Qualitative and Quantitative Research

Originally published as Chapter 7 in Glaser (2003). The Grounded Theory Perspective II: Description’s remodeling of grounded theory methodology, Mill Valley, CA: Sociology Press, pp. 99-113.

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

The main point in the next two chapters is that the methodological literature is filled with references to the quantitative-qualitative conflict or opposition. Qualitative data is credited with providing the meaning and factual interpretation that quantitative data does not, thus it is more accurate in findings, interpretation and theory as opposed to the conjectures that explain fabricated quantitative findings. Qualitative data is real life collection of data that avoids the quantitative distorting difficulties in collecting data by preformed questionnaires and overly simple analytic techniques. The arguments go on and on as to which is objective and which subjective, which is harder science and which is softer.

Among some groups of researchers and some fields, qualitative data research wins this continuous opposition. With this QDA power GT is drawn in as a QDA research method, since most GT is done with qualitative data which is relatively easy and inexpensive. GT becomes eroded, and default remodelled by QDA in the process, hence blocked, simply because most GT research to date is done with qualitative data. Its fundamental theoretical orientation is seen by consequence of this remodelling as symbolic interaction. But this is not correct, since it can be used with any theoretical codes, from any theoretical orientation. Most GT uses structural functionalism — theoretical codes actually — such as conditions, contexts and consequences or scaling codes, such as degrees, dimensions, cutting points, ranges, zones or typologies.

GT is a general methodology that can be used with any data, I have said time and again. It is an inductive methodology. Qualitative data does not define GT; GT just uses qualitative data mostly — but among many possible data. “All is data” for GT, since all data has latent patterns. It can use any data and any data in any way and in any combination: it can use qualitative data and quantitative data solely or in any combination.

It is paradoxical that so often qualitative researchers denigrate quantitative work as work with no symbolic meaning interpretation. Yet they laude it as science and try to make QDA look like science with quantitative trappings. Whatever the solution to this paradox in any researcher’s position, GT is abstract of it. GT just inducts abstractions or concepts from what ever data is being used. This paradox of a qualitative research making puts a reverse block on GT. GT is blocked by QDA erosion in many ways and a further consequence is that this cooptation totally blocks GT from being used with quantitative data.

But, to repeat, GT is a general inductive methodology that can be used, with excitement, with quantitative data. My dissertation, which was published immediately as a book (Organizational Scientists: Their Professional Careers Bobbs-Merrill, 1964), used quantitative data exclusively. It was an inductive core variable analysis of scientific recognition. It was modelled after Lazarsfeld’s The Academic Mind the Free Press, which was an inductive core variable analysis of apprehension in academic life during the McCarthy era. There were many monographs coming out of the Columbia University Sociology Department at that time that were pure inductive discovery using quantitative data. It was what was done as a norm.

In chapter 8 of the Discovery of Grounded Theory, “The Theoretical Elaboration of Quantitative Data” I wrote at length on the use of quantitative data for generating theory. The point of the chapter was to illustrate the careful relaxation of the rules surrounding quantitative data for the express purpose of generating theory. The rich veins in quantitative data can be mined when analysts relax their quantitative rigor in favour of GT rigor. If quantitative data is -handled systematically by theoretical coding of variables in elaboration tables, the analyst will indeed find rich terrain for discovering and generating theory.

I used Lazarsfeld’s elaboration analysis combined with my -discovered method of consistency analysis. It is a property space approach to induction, using index formation and four fold and three fold tables. Other techniques are latent structure analysis, reason analysis, multi-attitude distribution, some forms of content analysis and so forth.

These techniques can be used with original data and with secondary data. The later is abundant, since so much quantitative data is collected and not analyzed. So most often inductive analysis of quantitative data was a secondary analysis of a small amount of a large survey. I myself used data from a humongous survey of scientists. I choose a sample of the numbers of participants and a sample of the tested questions pertaining to recognition.

Also, in combination, a GT using qualitative data can be used before and after a quantitative study. A GT done before can suggest items for a questionnaire and can suggest salient hypotheses to verify. After a quantitative study, a qualitative GT of the substantive area leads to grounded explanations of quantitative findings and future research directions.

The after approach would stop the conjectural interpretations of quantitative findings. The after approach stops the non-scientific explanations of scientific data which is a paradoxical travesty. So much time and money is spent on getting objective data that is explained by an immediate particularistic bent of one interested party, who conceives of him/herself as generally knowledgeable. But is he/she??? They will say yes, but that is not scientific.

It never occurs to many researchers, using the before approach, to analyze the qualitative data when a qualitative study is done to form the questionnaire for the purpose of providing explanations for the quantitative findings after the study. What a loss.

Now let us look at the quantitative-qualitative opposition from the point of view of the blocking, eroding and remodelling GT.

The Call for Qualitative Research

The growth of qualitative methods and GT commensurately and its final acknowledgment as science has not really upset or subverted quantitative research. It is still seen as the most objective science in many disciplines, however strong qualitative research has become. As applicable in many other disciplines, Gummesson says “What is taught to students and PhD candidates in business schools is still essentially that quantitative techniques will give us the truth and that qualitative approaches are just preliminaries…. Quantification has become so ingrained in the mainstream of education that complying with its specifications and publishing it accordingly is the fast lane to a university career, even the single lane. At the same time, we fail to offer proper education in qualitative methods, which require more of personal maturity, sound judgment, involvement and interaction.” (“Are Current Research Approaches in Marketing Leading Us Astray,” in Marketing Theory, 2001) Professor Gummesson is right. Distance from the meaning of data is seen as more scientific compared to involvement in data by qualitative methods which is seen as subjective bias, interpreted from accuracy and distorted compared to quantitative data. The zeal for accurate QDA descriptions to meet this criticism erodes the abstraction aspect of GT when it is seen as a qualitative method. GT is not concerned with accuracy as objective or subjective, it is all data that is used to generate concepts for GT. (SEE “Are Current Research Approaches in Marketing Leading us Astray?” Evert Gummesson, Marketing Theory, 2001)

Quantitative research has a low theory yield that has deadened for over 40 years research in many fields. Survey techniques have been improved and useful in selected situations, such as political poles on “over news-ed” issues, but have not fundamentally improved their ability to provide theory. “The supremacy of quantitative measurement shuts out most of reality and hence the creation of more general theory”, says Professor Gummesson.

He is not against quantitative approaches per se, what he is against is their claim in that they are better, even the only science. In business research their claim has succeeded in acquiring a disproportionate share of research activity. “Counting and classifying can only take one so far. Meaning and interpretation are required to give significance to counts and classifications and these come from qualitative research,” says Gummesson. This call to qualitative research for after survey research has to counter the non-science image in the quantitative researcher’s eyes. It can be labelled “anecdotal evidence” in a derogatory way. The credibility of QDA is based on accurate description more than conceptualization, when trying to add qualitative research to a quantitative research realm. Thus the use of GT in this situation is eroded and remodelled. In chapter 9 below I shall discuss at length credibility’s requirement at length as an erosion of GT.

The use of GT as a qualitative methodology in this legitimizing method-mix is clear when Gummesson says “I have chosen for my methodology-in-use a package of the aforementioned approaches: Narrative research, action research, ethnography, GT and case study”. This method mix of qualitative methods is quite typical of the first forays of researchers leaving quantitative research and tempting qualitative research. GT abstraction cannot withstand the intense descriptive orientation of these other qualitative methods. Hence it is remodelled by default.

In adding meaning and research interpretation to quantitative research, qualitative immediately challenges the sampling techniques of quantitative research, the objectivity of questionnaire items vs. the assumed subjectivity of interviews and, worst of all, the qualitative results that are contrary to the pet idea, hence the vested fictions, of top management in whatever structure. In this challenge GT has no chance of NOT being eroded and remodelled. In order to meet this challenge to quantitative research, QDA sampling of a routine clear population in a unit was barely, legitimately enough of a departure from quantitative random sampling. GT theoretical sampling is too deviant to quantitative formed researchers. Efforts at total accuracy by QDA again are enough of a departure from so called questionnaire objectivity. “All is data” of GT is too much of a departure for the quantitative oriented.

Lastly, conjectured interpretations of quantitative results bring the research into consistency with pet ideas of the corporate managers. Researched interpretations, especially those of GT which are powerful in their abstraction, are too contrary, even seen as subversive, to management. Clearly to remain pure to its integrity, GT must stand alone as a general method, not as a meaning provider to quantitative methods.

As QDA brings meaning to quantitative research, it also brings another resisted dimension. QDA raises new or untouched topics which further points to the gap between quantitative research and the reality of action in process. As Gummesson terms “The shallowness of quantitative studies” totally neglects analysis of services marketing and relationship marketing, which are so vital to business and so damaging of the ideal of free competition. QDA descriptions were enough of a challenge to this status quo, which descriptions are embalmed in the literature of the field. Abstract propositions generated in GT again are too general to tolerate, hence GT is reduced to description.

The rules of quantitative work are bulwarked by particularistic fictions in their use. The less apparent rule-bound qualitative research is threatening. Thus the new rules of GT procedures, while very rigorous, are too much to take on in a quantitative atmosphere, so GT is remodelled to a QDA method.

Qualitative research also provided as part of meaning the “Voice” of the participants, access to participants and interesting, stimulating reading about the participants compared to the deprived access to the data in a survey. GT does not deprive voice of and access to participants, but its abstraction of the access is disconcerting to those who at last get to the data. And of course, QDA’s making reading scientific research stimulating and easy rather than the stiff difficulty of quantitative articles is clinched by vital description rather than conceptualization. Thus GT is eroded to a QDA method and legitimates it as the most procedurally complete and balanced method available.

The constraint by quantitative methods to make qualitative research look “not unscientific” clearly erodes GT when it is caught up in this progression. Contrary to many researchers’ beliefs, the positivistic criteria that dominate quantitative research are specific to it, not general to all research methods. Thus as we said in Discovery of GT qualitative research in general and GT in particular require different criteria for research that does continuous theory generation. And we have set them forth clearly in Discovery of GT and in Theoretical Sensitivity. A GT should fit, be relevant, work and be readily modifiable.

In particular GT requires continuous modification, not verification, and the subjective is conceived of as another form of objective reality. While in quantitative research subjective data is thought of as objective when it is aggregated, or congealed subjective, that is summations of subjective responses to questions in a questionnaire. For GT what is real is what is happening, however level of truthfulness. Once seen, extracting GT from being eroded into another QDA method in this progression from and reaction to quantitative data is not hard. One need only go with abstraction and conceptualization, and leave description to QDA researchers.

“What is science” is often treated as the empirical world narrowed down to quantitative data and statistical techniques of handling it. Actually it is the quantification of subjective responses which is the paradox. Qualitative research is not as “science” and merely an antecedent to deduction and quantification. Then conjecture takes over as interpretation of quantitative findings by selective referring to existing non research related findings based on cultural views, as well as some “ought” to be related research. In fact for those who see this demarcation between quantification and qualitative research for what it is, the distinction dissolves and it becomes common sense to use both methods for a research.

Again it becomes hard for GT to resist being drawn into qualitative method attribution and erosion by these transcending researchers. Default remodelling GT has to please both methods and their criteria. Simply going with GT abstraction and conceptualization is an easy way out of this erosion from being drawn into this method mix. It necessitates no argument, just knowledge of what GT is and doing it as conceived.

It is wise to respond to the call for the meanings in qualitative data in the face of the distance of quantitative data from meaning. BUT it is also wise to be careful of the implications for eroding GT by descriptive capture.

Succumbing to Quantitative Techniques

In spite of the recent and current zest for qualitative research there is however frequent succumbing to properties of quantitative research. Researchers weaned on quantitative methods may -succumb to overwhelming urges to reduce their qualitative data to numerical categories or neat variables. They seek to achieve respectability for their results at the cost of more penetrating analyses or interpretations that might raise questions rather than put them forever to rest. Qualitative research somehow gets quantified. It may be done by content analysis or often with computerization that sums instead of tapping the rich complexity of qualitative data.

This depicted researcher cannot live with the ambiguity, uncertainty and tyranny of worrisome accuracy in the data. He cannot tolerate it, so retreats to the objective reality of quantitative manipulation of data which he feels lead to objective facts independent of the researcher. Lack of tolerance is resolved. There is no longer doubt of qualitative accuracy. This retreat, of course, loses qualitative meanings.

If GT is caught in this retreat from a QDA method to quantitative trappings it is of course remodelled, but it is actually a moot issue for GT. GT is abstract of worrisome accuracy; it just conceptualizes latent patterns. They get modified by property generation when compared to new data. I have written at length on this. My discussion in the following sections will always come back to this simple circumstance: no matter what the problem between quantitative and qualitative methods, GT will not be eroded in the bargain if GT is seen as abstract of these data concerns and able to use all data.

Realistic Combinations

GT is in the middle of the quantitative-qualitative continuous controversy, which is basically different stances toward descriptive capture and focuses on worrisome accuracy. The issues of description do not apply to GT which is abstract of them (See The GT Perspective). Qualitative researchers keep up positivistic thought in a myriad of ways to achieve “solid research” so they affirm. As Janice Morse et al says in 2001, “We suggest qualitative findings are still not regarded as solid empirical research. A number of leading qualitative researchers argued that reliability and validity were terms pertaining to the quantitative paradigm and were not pertinent to qualitative inquiry.” They offer their solution to this controversy. (See International Journal of Qualitative Methods, vol. 2, no.2).

Given the preponderant use of qualitative data by GT researchers and the disuse of quantitative data by GT researchers, GT gets drawn into the qualitative side of the continuous controversy. It is then remodelled by QDA rigor requirements and good GT is consequently blocked. Actually GT can be used with both types of data (quantitative and qualitative) in any combination and integrate them in various ways while leaving out the issues of back and forth controversy. As we said in Discovery of GT, GT has its own canons of rigorous procedures, before, after and during the research.

Hans Thulesius, an MD in Sweden who has generated an excellent GT on balancing cure and comfort care in end of life cancer care (palliative care) sees this vision and promise when he says: “But I think that you should know that I consider researchers as prophets more or less, and you are a very good one! I think that GT is a method which is so underutilized that if properly recognized it would revolutionize many areas of research and not only qualitative data studies, but a merge with quantitative data analysis. It would give new important knowledge to biomedicine in its connection with nursing and other soft areas of health care. Unfortunately not many researchers today have their feet in both fields or recognize the need to be in both fields, but this is essential in order to optimize the discoveries in biomedicine and apply it to real life for real people. So I think that in 10–15 years time if properly developed — GT and variations of GT — could play an even more important role in medicine among other areas. This is my impression after experiencing GT and its power.” (email April 9, 2001) This, of course, applies to all fields, since GT is a general method.

In a subsequent email on April 15, 2001, Hans actuates his vision: “At the moment I’m doing statistical factor analysis of a screening instrument for posttraumatic stress disorder. I have responses from 300 persons. Factor analysis is about concentrating and condensing questionnaire items and finding new dimensions in data. It’s fun to have the GT experience while doing statistical work. I feel that a whole new world of understanding would unfold if using GT more with quantitative data. Mixing the creativity of thinking from GT with all those powerful statistical tools seems to me like an exciting potential for future research methodology innovations.” I showed his vision to be quite true in my dissertation using quantitative data, “Organizational Scientists: Their Professional Careers” 1964, Sociology Press. See also “Theoretical Elaboration of Quantitative Data”, chapter 8, Discovery of GT.

In his article “Bridging the Quantitative-Qualitative Divide in Political Science” June 1995, American Political Science Review, Sidney Tarrow chastises King, Keohane and Verba’s renowned book, Designing Social Inquiry, which takes the position that “a slightly more complicated theory will explain vastly more of the world”. Tarrow says “If this is so, they really ought to have paid more attention to relations between quantitative and qualitative approaches and what a rigorous use of the latter can off quantifiers.” “They offer very little about how qualitative approach can be combined with quantitative research.” Tarrow continues “More and more frequently in today’s social science practice, quantitative and qualitative data are interrelated within the same study. We need to think more seriously about the interaction of the two kinds of data.” His paper addresses this interaction.

He sees quantitative research as providing data on large numbers of single observations and qualitative data providing data on large numbers of variables in the same area. Then the results of the combined interaction of both types of data are many. Qualitative data research can then turn to history, culture, and current data to interpret quantitative data by tracing processes for an event and it can reveal tipping or non-systematic variables that interrupt -systematic time-series patterns, often permanently.

He talks about sequencing the two types of research so each leads to research based on the other: quantitative work leads to qualitative inquiry for interpretations and then this leads to a more pertinent questionnaire for quantitative research and on and on. He talks of “putting qualitative flesh on quantitative bones” by doing a subsample of a survey sample to research qualitatively by interviews the quantitative findings. Then doing another survey based on the QDA findings. He talks of combing both types of research at once on the same problem to triangulate the results, to achieve the most appropriate and specific hypotheses. He concludes that “a -single minded adherence to either quantitative or qualitative approaches straight jackets scientific progress. We should try to use different kinds of evidence together and in sequence” on the same problem.

Where does GT stand in these thoughts that I do agree with? Tarrow leaves out GT totally by implicitly seeing it as a QDA method. Hence again GT is dragged into QDA and eroded by the latter and good GT is blocked. This is a shame because actually GT can solve his quest for combination of the quantitative and the qualitative since it can be grounded in both types of data sequentially and/or at once and the resulting generated theory can be abstract of both. GT uses all as data and is abstract of what ever data it is grounded in. It is realistically perfect for the task of combination.

This combination of the qualitative and quantitative presents a problem that GT can solve. Either type of data has its analysis style that can dominate the other. Take the causal model. Quantitative analysis simplifies assumptions and causes of an event. While the qualitative analysis complexifies with many variables causal clusters of the event, GT can combine and generate a theory using both models without either dominating or without losing the best features of each causal model. GT disaggregates or deconstructs the polarity of the causal models of each method, by abstractly using both to explain what is going on both within the large aggregated numbers of quantitative findings and the case-orientation of qualitative findings.

Thus quantitative findings of the prevalence of say, visualizing deterioration on an ICU by nurses receiving no medical response can be explained by the non vital sign in-depth variables involved gained in qualitative research. GT uses all the data in the emergent theory on resolving such a concern. Empirical generalizations about large social units should not be explained by conjectural theory. They should be explained by qualitative research on the same problem either at the same time or sequentially using the constant comparative method of GT. Constant comparing the case data with the survey data works to generate theory.

Large unit analysis is hard to come around to this view. In an article: “Beyond Quantitative Research: Exploring the Reality of Welfare Policy,” July 1996, a paper given at the National Association of Welfare Research Workshop, Bonnie Glaser and Karen MacDonald say “Welfare research and demonstration projects are dominated by the quantitative approach, leaving little or no resources for a qualitative component.” “Qualitative research is more often conducted separately from funded evaluation projects, rather than in conjunction with those projects because research objectives are different.” They assert “Descriptive studies in and of themselves are important to give meaning and texture to outcome studies, but they are also a prerequisite to further analysis of causal mechanisms that lead to outcomes of interest. The integration of qualitative and quantitative methods has been called an instrumental strategy: for program evaluation when the program goals are clear but the causal mechanisms are not.”

This perennial problem of combination would be eased and solved if the “instrumental strategy” was used with GT to conceptualize the main concern in a problem area and how it was continually resolved. Perhaps the theoretical code of cause is not emergent thus not clear and another theoretical code would emerge to make clear the evaluation of the goals. 11

Sequencing GT and Quantitative Research

With and subsequent to GT substantive theory comes the future of application, new research directions, general implications and generating formal theory. Least interesting of all is the testing of a GT hypothesis by a quantitative research. The need is small and the yield not great. Substantive area changes in structure and culture are too fast for specific, tested hypotheses by slow quantitative research to hold. And indeed, the quantitative research just produces not a test, BUT more data to compare conceptually, generate new properties of the theory and thereby raise the level of plausibility of the theory. In short a quantitative test is really just more data for modification. See Doing GT, chapter on modification.

Testing a GT hypothesis by quantitative research is too slow and descriptive for our heterogeneous changing world. Quantitative research when used for verification and scientific worthiness is just not worth it. Views of “science” vary and testing is merely one view. GT is too multivariate and complex and theoretically coded in a myriad of ways for one hypothesis to be central enough for an expensive test. The test would end up inadequate and inconclusive for the whole GT theory. Modifications by constant comparison would come naturally.

Quantitative research on a GT could provide supporting confirmation, new directions for GT research, or extending or revising data for the GT, but it still resolves to modification. Also the quantitative research is very likely to lose the abstraction of GT, its scope and parsimony, if not compared correctly for conceptualizing. It thus could reduce it to a descriptive level and decrease its power. It then blocks future GT research, blocks induction and blocks raising a substantive GT to a formal level. Quantitative findings complement GT when conceptualized, not testing it.

So called pilot studies done by QDA but called GT are frequent enough and can provide relevant questionnaire items. But if the research is a genuine GT, then there is no such thing as a pilot study for another research preparation whether quantitative or QDA. GT stands on its own as a theory at any extent, not a preliminary pilot study. It may help formulate a quantitative study, which in the future just provides more data for comparisons. A quantitative study may, as we well know, need a GT study to explain its findings. With GT knowledge grows whatever way. For GT more data, whether quantitative or qualitative, means a substantive theory is starting to become more abstract to a formal theory, when constant comparing is done conceptually.

GT provides all the benefits and functions that all theory does. It can provide a ground breaking theory for a whole program of research to extend, evaluate and refine a substantive body of knowledge using other methods, including quantitative research. It provides grounded concepts as opposed to received, logical, conjectural and borrowed concepts from forcing research frameworks. Its power to open up an area is great with theoretical formulation and categories of relevance and direction.

Using the reversibility of indicators can provide good questionnaire items for GT categories and their properties, which then can be indexed after the quantitative survey. Substructing GT categories and their properties also provide items to operationalize in questionnaires and interview guides for quantitative and qualitative research and then a conceptualization of the data, if the category has emergent fit. For example it is possible to operationalize quantitatively the concept of illusioning in organizations using a GT on organizational illusioning. A remodelled GT by a QDA method mix loses this power.

The reader should keep in mind that not all researchers do GT — obviously — so routine QDA and quantitative research can then use a GT with confidence to integrate them since the GT will fit, work and be relevant. This is far more powerful “science” than a conjectured theory can offer.

The revealing sequences of GT — before, simultaneous, subsequent — and quantitative research are emergently whatever as a substantive field develops. Researchers take the field in all directions with their particular methods: QDA, Quantitative or GT, as studies flood in all directions stimulated by GT giving abstract meaning, relevance, interpretations and future research possibilities. The sequencing can go on and even take years. A good GT conceptually guides and mobilizes both QDA researchers and quantitative researchers in future research years later. Its general implications have lastly, far reaching power. So a blocked GT by QDA description erosion loses this power for quantitative and qualitative research as abstraction and conceptualization is lost. This occurs both on the GT method remodelling by QDA and on the skill level of the researcher being steeped in QDA requirements. QDA description provides little or no guide to a myriad of subsequent research, since its abstraction is low and it is soon stale dated.

Odis Simmons captures the sequencing notion clearly in his and Toni Gregory’s proposal to start a specialty in Grounded Action at the Fielding Institute. He says: “Grounded Action can be used with data that are either qualitative and/or quantitative in nature. The nature and type of data to be used at various phases of a Grounded Action project is itself open to discovery. A project may begin with open-ended interviews, progress to observations, quantitative archival data, surveys or whatever is indicated through the -evolving analysis.” Simmons, as we all should be when appropriate, is totally open to sequencing qualitative and quantitative data whatever way using GT. He is also open to using GT to also develop a program of grounded therapy as well as grounded action. See chapter 1, More Grounded Theory Methodology, Barney G. Glaser editor, Sociology Press.

Quantitative Clobbers of GT

In spite of the big success that GT has achieved in the world of research and especially GT using qualitative data, the GT researcher has to be prepared for quantitative clobbers from time to time. These occur in publication submittals, PhD committees, grant applications and critiques in general. I will cite a few, and I trust the reader will add more from his/her own experience.

Phyllis Stern in her paper “Overcoming the Rage of Rejection” chapter 7, in “Completing a Qualitative Project” 1997, editor Janice Morse, talks of these clobbers. “As a result of a disrespectful review, (many) never write again. The rejection that’s particularly hard to shake is the one that comes from a reviewer who judges qualitative work from the point of view of quantitative research.” For example the author may “receive a letter from the editor stating that they published only ‘scientific’ articles (read “quantitative”) so the qualitative-quantitative mix-up is still going on.”

Remodelling GT to a QDA is particularly subject to this kind of clobber, since QDA is more descriptive and does not provide the powers of conceptualization to offset the evidentiary view. It is easier to reject a QDA description than a conceptualization,
which overriding view implicit in the GT seems to explain and sum things up. The conceptual grab helps. Choosing journals compatible with the type of data is crucial. GT does better, as yet, in qualitative data journals.

Here is another publication rejection clobber based on the evaluator-reviewer, in the editor’s view, only being comfortable with the quantitative approach to QDA. That is they have the evidentiary approach to descriptive findings — with no notion of GT’s procedural rigor in generating conceptual, high applicable substantive theory, in this case on palliative end of life medical care. This is a clear block of GT which suggests it is to be remodelled to evidentiary, descriptive findings. This block comes from thinking GT is another QDA method. Email from Hans Thulesius, MD, Dec 01.

The reviewer says: “This paper presents a theory without any data whatsoever to support/refute or illustrate the arguments being made. This makes it impossible to judge the rigor of the work. In short, it does not adhere to the principle of good qualitative inquiry in terms of being transparent: adequate discussion of how themes, concepts and categories were derived for the adequate discussion on the evidence both for and against the researchers’ arguments and measures taken to test the rigor of the findings.”

This quote makes it so clear that quantitative evidentiary rigor is passed on to QDA and thus assumed of for GT. Thus, GT is remodelled. Han’s theory on balancing cure and comfort care for end-of-life cancer patients has been well received throughout the medical world in Sweden. It has great implications for practice when applied. Indeed, the quantitative oriented editor of this journal wanted Hans to develop a survey questionnaire of items based on his theory.

QDA success with grant proposals still rests in using quantitative evidentiary requirements such as clear populations, interview guides, preconceived professional problems and categories and a framework for analysis etc. Phyllis Stern says “The day may come when emergence will gain its rightful place in the funded grant proposal. However at present, the field is still quantoid-dominated and quantoid-minded reviewers are generally present when proposals are reviewed. As with manuscripts, proposals can be improperly assigned to reviewers who are incompetent in qualitative data methods and give unfair criticism.” pages 141–2 ibid

John R Cutcliffe, PhD writes me on Jun 7, 2002: “How can a researcher who wishes to remain pure to your GT methodology (like me) write grant an application, when the funding authority specifically states that I must identify the research question? Indeed, some awarding authorities are even more prescriptive in stating that they want a-priori hypotheses stated (something I absolutely resist) allowing the central problem to emerge … runs the risk of being rejected.”

The answers to his question are partly in chapter 9 & 10 in my The GT Perspective. One cannot change the formed. It is best to give a review committee what they want, however remodelled GT may appear for the proposal. Then do a pure (non-eroded) GT out of the QDA data. Or just do a GT. Once a good GT is underway, the QDA proposed problem and hypotheses will soon be forgotten in favour of the grab of a GT that explains what is going on.

Lastly the quantitative clobber of GT comes at times from the dissertation committee both during and at the defence if allowed to get that far. It is assumed that the scientific yield is far greater with quantitative research than qualitative research, so the dissertation should favour the latter. Of course and unfortunately GT is easily drawn into this preferential power as a qualitative, basically description method, is itself eroded and remodelled to suit quantitative canons. Evert Gummesson talks of this strong bias in his article referred above. “I am not against quantitative approaches per se. What I am against is their misapplication: their claim that they are better, even the only science; and their far too successful warfare to implant that claim in the academic system and acquire a disproportionate ‘market share’, close to monopoly.” The debate will continue for some time about comparative scientific yield in spite of strong positions to the contrary.

This strong, logic tight bias toward quantitative research is clear and extreme in the following email I received from Denise Johnston on 9/6/00 about her dissertation defence. “I was under no illusion that defending the thesis in an oral examination would be easy. The thesis was purely qualitative being examined in a Faculty that only credits quantitative research … the oral exam was far worse that I could have anticipated. My research was discredited and my method of investigation trivialised. The end result was my being asked to resubmit the thesis for examination within 18 months including stating quantitative methods which, in my opinion, would change the whole tenor of the thesis.” She told me that she could no longer work in this “hostile” environment. Fortunately the consistent accepting environments of qualitative research are growing at a great rate as QDA and GT dissertations accumulate in numbers.

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