Discovery of Grounded Theory

Strategies for Qualitative Research

Barney Glaser, Anselm Strauss, Barney G Glaser, Anselm L Strauss

• Publisher: Routledge
• Year: 2017
• Topic: Social Sciences
• eBook ISBN:
  9781351522151
• Subtopic: Social Science Research & Methodology
• Index: Social Sciences

Most writing on sociological method has been concerned with how accurate facts can be obtained and how theory can thereby be more rigorously tested. In The Discovery of Grounded Theory, Barney Glaser and Anselm Strauss address the equally Important enterprise of how the discovery of theory from data—systematically obtained and analyzed in social research—can be furthered. The discovery of theory from data—grounded theory—is a major task confronting sociology, for such a theory fits empirical situations, and is understandable to sociologists and laymen alike. Most important, it provides relevant predictions, explanations, interpretations, and applications. In Part I of the book, "Generation Theory by Comparative Analysis," the authors present a strategy whereby sociologists can facilitate the discovery of grounded theory, both substantive and formal. This strategy involves the systematic choice and study of several comparison groups. In Part II, The Flexible Use of Data," the generation of theory from qualitative, especially documentary, and quantitative data Is considered. In Part III, "Implications of Grounded Theory," Glaser and Strauss examine the credibility of grounded theory. The Discovery of Grounded Theory is directed toward improving social scientists' capacity for generating theory that will be relevant to their research. While aimed primarily at sociologists, it will be useful to anyone Interested In studying social phenomena—political, educational, economic, industrial— especially If their studies are based on qualitative data.

PART I:
Generating Theory by Comparative Analysis

II
Generating Theory

The term comparative analysis—often used in sociology and anthropology—has grown to encompass several different meanings and thereby to carry several different burdens. Many sociologists and anthropologists, recognizing the great power of comparative analysis, have employed it for achieving their various purposes. To avoid confusion, we must, therefore, be clear at the outset as to our own use for comparative analysis—the generation of theory. We shall first contrast our use of this method with certain other uses.¹ Then we shall define and describe what kind of theory can be generated through comparative analysis.

Comparative analysis is a general method, just as are the experimental and statistical methods. (All use the logic of comparison.) Furthermore, comparative analysis can, like those other methods, be used for social units of any size. Some sociologists and anthropologists customarily use the term comparative analysis to refer only to comparisons between large-scale social units, particularly organizations, nation, institutions, and large regions of the world. But such a reference restricts a general method to use with one specific class of social units to which it has frequently been applied. Our discussion of comparative analysis as a strategic method for generating theory assigns the method its fullest generality for use on social units of any size, large or small, ranging from men or their roles to nations or world regions. Our own recent experience has demonstrated the usefulness of this method for small organizational units, such as wards in hospitals or classes in a school.²

Before distinguishing our purpose in using comparative analysis from other purposes, we should mention one unfortunate use of comparisons: to debunk, disprove, or discount the work of colleagues. From his own readings, a sociologist can almost always find, if he wants to, some piece of data that disproves the fact on which his colleague has based a theoretical notion. Many sociologists do! If each debunker thought about the potential value of comparative analysis, instead of satisfying his urge to “put down” a colleague, he would realize that he has merely posed another comparative datum for generating another theoretical property or category. That is all he has done. Nothing is disproved or debunked, despite what those who are overly concerned with evidence constantly believe. Kinder colleagues, who present a sociologist with one or more negative case but are afraid of impairing his motivation, usually will suggest that some qualification in his theoretical assertion may be advisable. Their comparative analysis aids him in rounding out his own comparative analysis and further generating his theory.

We also intend to hold a dialogue with those who “put down” the comparative strategy as “not especially original.” True, the general notion of comparative analysis was developed by our sociological forefathers—Weber, Durkheim, Mannheim—and by social anthropologists. We can only trust that our readers will absorb enough details of comparative analysis as rendered in this book to be able to spot the advances in the strategy that should make a world of difference in its use.

Purposes of Comparative Analyses

The distinction made earlier between relative emphasis on generating and verifying can be illuminated further by considering the typical uses of evidence obtained through comparative studies.

Accurate Evidence

On the factual level, evidence collected from other comparative groups—whether nations, organizations, counties, or hospital wards—is used to check out whether the initial evidence was correct. Is the fact a fact? Thus, facts are replicated with comparative evidence, either internally (within a study), externally (outside a study), or both. Sociologists generally agree that replications are the best means for validating facts.

Although this use of comparative analysis is not, of itself, our goal, it is definitely subsumed under our goal. Naturally we wish to be as sure of our evidence as possible, and will therefore check on it as often as we can. However, even if some of our evidence is not entirely accurate this will not be too troublesome; for in generating theory it is not the fact upon which we stand, but the conceptual category (or a conceptual property of the category) that was generated from it. A concept may be generated from one fact, which then becomes merely one of a universe of many possible diverse indicators for, and data on, the concept.³ These indicators are then sought for the comparative analysis. (See Chapters III and IV.)

In discovering theory, one generates conceptual categories or their properties from evidence; then the evidence from which the category emerged is used to illustrate the concept. The evidence may not necessarily be accurate beyond a doubt (nor is it even in studies concerned only with accuracy), but the concept is undoubtedly a relevant theoretical abstraction about what is going on in the area studied. Furthermore, the concept itself will not change, while even the most accurate facts change. Concepts only have their meanings respecified at times because other theoretical and research purposes have evolved.

For example, one theoretical category related to the care of dying patients is their social loss—loss to family and occupation.⁴ This category clearly affects how nurses care for dying patients. The category of “social loss” can be generated from either the observation that VIP’s receive special care on intensive care units or that lower-class Negroes often are neglected on city hospital emergency wards. Even if the evidence changes (or is different in other hospitals for various other reasons), we can be sure that social loss is a category related to nursing care, and we can make predictions on its basis. We can predict that patients who have high social loss will receive better care than those who have low social loss. If that prediction proves incorrect, then we are likely to find out next what structural conditions have tended to negate this relationship; for example, how the medical staff has overcome this socially induced tendency in one type of hospital. In short, the discovered theoretical category lives on until proven theoretically defunct for any class of data, while the life of the accurate evidence that indicated the category may be short.

Empirical Generalizations

Another standard use of comparative studies is to establish the generality of a fact. Does the incest taboo exist in all societies? Are almost all nurses women? Is basic research the most revered goal of scientists in all research organizations? Accuracy is not at stake so much as establishing the structural boundaries of a fact: where is the fact an accurate description? For some sociologists and anthropologists this purpose becomes a quest for “universals”—facts and their explanations by other facts—that apply to all men irrespective of their society or culture.

Our goal of generating theory also subsumes this establishing of empirical generalizations, for the generalizations not only help delimit a grounded theory’s boundaries of applicability; more important, they help us broaden the theory so that it is more generally applicable and has greater explanatory and predictive power. By comparing where the facts are similar or different, we can generate properties of categories that increase the categories’ generality and explanatory power.

For example, dying of cancer in America can be characterized as occurring in a “closed awareness context”—while the hospital staff does, the patient does not know he is dying. Most doctors do not tell their patients that their illness is terminal, and patients find that cues that might alert them that they are dying are vague and hard to read until the last stages of their dying.⁵ In a Japanese hospital we once visited, cancer patients typically know they are dying (an “open awareness context”). Why? Because the hospital ward is openly labeled “Cancer.” The patient entering the ward reads a clear cue that makes him aware that he is dying. While in America the cues tend to be vague and fleeting, we discovered through the Japanese example that they can be clear even at the beginning stage of a long term of dying. Until then, we had not realized that cues can vary in clarity at the beginning of such a disease as cancer. We had thought that clear cues emerged only during the final stages; for example, when the priest arrives, or the patient’s pain is beyond endurance, or massive bodily degeneration occurs.

This comparative data from Japan stimulated us to find locations in America where clear cues are provided at the start of dying. We found that in a veterans’ hospital and in a prison medical ward, patients from the outset were given clear cues that they had cancer. Thus we discovered that under the structural condition of being a captive patient in a government hospital, one tends to die in an open awareness context. But most patients in America do not die under such circumstances.

Specifying a Concept

Another (usually detailed and painstaking) use of comparative data is to specify a unit of analysis for a one-case study. This is done by specifying the dimensions of the concept designating the unit. To make certain the reader understands what a given monograph will be about, in comparison with seemingly similar units, the author compares his unit for analysis with these other units. His comparison brings out the distinctive elements or nature of the case he has studied. For instance, Cressey painstakingly compared taxi-dance halls with all other forms of dance halls before proceeding with his analysis.⁶ Lipset, Trow and Coleman compared the distinctive political nature of the ITU with the characteristic political structure of other unions to establish their “deviant” case study.⁷ Wirth compared the Chicago ghetto with the European to establish distinctive changes in the new-world ghetto.⁸ Coleman, with the aid of IBM equipment, carefully distinguished between types of high schools on three dimensions, themselves checked out empirically to assure us that they are different in more than script.⁹

This standard, required use of comparative analysis is accomplished early in the presentation of a study for the purpose of getting the ensuing story straight. This use is, of course, subsumed under the purpose of generating theory. However, when the analyst’s purpose is only the specifying of a unit of analysis, he stifles his chances for generating to a greater degree than with any other use of comparative analysis. The distinctive empirical elements distinguishing the units of comparison are kept on the level of data, to insure clear understanding of differential definitions. As a consequence, the units’ general properties in common, which might occur to the analyst as he compares, are carefully unattended. No ambiguity of similarity, such as a general underlying property pervading all of them, is allowed between the competing units. Comparative analysis, then, is carefully put out of the picture, never to “disrupt” the monologue again.

Verifying Theory

When the analyst turns to theoretical concerns, evidence is invariably used as a test of his hypotheses—and thereby of the relevance of his categories; comparative data give the best test. Both implicitly and explicitly, the analyst continually checks out his theory as the data pour in. Explicit verification beyond testing his hypotheses may lead to establishing major uniformities and universals, to strategic variations of theory under different conditions,¹⁰ and to grounded modifications of theory.¹¹ A touch of generation may be included, but the researcher’s focus is on verifying; he generates theory only in the service of modifying his original theory as a result of the tests. And most of this work is done with existing theories; for example, Blauner’s work with Marxian theory or Lipset’s work with Michel’s theory.¹²

Some analysts focus on verifying the new theory that emerges in their data.¹³ Thus, in their work, theory is generated, but its emergence is taken for granted; what is intentionally worked for is the verification of this emergent theory. The analysts are preoccupied with “checking out” the “emergent set of propositions.” Their favorite technique is looking for negative cases or setting out deliberately to accumulate positive ones to gain further evidence for their hypotheses. And while, as in Dalton’s research, great trouble may be taken in actively seeking comparative groups, other analysts may use comparative groups incidentally or even implicitly.

These researchers in specific studies do not seem to have focused directly on how their theory emerged; as a result, they have not explored how they could have generated more of it more systematically, and with more conceptual generality and scope. A focus on testing can thus easily block the generation of a more rounded and more dense theory (see Chapter VI). Ordinarily, we are presented with well-tested theory fragments, which can only partially account for what is happening in the researched situation. Also, we are presented with plenty of evidence, coupled with at least implicit assurances that there were mountains more for verification—because evidence is still most important to the analyst as the means for testing how he knew his theory was “right.”¹⁴ This focus on evidence paradoxically allows cantankerous colleagues, with their own different comparative evidence or personal experience, to “pooh-pooh” his theory, wholly or in part.

Generating Theory

While verifying is the researcher’s principal and vital task for existing theories, we suggest that his main goal in developing new theories is their purposeful systematic generation from the data of social research. Of course, verifying as much as possible with as accurate evidence as possible is icquisite while one discovers and generates his theory—but not to the point where verification becomes so paramount as to curb generation. Thus, generation of theory through comparative analysis both subsumes and assumes verifications and accurate descriptions, but only to the extent that the latter are in the service of generation. Otherwise they are sure to stifle it. To be sure, the urge to generate is normal; and sociologists, students and professors alike, if they are not “hooked” on verifying, tend to give themselves enthusiastically to generating. But when generating is not clearly recognized as the main goal of a given research, it can be quickly killed by the twin critiques of accurate evidence and verified hypotheses. This happens especially when the critiques are made by an influential colleague or professor. The analyst’s confidence is destroyed because everyone involved fails to realize that accurate description and verification are not so crucial when one’s purpose is to generate theory. This is especially true because evidence and testing never destroy a theory (of any generality), they only modify it. A theory’s only replacement is a better theory.¹⁵

When the vital job of testing a newly generated theory begins, the evidence from which it was generated is quite likely to be forgotten or ignored. Now, the focus is on the new evidence that will be used for verifying only a part of the theory. Furthermore, sociologists will find it worthwhile to risk a period in their careers in order to test grounded theories, since these theories are certain to be highly applicable to areas under study. This situation is in contrast to the risk of testing a logico-deductive theory, which is dubiously related to the area of behavior it purports to explain, since it was merely thought up on the basis of a priori assumption and a touch of common sense, peppered with a few old theoretical speculations made by the erudite.¹⁶ The verifier may find that the speculative theory has nothing to do with his evidence, unless he forces a connection.¹⁷

Generating theory carries the same benefit as testing theory, plus an additional one. Verifying a logico-deductive theory generally leaves us with at best a reformulated hypothesis or two and ...

Table of contents

• Cover Page
• The Discovery of Grounded Theory
• Copyright Page
• Contents
• Preface
• Acknowledgments
• I The Discovery of Grounded Theory
• PART I: Generating Theory by Comparative Analysis
• PART II: The Flexible Use of Data
• PART III: Implications of Grounded Theory
• Epilogue
• Index