.routledge.com/textbooks/
9780415368780 – Chapter 23, file 23.1 doc.).
There are several features of this definition:
Theory is emergent rather than predefined and
tested.
Theory emerges from the data rather than
vice versa.
Theory generation is a consequence of, and
partner to, systematic data collection and
analysis.
Patterns and theories are implicit in data,
waiting to be discovered.
Glaser (1996) suggests that ‘grounded theory is
the systematic generation of a theory from data’;
it is an inductive process in which everything is
integrated and in which data pattern themselves
rather than having the researcher pattern them,
as actions are integrated and interrelated with
other actions. Glaser and Strauss’s (1967) seminal
work rejects simple linear causality and the
decontextualization of data, and argues that the
world which participants inhabit is multivalent,
multivariate and connected. As Glaser (1996)
says, ‘the world doesn’t occur in a vacuum’
and the researcher has to take account of the
interconnectedness of actions. In everyday life,
actions are interconnected and people make
connections naturally; it is part of everyday
living, and hence grounded theory catches the
naturalistic element of research and formulates
it into a systematic methodology. In seeking to
catch the complexity and interconnectedness of
everyday actions grounded theory is faithful to
how people act; it takes account of apparent
inconsistencies, contradictions, discontinuities
and relatedness in actions. As Glaser (1996) says,
‘grounded theory is appealing because it tends to
get at exactly what’s going on.’ Flick (1998: 41)
writes that ‘the aim is not to reduce complexity
by breaking it down into variables but rather to
increase complexity by including context’.
Grounded theory is a systematic theory,
using systematized methods (discussed below) of
theoretical sampling, coding constant comparison,
the identification of a core variable, and saturation.
Grounded theory is not averse to quantitative
methods, it arose out of them (Glaser 1996)
in terms of trying to bring to qualitative
data some of the analytic methods applied in
statistical techniques (e.g. multivariate analysis).
In grounded theory the researcher discovers what is
relevant; indeed Glaser and Strauss’s (1967) work
is entitled The Discovery of Grounded Theory.
However, where it parts company with much
quantitative, positivist research is in its view of
theory. In positivist research the theory pre-exists
its testing and the researcher deduces from the
data whether the theory is robust and can be
confirmed. The data are ‘forced’ into a fit with the
Chapter 23