Blocking Conceptualization

Barney G. Glaser, Ph.D., Hon. Ph.D.

[ This paper is Chapter 10 of Dr. Glaser’s new book,
Getting Out of the Data: Grounded Theory Conceptualization,
(Sociology Press, 2011)]

My purpose in this chapter is to go into some detail on
the various blocks to conceptualization that the reader can
and should be wary of so he/she can either avoid them, deal
with them adequately to do a GT study, or submit to them
humbly for greater gains for the moment. They are
authoritative blocks, preconceptions, inability to adequately
conceptualize, the initial confusion and regression, multiversion
view of GT, QDA requirement blocks, data collection
overload, data coding overload, peer reviews, dealing with
jargonizing GT, and being a novice both in experience and in
scholarship with GT. Obviously these are related in many
ways and I have dealt with them a bit in above chapters on
helping coding. My goal here is to put them into relief for
focused attention and thought so they can be avoided or
handled.

Generating good GT conceptual ideas requires the
researcher to be a non citizen for the moments of research so
he can come closer to letting the data speak for itself. He/she
needs to be free for the research of the normal issue
orientations of everyday life so he/she must limit normal
citizen bias. Suspending issues of gender, age, color, religion,
nationality etc. are important. Therefore to avoid this kind of
block the researcher should not get into a study when he/she
cannot handle the issue as data impartially; not handle as
neither right nor wrong. Gender studies are particularly
sensitive and hard to avoid strong bias orientations. Face
sheet data has to emerge as relevant, and often none do. They
cannot be assumed as in QDA. So many GT studies have
nothing to do with face sheet data.

Authoritative guidance is a major block to
conceptualization. Authoritative guidance comes in all
forms — companies, committees, supervisors, senior
colleagues, academic department, IRB requirements etc. And
if they do not know GT with an adequate level of experience
they are likely to block coding in favor of looking for
preconceived concepts and problems and demanding
conformity to bureaucratic requirements which block
emergent coding and herald QDA descriptive requirements.
We all know this.

Evert Gummeson, a professor of business, writes:
“Although most companies confess to the marketing concept
claiming they are customer –centered with customer needs
and customer satisfaction as their prime goal which is
compatible with GT they still want to see research
descriptions on preconceived practices of marketing, textbook
theory, short term profits or long term goals or quick fixes
and demand for facts on preconceived issues.” In sum, in this
research situation there is no room for momentarily
disregarding existing demands while conceptually coding for
the emergent.

The business conceptual jargon leaves little room for
letting GT tell its theory. This goes on in many academic fields
of intense jargon, such as psychology, political science,
psychiatry, economics, to name a few that leave little or no
room for new concepts in the authorities view. Their jargon is
supported by taken for granted assumptions that influence
what is attended to by extant theory which blocks attending
to coding for what is really going on. Often the local jargon
codes are wrong or miss the gist of what is going on, yet are
assumed to have validity. So be careful of using in vivo codes
that have no grounding, even if they are descriptively
captivating, and they will likely block coding using the cc
method. The in vivo code must have interchangeable
indicators. If local jargon emphasizes an in vivo code that
names a pattern with relevance, fit and grab imagery, and
passes the indicator requirements of validity the researcher is
fortunate. It does happen but not often. And when it does, the
participants usually see the pattern descriptively by its
indicators, not conceptually though they did conceptualize.
For example a few hospital doctors may say they are acting
supernormal when on duty, and then describe what they
mean. It is only a quick thought for the researcher to
conceptual the pattern as supernormalizing as he sees and
hears others acting supernormal. Open conversations without
structured interviews will tap whatever in vivo concepts
respondents may have.

Coding overload blocking happens two ways. One
incident coding produces too many codes that are not allowed
in GT as they are not patterns. They are extraordinary,
particularistic and probably not relevant. Coding beyond
saturation of many categories, that is, each category has too
many indicators, and then not stopping generating more
codes easily ends in too many codes. Both sources of coding
overload result from not choosing a core category. And can be
stopped by choosing a core category and doing selective
coding on the core and then doing a substantive theory about
it. One only discovers at any one time a piece or slice of the
data for a core category. Other possible cores are another
study of the same data, The researcher should be aware of
this occurrence as the second project grows in his head due
to his knowledge of the data. The second possible study
should be held in abeyance, certainly not included in the first
study. In short, cut the theory down to a single size. Unless
fatigue has set in, the second study awaits with partial coding
already done. Do not let two studies block each.

Having no personal compatible schedule, plan and/or a
series of deadlines can subtly block a study. Johnben Loy
wrote me “without a deadline I found myself dragging on the
research for months. I had a deadline imposed which
galvanized me into action.” Johnben finished on schedule
then and received his PhD. A schedule with a deadline
challenges blocks and removes many of them. So the
researcher, should if needed, set himself a comfortable
schedule that he can stick to based on his personal pacing as
he/she knows he can comply with and keep up. This
stimulates the delayed action learning of GT by regular
experience. It also keeps up preconscious processing and
develops confidence in autonomous decisions. I always
advise, for example, the plan of coding a bit every night to
keep the constant experiencing of positive effects flowing.

I have seen the advice “try to see action in each segment
of data. Attempt to code using words that reflect action.” This
could be a preconceptive block on coding if taken too
seriously. Let whatever emerges emerge, just not looking for
patterns to code and name which reflect action or processes.
Many are static like types, dimensions, cutting points etc.

I have suggested line by line coding as a way of screening
and interviews or field notes for emergent interchangeable
indices. One should move fast looking for indicators, and then
skip and dip in the data once a code has been saturated.
Thus line by line is merely the beginning. It can get out of
hand and block theory if an authority suggests to a
researcher to code each line indefinitely and independently,
which leads into single indicator concepts, then concept
overload with a loss of formulation of core substantive theory.
Single indicator codes lead to a range of non valid,
particularistic codes that never gain groundedness. One
indicator does not make a code.

I have mentioned many times about over coding, but the
same caution goes to caution against under coding. An
exciting code like supplanting or like desisting residual selves
can block further coding for the joy of explaining at length by
description what it entails. The conceptual grab of the code
can feel thrillingly theoretical with great general implication
and feel that all that’s necessary for a theory. Then the study
become one of conceptual description, not GT. Keep up the
coding for the sub core codes and their properties until you
reach theoretical completeness; keep up selective coding. Do
not let making sense speculatively take over, as it can easily
as sense making comes easily to many. Sense making can
easily lead to speculative theory on one code that is exciting.

Many people are meaning finders, irrespective of data and
can conjecture a potpourri of eclectic, at will codes with no
grounding on a exciting core They quickly sense make data to
stop chaos or not knowing while following the ”grab” of the
category. The result being speculative theory. One has to
point out to them that this is not GT which requires cc
method coding.

Ruth Naylor coined the term “fear zone” to write about
the confusion and doubts that occur and block the novice
when starting the initial coding for a GT. She sees fear as the
main concern for the majority of novice PhD candidates who
are not completely brimming with autonomy and self
confidence. They need to be ok’d with experienced guidance.
As Ruth said “I have been writing to Marko and also wrote to
Annette and both of them sent great advice which helped me
get unstuck (out of the fear zone and into the do it anyway
zone)” Thus the fear zone that comes with starting a GT
blocks coding, which block can be relieved by good
authoritative guidance. But it can be a solidified block
brought on by inexperienced in GT QDA advisors, both
informal and more emphatically formal PhD advisors, who
cannot tolerate the students confusion and wish to see
extensive QDA description and coverage to feel themselves
comfortable.

The uncomfortable, inexperienced supervisor will form up
the novice student with preconceived categories, committee
and school requirements to undo the confusion and rescue
him from fear. The experienced supervisors and colleagues
will themselves learn from their help to handle unclear coding
and confusion, which redounds to the confidence of the
novice. Thus the inexperienced GT researcher questing for
help, usually a PhD candidate, must chose their authoritative
advisor help wisely or they can be derailed and blocked from
coding easily. Joining computer networks of GT researchers
on the PhD is great for encouragement, support, specific
helpful ideas and relieving blocks.

Also the inexperienced GT researcher must avoid or
learn how to handle the inexperienced supervisor, who wants
periodic work checks and then imposes QDA requirements.
Fears cannot be successfully handled when taken to senior
advisors who do not do or understand GT from reading and
especially from experience. The novice must know his “outs”
or he will find he must compromise with the performing
requirements of committees and advisors. If the novice cannot
find help then he can be lost two ways, both in doing the GT
alone as a minus mentoree and in being at odds with his
department’s socially structured vested fictions yielding
schedule and content requirements activated by a conforming
supervisor.

The fellows of the GT Institute are all experienced
authoritative helpers and, of course, my and Judith Holton”s
seminars rescue many novices quiet successfully. And as GT
spreads throughout the world the availability by internet
grows of experienced colleagues who can help support the
novice and support the GT conceptual thinking style. Asking
questions of these colleagues will help handle personal
impasses starting with proper conceptual coding using the cc
method.

The fear zone of inexperience is expressed by many. One
wrote Judith Holton who is a highly experienced GT
researcher: “I am a little bit struggling with my GT analysis as
I have reached the conception theoretical level enough and
instead tend to go back to the descriptive out of anxiety
(arising from not knowing where my analysis is going)” Judith
replied wisely “As to staying conceptual, yes it is easy to slip
back into description when we are worried about where our
analysis is going and whether what we are is going to be good
enough. The important thing is to recognize that this
regression is a natural part of the GT process and that the
antidote is to stay open and trust in emergence. It works.”
Yes, keep going and trust to preconscious processing of
interchangeable indices and that the eureka moment is not
far away.

Another student wrote: “had supervisor meeting with my
two supervisors only yesterday… I am in a lot of difficulty with
supervisors understanding of classical GT and descriptive
writing. In final analysis I have tried to hold on to principles of
GT in my write up style, but I am under a lot pressure to
complete second drafts of chapters and I lack support from
my supervisors.” The concern is clear: being supervised by
authoritarian professors conforming to the school,
department and QDA requirements can easily block the
novice GT researcher from the very start or even midway into
his research. The novice should be careful of the program and
supervisors he chooses. Taking on the QDA formal approach
to the Ph.D. with a GT analysis may not work, the block
maybe too hard to overcome for the novice. The novice should
be humble. Initial fear of doing GT correctly cannot be
successfully allayed when taken to supervisors or colleagues
who do not understand GT from the “having done it”
experience. The GT jargon can be learned by reading my
books but requires experience of doing a full GT research
study, to not let the jargon slip into QDA description.

In spite of what Tony Bryant says “by late 1990’s GT was
far and away the most widely claimed method for social
research, eclipsing all other methods put together,” many
researchers engaging in GT still have little or no awareness of
conceptualization, conceptual level and therefore the
integration of conceptual levels. Because of the multi-version
view of GT they still can do QDA description as GT and not
know the difference or simply know of QDA’s legitimacy as
supposed GT. This, of course, accounts for the volume of
jargonizing GT advocates supposedly legitimating GT.

The draw of QDA is clear. Most people see description as
a natural way of seeing life. Many researchers find it hard, if
aware at all, to give up time, place and people in favor going
on the conceptual abstract. Changing to a conceptual level
requires an ability many QDA researchers may not have to
develop or barely have Furthermore, many QDA researchers
have an annoyed aversion to being categorized by or within a
pattern, preferring to remain particularistic and descriptive.
In sum, there is a general block among researchers to lifting
data to a conceptual level since most people are descriptive. I
am always surprised and delighted when an individual
emerges from the group that NEEDs the conceptual level, in
spite of all the descriptive research. The reason is that they
have conceptual ability, however latent, so description seems
repetitive and often almost boring by saying the same thing
over and over in different ways, when they have automatically
conceptualized the pattern. GT then becomes just what they
want to do for research. Choosing to do a GT starts their
autonomy from fellow QDA students and QDA supervisors.
The drift back to the descriptive level at times occurs as
natural, but not by choice, as they code and learn the skill to
maintain the conceptual level and a new way of thinking.

Keep in mind that suspending QDA rules of data
collection and analysis, as well as the literature so as not to
block a GT study, does not mean throwing out all one has
learned. The cc method is after conceptualizations of “what is”
not what ought to be. Suspending and remaining open to
what is really going on will soon transform the beginning
novice researcher to simply going where the data leads. Most
will go through the eureka effect (finding a core category with
grab) fairly soon and then suspending becomes routine. But
keep in mind that for the novice and his supervisor (s) they
must be able to tolerate a period of ambiguity and not
knowing to suspend extant, preconceived knowledge. One
must stop overlaying what is going on by what should go on.

This is particularly hard for ideologically driven people or
people with considerable research experience in other
methodologies. They have some unlearning or new learning to
do to supervise a GT research. Competitive department
teachers add one more possible block to coding with full
departmental support. I have seen that even though a PhD
committee delivers the usual QDA rhetoric of worrisome
accuracy, immaculate descriptive capture and conforming to
a particular theoretical perspective rhetoric, they can still be
overwhelmed by the richness of a GT, once the core and some
sub core categories are discovered. Blocks are then lifted.

However if the worrisome accuracy concern persists in a
committee by wanting many illustrations of codes like they
are evidencing findings as valid and wanting the researcher to
show how he/she got to the code, that can block coding. One
comment on Anna Sandgren’s dissertation “She did not give
example of how she got to the concepts i.e. she should have
illustrated the theses with field notes” Ana had to explain that
illustrations are just that. They are not evidencing, and that
codes are not findings requiring backup data. They are
conceptual abstractions which can be varied by conceptual
properties. Anna was not blocked, but a novice could very
easily be blocked by such derailment to the descriptive level.

To be sure, the novice GT researchers using classical GT
exhibit as best they can method loyalty to GT. But
supervisors with method a loyalty demand to a QDA style will
block the novice’s coding from the very start. The supervisor
will need to rescue the novice from “not knowing” and
confusion by suggesting the loyal using of QDA frameworks
and preconceptions to coding. Under this condition staying
open will be closed down for the GT novice and the evolving
learning curve of GT will be shut down as apparent
ineptitude. Data overwhelm is likely to result. What the novice
has to offer in being open to the emergent patterns is lost to
the QDA description orientation and worse yet to descriptive
redundancy of keeping the citing of interchangeable indices
as if a generalization not a pattern. The novice’s inexperience
with GT is not a confusion block, it is an open benefit to
fostering getting out of the data, but this is hard for the QDA
supervisor to grasp.

It very difficult to understand and develop method loyalty
to GT prior to using it. But if the novice has the courage to let
the problem concepts emerge in the face of QDA demands,
once the main concern and core category emerge, it provides
an armor very hard for the QDA supervisor to pierce and tell
the novice something different. Especially hard, even if the
/QDA supervisor wants to see pet codes or what he feels
should be going on. QDA descriptive capture will soon be
forgotten in favor of the emergent patterns of main concern
and core category and further into the memoing for a theory.
I cannot say it often enough: it is vital for the novice to find
supervisors who enhance the openness of coding. That is, find
a supervisor with open enhancer strategies.

Some schools through their departments and then
committees require lock step planning for the dissertation.
This kind of planning does not suit a GT. It blocks the
experiential growth that comes with the flexibility of abstract
coding. The implied plans are typical for QDA descriptive work
and descriptive generalizations and not intended for GT
abstraction which requires a variable action like everything is
going on at once as the theory grows, at whatever pace. The
pace is usually faster than a preconceived plan predicts which
is often recited in heavily jargonized terms.

Here is an example of a plan written on Jan 2011 that
goes on too long: “I am currently reading Theoretical
Sensitivity and Doing GT as preparation. Thereafter, I hope to
secure an on-line support as I prepare my proposal. My
faculty is comfortable with my choice of GT, but I still have to
succeed with my proposal. I hope to have the proposal ready
for June 2011 and ethical approval for access to the hospital
also by June 2011. Then I will probably need a year of being a
big ear with observation and interviewing before the main
concern and its continual resolution should emerge. That
would leave me with six to nine months to integrate the
relevant literature into the emerging GT. Then, six months to
do final writing up, editing and defense of the PhD. Then,
hopefully I would write the book/paper either in 2013 or
2014. I hope to finish my PhD in about 24 to 30 months.”

Obviously this plan is based on inexperience with
actually doing GT as she will soon learn. It is bare of the
immediate disciplines that arise when doing coding, such as
coded every night, constantly stop to memo, trusting to the
emergent using the cc method, selective coding and
theoretical sampling as to what is next, etc. Staying open to
the fours S’s of GT is important. GT goes on simultaneously,
sequentially, serendipitously and short range schedules. So
much goes on all at once as it sequences, no preconceived
plan fits.

The distinction between QDA and GT requires that the
dominant QDA community gets the difference between
conceptual and descriptive research and that coding to
conceptualize based on the cc method procedure is the only
way to really know GT. The QDA continued jargonizing of GT
suppresses coding in favor of data worries, lofty talk and
worrisome accuracy. As I said in my book “Jargonizing”
(Sociology Press, 2009), the GT vocabulary is way ahead of the
GT method and GT product. Jargonizing GT is usually
without proper GT meaning. It does not require procedural
talk. It just remodels GT to a QDA with no clear procedures,
folksy idioms, rhetorical musings and lofty talk. To
conceptualize is ignored by QDA writers in favor of
description, so implied is why should they care about the
careful procedural emergence of codes. All this blocks the
need to get out of the data abstractly by starting the real work
of GT: conceptually code. The novice will feel blocked until he
finds an experienced GT guide. And as the volume of GT
researchers increase with the jargoning popularity so does the
blocking of conceptualization increase. However this also
increases the many who run aground in the QDA confusion
and then find and come to conceptual GT as true believers
who have at last found their way.

One student writes: “I would like to come down and
spend some time talking to Barney regarding my GT progress.
I do not have any advisors who speak GT and the ones I do
have continue to have suggestions that I leave GT and use
QDA. I have a deadline for a pre-reading on 12/9 10 and I
submitted a bit of conjecture to satisfy the college and it was
a total waste of time.” So I met with her and afterwards she
wrote: “Thanks so much for yesterday. I am so excited at the
theory that is writing itself right before my very eyes.”

Here is more testimony examples to the exhilaration from
coding: Another student wrote me, Linda Poiseroux,
“Honestly, using GT is the best choice I ever made. It was
amazing to see the data emerge and form into categories/
properties allowing the main concern and core category to
appear. What a thrill”, Phyllis Stern wrote me, “Well the
theory does rise up off the page as the terms implies, but after
painstaking coding, when you finally get it, it seems like a
second coming” Another student wrote me “also I want to tell
you that when you go back to data you see things you never
anticipated.”

Bashing GT coding by QDA researchers can severely
block coding. A student writes, “GT studies have been
criticized for possessing some mystical quality where by a
slight of hand produces a list of “themes” and we are invited
to take them on trust that they somehow emerged from the
data without being offered step by step explanation of how
they have been built up.” It is difficult to ascertain the
credibility of research if the product cannot be linked
explicitly with the process… The way in which the process is
actually executed remains largely elusive with inconsistent
and therefore no way to ensure credible and trustworthy
research.” This researcher has absolutely no conceptual
ability or vision and does not study my books. He just
jargonizes wanting QDA evidential proof. How codes are
discovered is a simple a set of procedures in print since 1965.
His bashing however naive and unwarranted and unscholarly
could easily block novice researcher who is in the fear zone.

Suddaby, in his paper “What is Wrong with GT” bashes
GT too. He says, “A common characteristic of most efforts to
use GT is a neurotic overemphasis on coding. That is the
ridged application of GT techniques might produced passable
results but such mechanical approach usually lacks the
spark of creative insights upon which exemplary research is
based.” This statement would block the coding joy of any
novice GT researcher with its doubtful implications of coding.
Again, he has a very “QDA view of conceptual research and a
lack of knowing GT procedures. Suddaby complains, “The
process of data analysis including techniques and category
creation should be made apparent to the reader.” The cc
method paper has been published everywhere and first in
1965, So much for his poor scholarship which leads to
bashing GT.

There is excessive concern of ethic committees and IRB
boards for the privacy of respondents when doing GT. There is
no notion that their concern may apply to QDA description
but not to GT abstraction, where time, place and people are
left out. They do not know the description/conception
difference. As a result they require consent forms and usually
approved interview guides, and specific data collection
populations, all of which block flexible data collection, flexible
coding and theoretical sampling. IRB requirements can
strangle the open, not preconceived nature of GT. GT cannot
legitimately follow the theory quest as it emerges from coding
and changes relevancy of topics, populations, locale, etc.
Open conversations, so useful to emerging codes, as a
byproduct of strict interview guides are forbidden by consent
forms. They go on anyway, but their forbidden nature is
blocking of full collection and use in order to keep them nonrevealed.

Some professors of QDA research say that “doing good
research demands some form of linkage between the
philosophical, theoretical perspective and methodological
consideration that together constitute a coherent approach to
knowledge. This stops coding in its tracks. It is rhetorical with
no meaning for GT. How to solve this is not the researcher’s
problem. Trying to link GT with a philosophical, theoretical
perspective blocks it use to a particular data. It privileges one
data type over another, like specializing in constructionism or
symbolic interaction or systems theory. It does not address
the notion that GT is a general methodology using any data.
This lofty talk demands that the data used be with the
theoretical perspective chosen All this detracts from the “all is
data” and all data has patterns, general approach of GT.

Coding as soon as possible shortens this fear zone period
by the experiencing the exhilaration and joy of the “drugless
trip” ending in the “eureka, I’ve found it” feeling of discovery.
The reader can see from this chapter that I could go on
endlessly to show that there are countless blocks to coding
conceptually coming from many quarters. They are, to cite a
few: school PhD requirement structures, PhD formats,
department structures and perspectives, inexperienced GT
professors as supervisors or external critics, preconceptions
from many sources, IRB requirements’, journal peer
reviewers, QDA bashers of GT, novice fears, general and
authoritative inexperience with GT, inability to conceptualize,
multi-version view of GT, tape recording, computer
management of concepts etc., etc. most which follow the
standard QDA description model. There are more.

I can only hope that the researcher using GT will be
aware and wary of these blocks, and more unmentioned here,
by knowing many indicators of them, for himself and his
GT’er friends, and overcoming them to take a chance on
conceptual coding and the ensuing exhilaration of the
drugless trip to the eureka moment of discovery.

In closing this chapter, here are my comments on several
data worries quotes from social constructivists with no
realization of GT abstraction. These quotes are a sure block to
coding what is going on:

Quote: “With much of emphasis placed on coding
procedures, theoretical saturation and theorization, little
reflexive attention appears to have been placed on the
construction of interview data and possible statements for a
reflexive approach to GT to handle criticism of ways of using
data collected via traditional GT methods.”

My comment: There is no traditional data collecting
methods in GT. “All is data” and it is up to the researcher to
figure out what data he/she has and code its patterns. What
reflexive means here is not detailed! It is just lofty talk to
engender data worries which in turn blocks coding for the
abstract level. Use of data is the emphasis in the quote,
whatever that means in constructionism, but it sure blocks
GT coding by the cc method.

Quote: “Constructivist grounded theorists acknowledge
that categories, concepts and theorization do not merely
emerge from data but rather are defined by the researcher.
The constructionists list several limitations of GT data: 1.GT
researcher bases his data on his own conception of
respondent. 2. He treats the respondent as a vessel of facts. 3.
He ignores the inscription devices in the construction of the
interview and 4. He treats the data collected as reports that
are reality.”

My comment: These are descriptive data worries of QDA
researchers. “All is data” for the GT researcher. Whatever the
data is it is coded by the cc method for patterns, which are
not preconceived. If anything the constructionist says is
relevant, it will emerge in the coding. The abstract level of GT
leaves the constructionist concerns behind to wallow and
wrestle on the descriptive level. What is real for the GT
researcher is exactly what is going on in his “whatever” data
and data mix.

Quote: “Constructionists acknowledge the mediating role
of how categories and concepts are constructed by interviewer
and respondents as coproducers of knowledge.”

My comment: Thinking about this statement would block
anyone from coding. It sews doubts about codes using the cc
method for abstraction in favor of accurate description, if ever
achieved without argument doubts. It puts more block on
abstract coding by emphasizing coverage of descriptive data
and worse yet, by emphasizing the particularism of each
individual respondent, so impossible to generalize. If a bias
exists in anyone interview, it is just another variable to be
conceptualized. It is hard to jump into GT conceptual coding
thinking about all this, which has a series of descriptive
concerns with no realization that GT coding follows a pure,
variable conceptual track.

Quote: “From the outset of a study the lived experience of
the participant is assumed to be accurate and then is
mediated by the researchers’ various technologies and
inscription devises he employs. As the interview travels
though these technologies less of the respondents experiences
are captured. Yet, paradoxically the constructivist researcher
provides the participants with more responsibility and more
voice in categorizing themselves as much as possible.”

My comment: All this is absolute NO for GT. The GT
researcher just codes the data, over many respondents, for
patterns of what is going on as “all is data”. Very few
respondents know their abstract latent patterns, and if one
does seem to that is just more data to code. The goal of
constructionism is descriptive coverage and coproduction of
accurate knowledge. This not the goal of GT abstraction. In
GT, respondents are not the passive vessel of objective
knowledge as constructionists accuse GT of treating them.
They are the data, whatever it may be, and the data is coded
conceptually in abstraction of their lived experiences.
Respondents’ participation to a level of collaborative research
is totally irrelevant for GT.

The constructionist block on conceptual coding, however
unintentional, is clear. Their needs have no place in GT
research. Nor do constructionist views on data collection
make for an out dated classical GT that needs renewed
legitimacy. Constructionism is just a different methodology
trying to take over classical GT using the multi-version view of
GT to accuse GT of failing descriptive objectivity. For GT their
arguments are not relevant. The novice GT researcher would
find it hard to code if he/she joins in this discussion, which
can easily be ignored.