Índices ecológicos de la estructura comunitaria zooplanctónica

This project follows a case study approach. However, there is no guarantee that simply calling it thus will convey to the reader what is meant by the term “case study”. On the surface, it seems like there is a consensus about what a “case study” is. Yin, for instance, provides a much-quoted definition of a case study as “an empirical enquiry that investigates a contemporary phenomenon within its real-life context when the boundary between phenomenon and context is not clearly evident” (Yin 2003:13). This minimal definition of a case study is hardly disputable, but a closer look at the literature on case studies reveals several epistemologically grounded disagreements. This section will discuss different definitions of case studies, competing views on case study research design, and the epistemological basis of case studies.

One way to try to come to grips with the concept “case study” is by seeing what it is not, that is, to compare it to other methodological traditions or research strategies within the social sciences. However, this does not clarify matters much, as there is a complete anarchy in the categorization of research strategies in the social sciences, as can be seen by comparing a few relatively recent methodology textbooks. Creswell (1998) contrasts case study with biography, phenomenology, grounded theory, and ethnography; Yin (2003) contrasts it with

85 _{Some of their titles are so long that I prefer to invent for example the name “Madrasi” rather than repeat}

127 experiments, surveys, histories, and archival analysis; and Bryman (2004) contrasts it with experiment, longitudinal design, cross-sectional design, and comparative design. What then shall one make of my study which calls itself a case study, and employs surveys, histories, archival analysis, and a comparative design? The important thing here is to distinguish between the broad research strategy and the concrete methods of data collection. The first encompasses the purpose of the study as well as its epistemological foundation, and the latter refers to how the researcher acquires the necessary empirical material for answering the research questions. A case study may best be defined as a research strategy and not as a

method of data collection, which may vary according to the needs of the research question.

Mitchell (2002) provides the following definition of “case study”: “a detailed examination of an event (or series of related events) which the analyst believes exhibits (or exhibit) the operation of some identified general theoretical principle” (Mitchell 2002:170). He argues that an empirical investigation has to be set in a larger theoretical context in order to qualify for the term “case study”. It makes sense to limit the term “case study” to a study of something which is seen as a “case” of something, of a larger phenomenon, process, type, or problem. The question remains whether the theoretical context and the larger phenomenon are necessarily known at the outset, or are inferred from the empirical findings of the research. I will return to that question later, but first I will turn to the classifications of different types of case studies, and what we can infer from these typologies about case study as research strategy.

Types of case studies

One of the main characteristics of case study research is the purposeful sampling, or rather

selection, strategy, where cases are selected according to predefined criteria. This is in

contrast to statistical analyses of survey data where the units of analysis are a representative sample of the universe or the population.

Several authors have developed typologies of case studies dependent on the purposes served by different types of studies. As with the different conceptualisations of how a case study differs from other research designs, the typologies of different kinds of case studies vary between different authors. Table 1 summarizes case typologies based on the purpose of the

128 study in a few methodological textbooks and articles. The table is not meant to provide a complete list of types of case studies, but to exemplify variations in the focus on and conceptualisations of case study as research strategy.

Table 1. Types of cases found in Bryman (2004), Creswell (1998), Flyvbjerg (2003), and Yin (2003).

Type of case Purpose Listed by

Intrinsic Of interest in itself Creswell

Instrumental Used instrumentally to illustrate a particular issue

Creswell

Extreme/deviant/unique Studied because of its intrinsic interest

Flyvbjerg, Bryman, Yin

Maximum variation (two or more very different cases)

Give “information about the significance of various circumstances for case process and outcome”

Flyvbjerg (:426)

Critical Confirm, extend, or challenge a

preconceived theory

Flyvbjerg, Bryman, Yin

Paradigmatic “Develop a metaphor or

establish a school for the domain that the case concerns.”

Flyvbjerg (:426)

Revelatory Give information on an issue previously inaccessible to analysis

Bryman, Yin

Exemplifying Provide a suitable context for answering certain research questions

Bryman

Representative/typical Gain knowledge about typical or commonplace situations

Yin

Longitudinal Give information about how

things change over time in the same case

Yin

The differences between the types of cases listed above are not always clear, and Flyvbjerg (2003) points out that cases may indeed serve several purposes, depending on the aim of the

129 study. Furthermore, some purposes of a case study, in particular its function as a paradigmatic case, may be impossible to determine in advance, as the singularity and significance of a case will often not become apparent until a late stage of case study research (Flyvbjerg 2003; Bryman 2004). In practice, there will often be a pragmatic aspect to case selection, as can be seen in Bryman‟s (2004) category of “exemplifying case”, a case which provides a suitable context for answering certain research questions. Frequently, cases are selected because they were the ones which were practically feasible to study, e.g. this was the organisation which welcomed you, or a village where the monsoon had not played havoc with the access roads, or it was the unit which fitted most of the criteria/factors you wanted your case to shed light on. Implicit in a process of categorization of types of cases like the ones above, is the assumption that the cases are not only interesting pieces of evidence on their own right, but representations of something else, samples of a bigger universe. This is at the core of case study as a research strategy. Especially the terms “critical case”, “deviant case”, and “exemplifying case” clearly alludes to a larger universe of phenomena about which findings from the study of a particular case can provide knowledge and understanding. Walton (1995) explores this particular issue of case study research. In general, Walton argues that the crucial defining question during a case study is “A case of what?” This may be a question we struggle with throughout the research. A case study is not only a study of an empirical instance, but involves broader claims about reality and about representing a universe of a phenomenon to which we can generalize based on the chosen case. This leads us to the question of how we can generate theory from case studies.

Theoretical generalization from case studies

How can we draw inferences about theory based on empirical observations? As far as I can see, there are two main discussions regarding how we can generate theory from case studies. The first is what kind of research design is most appropriate, i.e. whether a single-case study or multiple-case study is most fruitful and for which reasons. The second question, which is related to the first, concerns whether the theoretical understanding of a case must be clear at the outset of the study, or is developed during the course of the study.

130 The question of single- vs multiple-case studies is related to different epistemological approaches to social science. Some authors advocate a quasi-experimental research design involving multiple cases. Yin (2003) and Eisenhardt (1989; 1991) are examples of this position. The logic behind doing multiple case studies, according to Yin and Eisenhardt, is replication, analogous to the logic underlying multiple experiments. “For example,” Yin says, “upon uncovering a significant finding from a single experiment, the immediate research goal would be to replicate this finding by conducting a second, third, and even more experiments” (2003:47). The same is valid for multiple case studies, he argues. Eisenhardt (1989) similarly outlines a recipe for case study research based on a combination of both hypothesis-testing approaches and experimental-replication logic. Eisenhardt (1989) even argues that as many as

four cases are a minimum requirement to achieve the goal of theoretical development through

case studies.

This has been contested by for instance Dyer and Wilkins (1991) who argue that this is a “hybrid” between qualitative and quantitative ways of analysis, and risks losing the particular strength that case studies have of providing rich and detailed contextual material and narratives which describe “general phenomena so well that others have little difficulty seeing the same phenomena in their own experience and research” (Dyer and Wilkins 1991:617). The reasoning underlying the quasi-experimental design for multiple case studies resembles hypothetical-deductive methodology and nomothetic science. It is an attempt at constructing a closed system in which to test theories which aim at general, universal explanations. The replication logic described above allows for falsification of theoretical claims and aims at strengthening, if not verifying, existing theories. Yin maintains that the inferences drawn from this design involves “analytic generalization” as an alternative to statistical generalization. Analytical generalization is done when “a previously developed theory is used as a template with which to compare the empirical results of a case study. If two or more cases are shown to support the same theory, replication may be claimed” (Yin 2003:32-33). Campbell, in the foreword to Yin‟s book, holds that this approach is similar to a “randomized-assignment-to- treatments model” in an experiment where rival hypotheses are specified and specifically controlled for. He attributes Yin‟s “insistence that the case study method be done in conformity with science‟s goals and methods” to Yin‟s background in experimental psychology (2003:x). This is plausible. Researchers with other disciplinary backgrounds, like

131 anthropology or human geography, may be less inclined to base their research design on a model which strives to achieve the ideal of ceteris paribus conditions.

The rigorous quasi-experimental design advocated by Yin and Eisenhardt is not the only kind of design which provides alternatives to statistical generalization. Mitchell (2002) discusses the epistemological basis of case studies. Like Yin, he contrasts this to statistical generalization (or “enumerical induction” as Mitchell calls it). Statistical generalization means to draw conclusions about frequencies and correlations between variables from random, representative samples to parent populations. However, as is highlighted in any introductory text on statistics, the decision on whether correlation between variables is spurious or not rests on a different kind of logic. “Sometimes it becomes more a matter of common sense than of statistical application to determine if an observed correlation can be practically interpreted or if it is spurious,” say Bhattacharya and Johnson in Statistical Concepts and Methods (1977). Even in statistical analyses, inferences about the relationship between variables cannot be based on enumerical or probability logic at all, but has to be based on theoretical thinking and logical deduction, argues Mitchell:

“The inference about the logical relationship between the two characteristics is based not upon the representativeness of the sample and therefore upon its typicality, but rather upon the plausibility or upon the logicality of the nexus between the two.” characteristics. (Mitchell 2002:175)

Whereas in statistical analyses both enumerative and analytical/logical inferences must be used, in case studies, inferences are only analytical. Contextual knowledge can guide our “common sense” in this matter. Based on this, Mitchell further argues that there is nothing to gain by looking for a typical case, or defend your case in terms of typicality. Concern with typicality is to confuse enumerative and analytic modes of induction. Cases should rather be selected based on their explanatory power (Mitchell 2002).

Comparative case studies need not be based on the replication logic advocated by Yin and Eisenhardt. A comparative design will also allow contrasting findings to act as “a springboard for theoretical reflection” (Bryman 2004). Bryman (2004) suggests that a useful design may be a comparison between very different cases, for instance a successful and an unsuccessful case. Similar findings from contrasting cases can be just as important and interesting as differences. Given the impossibility of controlling the “laboratory” environment in a study of

132 the real world, it may not be the most fruitful strategy to try to achieve the scientific ideal of experiments in a closed system. For example, no two villages in India are identical, and it is impossible to control for all the confounding factors in an analysis of the struggles over Narmada water in two Indian villages. Ceteris paribus conditions are thus not possible. A comparative case study may explicitly acknowledge this difference, and the aim may be to explore how the same phenomenon/a (or the Narmada project, in my case) is playing out in different circumstances or localities. For this, a “maximum variation” set of cases may be chosen.

The second question regarding theory generation relates to how and when we know the answer to the question “What is this a case of?” In quasi-experimental research designed to test existing theories, we need to know in advance what the case represents. Yin argues that the ambiguity of cases is a vulnerability of case studies, and that we have to carefully “investigate the potential case to minimize the chances of misrepresentation” (2003:42). The frequent change of perspectives, research questions, and theoretical ideas during the course of case study research, is a weakness according to him, and he argues explicitly for rigour in designing the research:

“[Y]ou need to avoid such unsuspected slippage; if the relevant research questions really do change, you should simply start over again, with a new research design.” (Yin 2003:45)

Others see the flexibility of case studies, that they by design are more open to surprise and available for multiple purposes, as a strong point:

“[C]ase studies, especially those which start with the case in its own right rather than as an instance, are more likely to uncover unanticipated findings as the details are explored.” (Platt 1988:177).

Yin‟s demand for rigour is not only sometimes practically unfeasible for lack of time and funds, but may also, for some research problems, be theoretically problematic. Several researchers have described how they, during the course of their investigation, discovered that the case they chose to study was not best understood as a case of what they thought it would be at the outset (f.ex Flyvbjerg (2003) and Walton (1995)). Walton argues that a case is not selected based on a pre-existing universe that it represents and of which it later provides explanations and theories. On the contrary, our perceived universe is referred from cases,

133 either from your own case, or from other case studies, in a dialectical process involving both inductive and deductive reasoning. In order to frame our case, we need to make “theoretical choices about the causal forces that distinguish and critically affect the case” (Walton 1995:124).

Walton (1995) uses his own experience of research on the Owens‟ Valley Rebellion in the USA in the 1920s to argue for the theoretical case. This project turned out to be a study of something quite different than what he set out to study:

“The Owens Valley study began with the ambition of probing in more depth the causes of rebellion analyzed in previous cross-national case studies. In the early going, my assumption that the Owens Valley presented a case of something familiar in U.S. history or in the sociological literature on social uprisings was frustrated. The episode belonged to no known universe from which typological distinctions could be drawn and causal explanations hypothesized.” (Walton 1995:135)

Instead of a case study which would provide a theory of causes of rebellion, he changed it to an analysis of how collective action was shaped by the particular configuration of the state in given periods of time, a longitudinal case study of “the changing role of agency in history” (1995:133). He concludes from this that case study research is a thoroughly theoretical exercise:

“The question of cases, their designation and reformulation, therefore is a theoretical matter. The processes of coming to grips with a particular empirical instance, of reflecting on what it is a case of, and contrasting it with other case models, are all practical steps toward constructing theoretical interpretations. And it is for this reason, paradoxically, that case studies are likely to produce the best theory.” (Walton 1995:127).

Although it might be too strong to claim that case studies are likely to produce the “best theory”86

, I follow Walton in seeing the reformulation of research questions, methods of data collection, and case boundaries, as intrinsic parts of the theorisation process itself, and not as weaknesses. If we always knew at the outset what a case study was about, and how a case was to be understood and conceptualized, theory development would indeed be a narrow and limited exercise.

86 _{What kind of method that will produce the best theory will depend on a range of issues, like the research}

134

SSP, Krushigam and Motugam – what kinds of cases are they?

My case study can be seen as an intrinsic case study of the Sardar Sarovar Project, which is of interest in and of itself. This is a case of a larger universe of large-scale development projects, initiated in a top-down manner from the state, and criticised for lack of sensitivity to local knowledge, ecology, and culture. As described in Chapter 5, large dams have aquired the status as critical symbols of a flawed development model, and the Sardar Sarovar Project is one of the most important of these symbols. Within this case, I am doing an instrumental comparative case study of two villages. They are selected because they provide good contexts for certain research questions to be answered, and as such they can be seen as “exemplifying cases”. In Krushigam, I explore the implementation of the SSP in a poor and water deficient setting where caste heterogeneity prevents collective action and organisation. In Motugam, I explore how leaders with political power are exerting pressure on the government to alter the decided policy for water allocation and the challenges of collective organisation of water resources. In addition, the two villages are selected as contrasting cases of maximum variation in resources, both human/organisational and economical/natural.

I do not claim that this design enables me to tell the full and complete story of what influences the implementation and potential impacts of the Sardar Sarovar Project. But they will allow me to thoroughly explore important aspects of this, and draw conclusions about possible implications for other villages in the command area. This study will also allow, at a more abstract level, reflections about the development potential of mega-projects like the Narmada/Sardar Sarovar Project, and the validity of the arguments of strong critics or proponents of such projects.

As is clear from the account of the research process in this study in the first part of this chapter, a level of pragmatism was necessary when defining and designing the study. Like