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Qualitative Data Analysis
Sample Lecture Pack
Code: REM050
Postgraduate Study in
Educational and Social Research by
Distance Learning
This is an extract from a lecture pack for a module offered as part of the University of
London International Programmes Master of Research (MRes) in Educational and Social
Research. Materials for this degree programme are developed by academics at the
Institute of Education of the University of London.
For more information, see: www.londoninternational.ac.uk
© University of London, 2014
Module 5 Qualitative Data Analysis
Module introduction
by Will Gibson
Key reading
• Chapter 2 ‘Description, analysis, and interpretation in qualitative enquiry’,
pp. 9–54, from Transforming Qualitative Data: Descriptions, analysis and
interpretation by H. Wolcott
Introduction
In social research, analysis is often one of the most under-discussed parts of the
research process. Although authors often include a quite elaborate account of the
findings of their investigations, published research in books and journal articles
rarely includes a detailed outline of the process of analysis. Authors may use
general descriptive terms like ‘grounded theory’, ‘CAQDAS’ (computer-assisted
qualitative data analysis), ‘discourse analysis’, ‘narrative analysis’, and ‘thematic
analysis’ to describe their analytic work but, at best, these merely characterize
very general approaches, commitments or tools and do not help to explain what
might have been involved in any particular instance of their use. They are, in
other words, general descriptions, rather like the term ‘ethnography’.
Textbooks on analysis are usually much more explicit, but they can also be a little
confusing. Compare, for example, Miles and Huberman’s (1994) text Qualitative
Data Analysis with Wolcott’s (1994) Transforming Qualitative Data or Grbich’s
(2006) Qualitative Data Analysis and you will see three very different articulations
of the process of analysis. If the experts cannot agree on what analysis is, how
on earth are researchers new to the area supposed to know what to do? One of
the aims of this module is to show the breadth of work that is done in the name of
qualitative analysis, and to explain the various ways in which different authors,
disciplines and focal areas have defined approaches to analysis. In this way, the
module will produce a basic map of the field of analysis. You will look at
grounded theory, discourse analysis, narrative analysis, and reflect on some of
the issues implicated in these various domains of work. It is important to
emphasize from the outset, though, that the field of qualitative analysis is far
broader than the particular approaches that will be discussed here. Wolcott
(1994) has pointed to more than 50 distinct types of analysis, and it would clearly
be impossible to discuss all of those. My aim in this module then is to create a
critical awareness of issues related to analysis, and to exemplify these in relation
to some of the more common analytic forms.
Researchers very often come to analysis with strong preferences for particular
methods of data work. In providing a general overview of approaches, this
module does not intend to suggest that these different approaches to analysis
should be treated as something like a set of tools in a toolbox, or that researchers
typically work by selecting the right tool for the appropriate analytic job. Of
course, you cannot discount the idea that some researchers might work in that
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fashion, but it is not typically the case, because professional expertise,
disciplinary focus and theoretical commitments tend to lead researchers to
specialize in one area rather than another. Rather, the purpose of the module is
to give a sense of how such approaches function, why people who use those
approaches do so, and the types of aims they typically have when they do so. A
part of the process of development as a researcher involves creating your own
expertise and preferences about the most appropriate forms of analysis.
The process of analysis
One of the most important points to make about analysis is that it is not best
thought of as a ‘stage’ in social research, but is better regarded as a form of
research work that is informed by and informs all other aspects of research work.
One of the commonest ways of portraying the social research process is as a
linear move along the lines outlined below:
formulate questions

search literature

design research

collect data

analyse data

write up research.
In some respects, this way of representing social research misrepresents every
aspect of the process. Questions are not formulated only at the beginning of
research but are iteratively worked out through the research process; literature is
used to inform and position research interests not only prior to data collection, but
in relation to every aspect of research work, including analysis, writing, and
research design; research design is an evolving aspect of the research process
that is informed by data analysis and by the types of data that are collected.
In the abstract, a researcher may begin their research with any component of
research work (excluding, perhaps, the writing up of findings) and move from
there to any other component. For example, some researchers do begin their
projects with the consideration of some data and use their analysis of it to
formulate a problem. For example, in his work on the analysis of conversation
Harvey Sacks (1992) frequently described the analysis of data as a means of
developing a problematic that could subsequently be systematically explored in
relation to a larger data set. Another model of research might involve a
researcher beginning with a loose idea of a research interest, generating a
preliminary idea of data that might be useful for exploring that interest, analysing
their data and, from there, creating a more detailed view of both their question
and of their research design (this is a common orientation in grounded theory, for
example). Indeed, in many approaches, analysis is most effective when it has the
possibility of informing the other features of research – that is, where researchers
are able to use their analysis to make adjustments to their research design, to
think about other literature that might be relevant to their project, or to modify
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their research question or even their research interest itself. This does not mean
that there is no relevance to the linear model represented above, because it is
typical for researchers to attempt to create some sort of forward movement in the
research process (often represented in research timetables) that has some parity
with the linear approach. It must be accepted, however, that it is something of an
idealization, rather than an accurate representation of the actual process.
Technology and analysis
A very dominant discourse in the area of qualitative research concerns the role of
computers in analysis. Programs such as Atlas.ti, NVivo, Qualrus, MAXQDA, and
the Ethnograph are all forms of CAQDAS – computer-assisted qualitative data
analysis software. These types of software are, in some instances, very useful
tools for helping researchers to organize their analytic work. They are typically
useful in helping them to code their data (you will look in detail at the issue of
coding in Unit 2), to explore their coding frameworks, to organize their analytic
notes, and so on. These programs, in essence, provide databases that help
researchers to manage their data and their analysis of it.
Importantly, these sorts of software are not relevant to all forms of data work.
While a researcher undertaking grounded theory might well use something like
Atlas.ti to organize their work, someone undertaking critical discourse analysis
may find that such a programme would be of little use to them, because they tend
to work with much smaller segments of data. It is a common misunderstanding to
think that all qualitative research should involve the use of software of this type: it
is not the case. Nor is it the case that such software actually ‘performs’ analysis;
these programs are tools that help researchers organize their work.
Generating and exploring data
One way to think about social research design is in terms of the creation of a
strategy for generating data. The use of the word ‘generating’ rather than
‘collecting’ is important here: to refer to the ‘collection’ of data implies ‘gathering
up’ pre-existing or ready-made fragments or forms of evidence. In contrast, the
notion of ‘generating’ data emphasizes the role of the researcher in the creation
of data; those data are an emergent property of a researcher working in a social
setting in relation to a particular set of interests.
One of the implications of thinking about research design as data design is that
data are created for a purpose – to deal with some problem or issue. This basic
point helps to show that when researchers come to deal with their data they do
not come to it ‘cold’, so to speak, but with distinct motivated interests.
Researchers ask questions of data that are related to their research concerns –
they try to find things out that will help them to answer their research questions or
gain clarity on some concern or other.
However, analysis is not simply a matter of answering pre-specified questions: it
is also often characterized by a process of generating new questions. Analysis is
exploratory and, like all good explorations, full of surprises. It is very common for
new interests and concerns to arise from the interrogation of data. This is
precisely why it is so important to allow your analysis to inform your research
design, because if it does not it may not be possible to empirically explore the
interesting questions developed through the examination of the data. Data
analysis should begin as soon as some data have been collected so that you can
reflect on: how the emerging data relate to the research questions; whether or not
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the specified design is actually working in terms of the production of interesting or
relevant data; whether there are other interests that may need to be incorporated
into the design of the generation of data; whether or not there are other
interesting literary sources that need to be consulted.
Forms of data
The types of ‘things’ that researchers might treat as data are extremely varied.
Photographs, video recordings of activities, notes in books about things a
researcher has seen, audio recordings of interviews or informal conversations,
newspaper reports, minutes from meetings, diaries, books, web pages, blogs,
films, television programmes, recordings of music, household objects – all of
these can be used as data to deal with a problem. The question ‘what is data?’
can only really be answered in relation to a particular research issue because
‘data’ is defined by the relevance of some ‘thing’ to a particular research topic.
Further, in any given project, there is likely to be a wide variety of possible data
sources that could be used, and the purpose of the research design process is to
narrow that down to very particular features.
Structure of the module
In this module you will be exploring all of the issues outlined above. You will be
doing this through a combination of data analysis exercises, as well as through
detailed reading of descriptions of approaches to analysis. The structure of the
units to this module is as follows:
Unit 1 Grounded theory
Unit 2 Thematic analysis
Unit 3 Discourse analysis
Unit 4 Transcription
Unit 5 Narrative analysis
Learning outcomes
By the end of the module you should be able to:
• explain the main principles of grounded theory and some of the key debates
within the perspective
• undertake a thematic analysis of an interview transcript
• define, describe and apply different discourse analysis strategies
• transcribe audio recordings of talks using a variety of transcription approaches
• use and critique narrative analysis.
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Reading
The key reading for this module is included at the end of this lecture pack.
However, if you would like to supplement your reading with other materials there
are a lot of options available to you. There are not many books on qualitative data
analysis that provide a very detailed overview of the entire field of approaches
and issues. Usually, books tend to focus on one or other type of qualitative
analysis. If you are thinking of buying a book it is perhaps most useful to think
about what type of analysis you are most interested in and to purchase
something that deals in a focused way with that. The references at the end of the
various units of this module will give you an idea of some of the key texts in the
various areas.
References
Grbich, C. (2006) Qualitative Data Analysis: An introduction. London, Sage
Miles, M. and Huberman, A. (1994) Qualitative Data Analysis. Thousand Oaks,
Sage
Sacks, H. (1992) Lectures on Conversation, Volumes I and II. London, Blackwell
Wolcott, H. (1994) Transforming Qualitative Data: Descriptions, analysis and
interpretation. London, Sage
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Module 5 Qualitative Data Analysis
Unit 1 Grounded theory
by Will Gibson
Learning objectives
After studying this unit you should be able to:
• define grounded theory and explain its central procedures and elements
• explain the difference between the various articulations of grounded theory
• analytically evaluate the debates related to grounded theory, particularly the
divergences within the work of Glaser and Strauss and the constructivist
critiques of the approach.
Key readings for this unit
• ‘Grounded theory: objectivist and constructivist methods’ by C. Charmaz
(2000)
• ‘Introduction’ and Chapter 5 ‘The constant comparative method of qualitative
analysis’ from The Discovery of Grounded Theory by B. Glaser and A. Strauss
(1967)
• Chapter 1 ‘Introduction’ (pp.1–7) from Basics of Grounded Theory Analysis by
B. Glaser (1992)
Introduction
A background to grounded theory
Grounded theory (GT) is a very influential approach to working with data in
qualitative research. Strictly speaking, the approach, as originally formulated by
Glaser and Strauss, was not conceptualized as a solely ‘qualitative’ approach,
but it has had a bigger impact on qualitative than on quantitative researchers.
Grounded theory originated from the collaborative work of Barney Glaser and
Anselm Strauss. Both Glaser and Strauss were sociologists trained in the US, but
of very different stock. Strauss had worked in the Symbolic Interactionist tradition
at the University of Chicago. Much of Strauss’s work, both prior and subsequent
to his collaborations with Glaser, display similarities with that perspective. For
example, his work on the sociology of work in healthcare settings shows a
theoretical concern with the institutional organization of professionalized practice
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– a dominant theme in much ‘interactionist’ work. Barney Glaser studied at the
University of Colombia and his work shows some similarities to the functionalist
sociology of Robert Merton and Paul Lazarfeld. The details of their backgrounds
do not concern you here, but it is useful to bear them in mind because they offer
a context for understanding the divergences that Glaser and Strauss took in their
later work. It is also important to note that in their writings, particularly in their first
grounded theory book, The Discovery of Grounded Theory (1967), the authors
frequently refer to ‘sociologists’ rather than ‘social researchers’. This is partly
because of their own academic contexts of work, but it should be emphasized
from the beginning that their audience is far wider than this restricted readership.
One of their first collaborations was on an empirical study of the different levels of
awareness that patients in a San Francisco hospital had of their own risks of
death, and the ways in which these levels of awareness were interactionally
managed by hospital staff. The study focused on the ‘tactics’ used by nursing
staff, family members and other hospital personnel to deal with the patients’
awareness (or lack of awareness) of their likelihood of dying. Glaser and Strauss
were also concerned with the impact of these tactics on the patient, the staff, and
the functioning of the institution. This study culminated in the book Awareness of
Dying (1965), which formed an empirical basis for Glaser and Strauss’s
development of grounded theory. Their original articulation of grounded theory in
The Discovery of Grounded Theory (which is often referred to as simply
Discovery) drew heavily on the work Awareness of Dying.
In the Introduction to Discovery, Glaser and Strauss described the main
contribution of their new approach to social research work as providing an
alternative to the development of theory prior to empirical work. In essence, the
authors argued that the hypothetico-deductive model of scientific enquiry, where
theoretical problems are specified and then verified through research, was of
limited use in the social sciences. Theory, they suggested, was most effective
where it helped researchers to understand an empirical context, and should be
developed – or generated – in relation to an understanding of that context, rather
than in advance of it. As the authors put it (1967: 3):
Our basic position is that generating grounded theory is a way of arriving at
theory suited to its supposed uses. We shall contrast this position with theory
generated by logical deduction from a priori assumptions.
This move to empirically situated or ‘grounded’ theory development represented,
they argued, a radical departure not only from quantitative approaches to social
science, but also from qualitative ones.
The distinction between the apriori theorizing and grounded theorizing can be
demonstrated nicely through Glaser and Strauss’s own study, Awareness of
Dying. In their research at the San Francisco hospital, the authors did not begin
with a theory of how patients’ awareness was interactionally managed, but
developed their theory through detailed empirical work, consisting largely of
interviews and observations. It is easy to imagine a different approach, in which
they may have begun their study with a theoretical notion that, for example,
different pre-specified personality types manage the matter of ‘awareness of
death’ in different ways. A researcher might use their pre-codified and defined
personality categories as a means to classify the participants in the study, and to
make comparisons between them. In Glaser and Strauss’s approach, however,
all categories, hypotheses and concepts need to be derived from the examination
of data rather than developed prior to research. Theory should be an outcome of
data analysis, not a precursor to it. The introduction to Discovery provides a
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detailed description of this ‘apriori/grounded’ theory distinction. In the remainder
of Discovery, and in the various books that they produced afterwards, Glaser and
Strauss outline a set of procedures or a methodology for producing theory from
data and empirical work. In this respect, grounded theory is a methodology for
creating theory through empirical work – a methodology that is built on an
assumption about how theory ought to function.
Key components of grounded theory
Constant comparative method
The constant comparative method is a key aspect of grounded theory that
involves formulating a number of stages to developing theory through data. In
Chapter 5 of Discovery, the authors provide a detailed outline of the difference
between this approach and other common approaches to qualitative data
analysis. The distinction turns on the use of a systematic approach to generating
theory through coding and other analytic apparatus, such as hypotheses, memos,
theoretical sampling, triangulation, code properties, and so on. I will say
something about each of these in turn below. The authors’ own description of the
constant comparative method has become historically important in qualitative
research, so rather than trying to summarize it I have provided it as a reading to
accompany this unit.
Theoretical sampling
Theoretical sampling involves the creation of sampling strategies that relate to
the emerging theories being created through the interrogation of data. The people
included in the study (or the documents to be analysed, the sites of observation,
the cases of inclusion) are selected on the basis of their potential relevance to an
emerging theory. In their original articulation of grounded theory, a researcher
begins a study with quite a loose idea of who to involve in the research, usually
based on tacit and lay knowledge. The authors give the example of a study of a
hospital, where the researcher uses their basic understanding of the division of
labour in the hospital to decide to interview, doctors, nurses, and other key
personnel. As the study progresses, and the researcher gains a more nuanced
understanding of the hospital, the researcher creates different selection criteria:
different concepts to guide the selection of people. The researcher may realize
that some of the crude categories that were originally used are not used by the
people in the organization (such as ‘administrative staff’), or they may realize that
there are more subtle ways in which the people in the organization distinguish
between or label personnel that might be useful selection criteria.
The implications of this approach to theoretical sensitivity is that analysis must be
thoroughly integrated into the collection of data, and is by no means an
‘afterthought’. Analysis informs the construction of sampling procedures and of
research design more broadly, including the selection of methods, the decisions
about how many people to involve, and so on.
Hypotheses
The concept of hypotheses plays an important role in Glaser and Strauss's
(1967) formulation of their approach. A hypothesis is a statement about a
theoretical assumption that emerges from the examination of data. Hypotheses
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are also mechanisms for driving the examination of data, for creating new
sampling strategies or codes and categories.
To give you an example, I am currently involved in an ethnography that is
examining the training procedures in a trauma care ward in a London hospital.
Trauma care involves close collaboration between specialized healthcare
professionals such as anaesthetists, orthopaedic surgeons, nurses, pre-hospital
care teams (like ambulance and helicopter crews) and so on. One of the
problems that trauma care teams face is that very little formal training is offered
on how teams ought to co-operate. Another problem is that participating in the
trauma team is, in most cases, only a small part of the professional’s role. For
example, orthopaedic surgeons only spend about one-third of their time doing
trauma work, the rest of their work being dedicated to longer-term care regimes.
These two observations emerged quite quickly in our study, and raised a number
of hypotheses for the research team. One hypothesis was that there may be a
lack of professional commitment to trauma care in particular fields, and that
mistakes in care provision may occur as a result of these politicized
commitments. This hypothesis was used to select some participants for interview,
including some of the personnel who had been mentioned as potentially ‘difficult
members’ of the trauma team.
Not all hypotheses turn out to be correct, and it is a normal feature of grounded
theory work that researchers may need to re-formulate their hypotheses and
related concepts, sampling strategies, codes, and so on in the course of their
research.
Codes
A code is a category that is used to describe some general feature across a data
set. Codes are used to examine commonalities across the data set, differences
across a data set, and relationships between commonalities and differences. By
creating a category, a researcher provides a way of seeing the commonalities
across a set of cases. In Chapter 5 of Discovery (1967: 105–6), the authors give
an example from their Awareness of Dying study:
… the category of ‘social loss’ of dying patients emerged quickly from
comparisons of nurses’ responses to the potential deaths of their patients.
Each relevant response involved the nurse’s appraisal of the degree of loss
that her patient would be in his family, his occupation, or society: ‘He was so
young,’ ‘He was to be a doctor,’ ‘She had a full life,’ or ‘what will the children
and her husband do without her?’
Each instance of data that is included in the category fits the description of the
category. In the above example, this ‘something in common’ involves an
articulation of ‘social loss’.
By generating a number of codes, researchers start to create patterns in relation
to their data that categorize the data as ‘of this type’ or ‘of that type’. In this way,
the researcher specifies not only commonalities, but also differences between the
cases in their research. A researcher may realize that some of the people in a
given category (say, ‘doctors’) are different from other people in that category
because of some concept that has developed from their theory. In our trauma
care study, there is clearly a difference between doctors who are highly
committed to the trauma team and those who are not. These distinctions have
emerged through the examination and coding of data.
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Furthermore, as coding develops, researchers start to explore the relationships
between their codes. For example, it is clear that some of our ‘non-committed’
trauma doctors get their disinterest from the nature of the other teams that they
participate in, some of which regard trauma care as uninteresting, not useful for
professional development, and unsocial because of the uncertainty of the working
hours. These differences emerge through using data codes for ‘motivation’,
‘attitude to trauma care’ and ‘trauma team specializations’, and examining the
relationship between these. For example, researchers can use qualitative
analysis technology to search their codes to see the extent to which two or more
codes occur at the same time. Using Boolean search terms (and, not, or, and/or),
researchers can create simple and more complex searches of their data and
codes and find out the relationships between their codes. The results of these
searches can be used to create new codes and new hypotheses for further
exploration.
Much of the methodological discussion in the various texts associated with
grounded theory involves examining the procedures of defining codes and
relating them to each other.
Properties
The notion of properties makes a brief appearance in Discovery but is described
in more detail in Strauss’s later collaborations with Juliet Corbin. For example,
Strauss and Corbin (1987) define a property as some aspect of a code that varies
along a scale. The following extended quotation illustrates this idea nicely with
reference to a study of drug taking:
… we might say that one of the properties that differentiates ‘limited
experimenting’ with drugs from ‘hard-core use’ of drugs is ‘frequency’ or the
number of times a week the person is ‘stoned.’ We dimensionalize the
property frequency by saying that with limited use, the user is stoned only
occasionally. If we wanted to qualify or explain the term ‘limited experimenting’
even further, then we could say that the teen uses drugs and gets stoned only
when at a party with other teens at which drugs are readily available and
passed around, whereas we might say that the hard-core user is stoned very
often, using drugs three to four times a week, either when alone or when with
selected others, and seeking out drugs on his or her own rather than having
them passed around at a party. This qualifying of a category by specifying its
particular properties and dimensions is important because we can begin to
formulate patterns along with their variations. For example, we might say,
based on frequency of use and the ‘type of drug used,’ that this situation can
be classified into the pattern of ‘limited experimenting’ with drugs. Perhaps if
we do another interview and the patterns of drug use and getting stoned fit
neither identified pattern, then the analyst can develop a third pattern such as
the ‘recreational use’ of drugs. Patterns are formed when groups of
properties align themselves along various dimensions.
(Strauss and Corbin, 1987: 117, original emphasis)
Theoretical saturation and theory solidification
Theoretical saturation and theory solidification are important aspects of grounded
theory that refer to the ways in which a theory takes shape. Solidifying the
theory entails the ‘firming up’ of a theory and its constitutive components
(categories, properties and hypotheses). Here, the analyst begins to discard nonrelevant properties and categories and to work with a more stable selection of
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concepts and ideas. A fundamental aspect of this later stage of theory
development is that of theory saturation, which refers to the point at which
theoretical work (like applying a code category or defining a property) routinely
produces the same results or conclusions. For example, where a researcher
stops producing new categories, and stops modifying their categories in the light
of new data (because the existing categories are well defined, sufficient, and
suitable to new instances), then the researcher may be said to have reached
theoretical saturation.
Writing
Glaser and Strauss’s articulation of writing is quite distinct from other descriptions
of the writing process in qualitative social research. In many constructivist
approaches the ‘writing process’ and ‘writing up’ are very much intertwined.
Writing is an aspect of the development of ideas, and there is no clear boundary
between the working out of ideas on paper and writing up. Through writing,
researchers may discover new theories and ideas.
In principle, grounded theory accepts this premise, but suggests that all ideas
should be very well developed and empirically worked through before ‘writing up’
is undertaken. Writing up should be about simply putting the worked-out ideas on
paper, and not about creating anything new.
Debates and dilemmas in grounded theory
As you have seen, one of the key and defining features of grounded theory is the
emphasis on generating theory through research rather than prior to research.
One of the strongest examples of this view in Glaser and Strauss’s work (both in
their early work and in their subsequent divergent writings) is in terms of the uses
of literature. For example, Strauss and Corbin make a distinction between
technical literature and non-technical literature, the former referring to published
academic work – like books and journal articles – and the latter to diaries,
documents, reports etc. As with Glaser and Strauss (1967) and Glaser (1978,
1992), Strauss and Corbin (1987) argue that for the purposes of grounded theory
it is best to avoid using literature to generate theoretical or conceptual ideas that
can be pursued in relation to the research. In a particularly telling statement
(Strauss and Corbin, 1990: 49) they argue that:
… if you begin with a list of already identified variables (categories), they may
– and are indeed very likely to – get in the way of discovery. Also, in grounded
theory studies, you want to explain phenomena in light of the theoretical
framework that evolves during the research itself; thus, you do not want to be
constrained by having to adhere to a previously developed theory that may or
may not apply to the area under investigation.
However, both Glaser and Strauss (1967) and Strauss and Corbin (1987) also
argue that it may be useful to use literature subsequently to compare the
categories that the research has generated with other research in the field – see
Goulding (2002) on this point. In this respect then, literature may be a good way
of generating ideas in subsequent analytic stages, but not in the first instance.
A strong criticism that has been levelled at this aspect of grounded theory is that
it represents something of a disingenuous view of how research typically
proceeds. Goulding, for example, argues that Glaser and Strauss’s
characterization of their research as closed off from apriori formulation belies the
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level of their research knowledge and their prior professional experience. Further,
since the authors do not preclude the use of externally derived concepts at other
stages of the research, their insistence on avoiding them at the earlier stages
seems a little strange. If ‘external’ ideas can drive research later, why not let it
drive it earlier? Surely the effect is, in the end, the same?
The charge of positivism
This critique of a touch of disingenuousness in grounded theory is a part of a
wider critique of the approach as representing some clear positivistic tendencies.
The notions of ‘discovering’ theory in some objective fashion, the aims of
unbiased data collection, and of trying to find some external objective reality have
been strongly problematized by those who have adopted more interpretivist
stances in the qualitative social sciences, such as Charmaz (2000: 509). Glaser
has responded in characteristically robust fashion in the open-access journal
Forum Qualitative Sozialforschung (FQS) (Glaser, 2002), where he takes
substantial issue with the constructivist position.
The divergence between Glaser and Strauss
As I noted in the introduction to this unit, Glaser and Strauss later parted
company in quite a dramatic fashion. Strauss’s collaborations with Juliet Corbin
were interpreted by Glaser as involving a radical departure from the initial
formulations of grounded theory. Glaser’s vitriolic response to this perceived shift
is a rare example of ‘gloves-off’ discourse in academia and, because of this, I
have included it as another short, key reading for this unit. This reading
articulates a tough response to Strauss and Corbin’s work, and one that outlines
nicely some of the differences between the authors’ later work.
Concluding remarks: grounded theory, grounded
theory, and grounded theory
It should be clear from the discussion you have read in this unit that grounded
theory is far from a unified approach. The divergences between Glaser and
Strauss’ own work, and the ways in which other grounded theory contributors
have worked through these debates and their fit with other qualitative
approaches, have created a complex network of articulations of the approach.
Furthermore, the term ‘grounded theory’ is, in some instances, used in a very
imprecise way, and can refers to nothing much more than the undertaking of
qualitative research. When some researchers refer to grounded theory they mean
something like ‘qualitative research’ or ‘data analysis’. This looseness and
slippage of the term can make it very difficult for researchers to understand what
grounded theory really is, both in general and in specific instances of its
application. Through this unit and its associated readings, you should become
knowledgeable of the subtle variations in approach, and equipped to make your
own judgements about the particular claims being made when researchers refer
to their work as involving grounded theory.
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References
Charmaz, C. (2000) ‘Grounded theory: objectivist and constructivist methods’ in
Denzin, N. and Lincoln, Y. Handbook of Qualitative Research (2nd edn), London,
Sage.
Glaser, B. (1978) Theoretical Sensitivity: Advances in the methodology of
grounded theory. Mill Valley, CA, Sociology Press
Glaser, B. (1992) Basics of Grounded Theory Analysis. Mill Valley, CA, Sociology
Press
Glaser, B.G. (2002) ‘Constructivist grounded theory?’, Forum Qualitative
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