Medical anthropology

Contents

Approaches: 1

Ethnomedical approach: 1

Biomedical approach: 2

Ecological Approaches: 2

Critica Approaches: 2

Applied Approaches. 3

Medical Anthropology studies human health problems and healing systems in their broad social and cultural contexts. Medical anthropologists engage in both basic research into health and healing systems and applied research aimed at the improvement of therapeutic care in clinical settings or community public health programs in prevention and disease control. Drawing from biological and social sciences, as well as clinical sciences, medical anthropologists have contributed significantly to the understanding and improvement of human health and health services worldwide. As a result, the growth of the subdiscipline in recent years as reflected in publications and meetings, training programs, and influence outside of anthropology has been remarkable.

Medical anthropology is not characterized by a single theoretical paradigm. For example, ethnographic description and analysis of religion and healing systems are as old as anthropology itself, while new approaches like critical medical anthropology are the product of more recent intellectual trends. This has sometimes led to intense debates within the field such as those between clinically applied medical anthropologists (interested in making cultural knowledge useful to the aims of medical practitioners) and critical medical anthropologists (interested in the phenomenology and political economy of biomedicine). But, even though the scope of intellectual inquiry is very diverse, it is possible to identify five basic approaches: biomedical, ethnomedical, ecological, critical, and applied. These approaches share three fundamental premises:

1.       illness and healing are fundamental to the human experience and are best understood holistically in the contexts of human biology and cultural diversity

2.       disease represents an aspect of the environment that is both influenced by human behavior and requires biocultural adaptations

3.       the cultural aspects of health systems have important pragmatic consequences for the acceptability, effectiveness, and improvement of health care, particularly in multicultural societies

Approaches:

Ethnomedical approach:

The initial development of medical anthropology derived from anthropological interest in different illness beliefs and healing practices (Rubel & Hass 1996).

Cultures have developed more or less organized approaches to understand and treat afflictions, and identify the agents, forces, or conditions believed responsible for them. Ethnomedicine is that branch of medical anthropology concerned with the cross-cultural study of these systems. While medical systems or elements thereof were foci of research early in the 20th century in the work of W. H. Rivers, the study of popular systems of health and illness did not coalesce into a field of study

in anthropology until the 1980s. Foundational formulations of the field of medical anthropology appeared in the 1950s and 1960s, in the works of such writers as William Caudill and Steven Polgar.

The earliest ethnomedical research was confined to the study of non-Western societies and exotic cultures and was generally subsumed under the comparative study of religion. Ideas about sickness and therapeutic rituals were analyzed as a window on underlying cosmological beliefs and cultural values. As the intimate relationship between the concepts of illness and the social organization were recognized, ethnomedicine became a common focus of ethnographic research. Fabrega (1975: 969) defined this approach as "the study of how members of different cultures think about disease and organize themselves toward medical treatment and the social organization of treatment itself." Typical ethnomedical studies focus on the classification and cultural meaning of illness (both somatic and mental), the health-seeking behaviors of people suffering from illness, and the theories, training, and practices of healers. Nichter (1992: x) described twelve areas of current ethnomedical work, including the "study of the afflicted body as a space where competing ideologies are contested and emergent ideologies are developed through medico-religious practices and institutions which guide the production of knowledge."   

Biomedical approach:

Although not always recognized as such, much of the research in BIOLOGICAL ANTHROPOLOGY using the standard epistemology of science and focusing on human biology and the health consequences of different stresses is part of medical anthropology (F. Johnston & Low 1984). For example, it has long been recognized that DISEASE has acted as an important agent of natural selection in genetic and cultural EVOLUTION. Biomedical anthropologists have used immunological studies to trace EPIDEMICS. Biological anthropologists have examined human physiological adaptations to a wide variety of stresses, including high elevation, cold temperatures, nutritional deprivation, and infectious disease. Laboratory-based scientific methods (such as the biochemical analyses of ethnopharmacological compounds) are used to analyze the biochemical and physiological functioning of ethnomedical practices. This type of analysis played a role in the discovery of a Hepatitis vaccine (Blumberg 1982).

Ecological Approaches:

The ecological approach in medical anthropology focuses on how human cultural and behavioral patterns shape the complex interactions of the pathogen, the environment, and the human host, and produce both infectious and noninfectious disease states (Inhorn & Brown 1997). In recent years, ecological studies of health and illness have looked beyond local socioeconomic factors that influence disease rates to emphasize the larger political economic forces that constrain the behavior choices of populations. Both Ecological Anthropology and political ecology examine how cultural, physical, and political-economic environments shape the distribution of disease morbidity and mortality. Disease patterns described with epidemiological methods (in regard to time, place, and person) often reflect cultural practices associated with diet, activity patterns, sexuality, and so forth. In addition, culturally defined group practices such as the introduction of IRRIGATION agriculture can transform the disease ecological balance in favor of a pathogen like malaria or shistosomiasis, and in turn damage health. Ecological analyses in medical anthropology also reveal many cases where cultural changes improve health for some groups.

Critica Approaches:

Critical medical anthropology (CMA) is a label applied to two distinct intellectual movements that influenced the field during the 1980s and 1990s. One emphasized the marxist approaches to understanding how macrosociological political-economic forces influence health and structure health-care systems. The second movement is more epistemological, it questions the intellectual underpinnings of contemporary biomedical theory and practice. This approach has been influenced by postmodern thinkers like Foucault who emphasize the social-constructionist nature of reality and the social power inherent in hegemonic institutions like "Biomedicine." What these movements have in common is the demand for a fundamental rethinking of the premises and purposes of medical anthropology.      

The political-economic orientation of CMA views health issues in the light of the larger political and economic forces that pattern human relationships, shape social behavior, and condition collective experience (Merrill Singer 1989). Macrolevel processes such as world CAPITALISM are seen as the dominant forces that shape clinical practice and influence the distribution of disease. Medicine is perceived not only as a set of procedures and treatments, but also as a particular set of social relationships and an ideology that legitimates them. Recognition of the centrality of the political-economic dimensions of both sickness and healing, as well as the unequal social relationships between healers and patients is the hallmark of this approach.     

The second branch of CMA challenges the epistemology and universality of assumptions underlying the theory and practice of Western medicine, which were conventionally exempt from cultural analysis in medical anthropology. This approach has been responsible for the label "biomedicine." Medical anthropologists like Lock and Scheper-Hughes (1996) advocate the deconstruction of how mind and body are conceptualized as a way to gain insight into how health care is planned and delivered in Western societies. The separation of mind and body in biomedical science is so pervasive that there is a need for more precise vocabulary for the interactions of mind, body, and society.            

Applied Approaches  

Interest in the applied aspects of medical anthropology has been present since the initiation of the discipline. There are two branches of applied work, clinical and public health. Clinically applied medical anthropology is best known for its use of explanatory models to explore conceptual differences between physicians' and patients' perceptions of disease and illness. Clinically applied anthropologists work in biomedical settings with health practitioners and the delivery of health care services; they are also involved in the training of future professionals. Without a single theoretical proposition, it can be interpreted as anthropological theory and methods devoted to the topics of health, illness, and health care. Clinical medical anthropological research has a very wide range, including microlevel studies of health-care choices, illness beliefs, and life-course events like CHILDBIRTH or menopause; the examination of cultural influences on health-seeking behavior, disease distributions, the experience of illness (e.g., pain), and interactions of healers and patient (i.e., compliance); and macrolevel research on health-care systems and their political and economic contexts (Chrisman & Johnson 1996). Some clinically applied medical anthropologists are employed within hospitals and clinics as cultural mediators and interpreters.      

Applied medical anthropology research in public health has gained importance in recent decades (Coreil & Mull 1990). More medical anthropologists are working in international health projects, particularly because of the programmatic emphasis on primary health care and interventions in nutrition and oral rehydration therapy that require community participation. Anthropologists have worked on all aspects of such projects, including problem identification and analysis, intervention, and evaluation of specific health problems.

Interpretative Anthropology

Contents

Origins: 1

Culture as Text. 1

Hermeneutics: 2

Interpretive Anthropology provides accounts of other cultural worlds from the inside and at the same time reflects on the epistemological groundings of such accounts. It is associated with the Chicago school of anthropology in the 1960s and 1970s, especially with the inflection given to symbolic anthropology by Clifford Geertz. Interpretive anthropology was positioned against purely behaviorist, statistical, and formalist-linguistic approaches to human society because it insisted on the importance of the active negotiation of meaning, the decay and growth of symbols, and the richness of linguistic metaphoricity. The effort to unpack culture as systems of meaning led to parallel interests in the processes of interpretation, and eventually, on the one hand, to a stress on differentiated competing discourses within a culture, hegemonic and counter-hegemonic processes, and critical anthropology, and on the other hand to a stress on ethnography as itself a process of interpretation (M. Fischer 1977).

Origins:

Victor Turner brilliantly elaborated Van Gennep’s notion of liminality. Building on Van Gennep’s concept that the transitional phase sometimes acquires a certain autonomy from the rest of the ritual, Turner developed a view of a “state of transition,” in which the inhabitants are “betwixt and between” normal social status. Based on his intensive study of life crisis rituals among the Ndembu of Zambia, Turner regarded this liminal or transitional phase as ambiguous, inversive, ludic, and a source of the intensive, effervescent camaraderie that he described as “communitas.”

Turner’s works represent a trend in anthropological studies of ritual that shifted emphasis from seeking for function to meaning in 1960s and 1970s. Symbolic and interpretative anthropology developed out from this trend and have had tremendous influence on anthropological studies of death ritual. They have sought to understand symbols and rituals primarily through the indigenous interpretation of the society in question. Victor Turner defined ritual as an aggregation of symbols, with the symbols being the smallest unit of ritual that still retains the specific properties of ritual behavior. From this definition, we can see a crucial feature of his methodology, which works from discrete ritual symbols (“storage units,” “building blocks,” and “molecules of ritual”) to their incorporation in ritual systems, and then to the incorporation of such systems in the whole social complex being studied. He stressed the common diachronic profile or processual form in rituals, that is, the sequence of ritual acts in social contexts. He treated ritual symbols not as static, absolute objectifications but as social and cultural systems, shedding and gathering meaning over time and altering in form. This emphasis on social process distinguishes him sharply from his own background in British social anthropology, which focused primarily on structure and static functionalism.

Culture as Text

The metaphor of cultures as texts, popularized by C. Geertz (1973), initially only meant that anthropologists read meanings in a culture as do native actors, and (in Ricoeur's 1981 influential version) that social actions leave traces that can be read like texts. Geertz's ethnography highlighted occasions when actors were at a loss to know how to construct a ritual, or when meanings needed to be renegotiated and established for particular interactions to be accomplished. Interpretive anthropology provided a devastating critique of cognitive anthropology's hopes for objective grids of meaning by showing that these grids were shot through with the analysts' own cultural categories and assumptions, thus vitiating the project. Structuralism was similarly, if less devastatingly, criticized as being too distant from the intentionality and experience of social actors. Interpretive anthropology in turn was itself criticized for seeing meaning wherever and however the analyst wished rather than having any objective method or criteria of evaluation.        

One response to such criticism was to conceive of cross-cultural understanding, like any social understanding, as but an approximation, variably achieved through dialogue: a mutual correction of understanding by each party in conversation to a level of agreement adequate for any particular interaction. Geertz's own version of this argument for cross-cultural work was that ethnography is a translation between "experience-far" and "experience-near" languages. This relativist understanding of the distinction between emic and etic categories avoids the need for, and denies the cogency of expecting, universally objective grids of meaning against which various cultural definitions might be measured. It focuses attention upon the ways in which meaning is established within communicative processes   both those processes that establish relatively stable meanings over time (such as Max WEBER's interest in legitimate forms of domination) and those that are fundamentally renegotiated in each interaction. Others took the idea of dialogue in directions that empirically documented   from the sociolinguistic tape-recording to hermeneutical cultural accounting   how actors negotiate their understandings as well as how they interacted with cultural outsiders. At issue was not merely Max Weber's call for a verstehendes Soziologie, a sociology that gives a central role to actors' own understandings, but also the criterion of methodological individualism, the requirement that any sociological theory be able in principle to explain actions in terms of the intentions and purposes of individual actors. This criterion of acceptability was intended as a guard against essentializing Romantic group-mind characterizations of cultural beliefs and practices, so badly misused by the Nazis as well as ordinary racists, and does not necessarily contradict DURKHEIM'S notions of the social or cultural as an emergent level of organization that cannot be simply reduced to individual intentions.

Hermeneutics:

Hermeneutics is the science of interpretation and maintains an interest in the content as well as the form of what is being interpreted. The term itelf originated with the practice of interpreting sacred texts. It is based on the principal that we can only understand meaning of a statement in relation to a whole discourse or world view of which it forms a part.

In conclusion it can be said that the mix of interests and kinds of ethnography that interpretive anthropology generated   interest in the "native point of view," in the competing discourses within social fields, the ritualized ways in which hegemonic perspectives might be reinforced, in the negotiation of meaning and the changes in the constitution of culture that negotiation can sometimes effect, in the interpretive and dialogic processes both of social action and of ethnographic fieldwork and writing   constitute a transition between the discussions surrounding the ethnographies produced by functionalism and those surrounding the issues of postmodernism. Clifford Geertz (1995) himself is a rebel child of the various functionalisms of anthropology and Parsonian sociology, and father teacher defender to the ethnographers who are challenged by the postmodern. The philosophical issues raised, refined, and elaborated are perennial.

ANTHROPOLOGY OF RELIGION

Approaches. 1

Major theories in brief: 3

Functionalists: 3

Marxists: 3

Gender studies and feminists: 4

Rational choice theorists: 4

 

It is widely known that all societies known to anthropologists possess some sort of belief systems which can roughly be termed as religion or religious beliefs. Since, these beliefs vary cross culturally anthropological definition of religion is quite broad. Religion is its widest sense religion is any set of attitudes (acts and actions), beliefs and practices related to supernatural power and forces. These power calls for an array of forces including gods, spirits, ghosts or demons.

Approaches

The anthropological approach to religion has two predominant traditions: the intellectualist and the symbolist, each of which may be further subdivided. Following Tylor (1871), who argued that early religion arose from people's beliefs in spirits of godlike beings (see animism), the first is called "intellectualist" because religion is seen as a system of explanation. People, it was claimed, invoked beliefs in spirits or gods in order to explain natural events and phenomena in the world about them. The symbolist approach, derived from Durkheim (1915), sees religion as                making symbolic statements about the social order, not as explaining nature. Beliefs, rituals, or myths may reinforce ideas about authority but are not peoples' attempts to explain why authority is there in the first place. Hence, for the symbolists, religion does not attempt to solve intellectual or empirical problems. Tylor's intellectualist definition grew out of his theory of cultural evolution and the development of human reason. He saw magic, science, and religion as manifestations of the human intellect and, though different from one another, as likely to coexist in all human cultures. Magic was a form of mistaken science. Whereas scientific assumption could be shown to be true or false through empirical tests, magic tried to solve problems through associations of ideas that simply seemed to fit with each other: he gave as an example the Greek view that the yellow of a gold ring could draw out the yellow of jaundice and so cure it. Magic and science were, however, similar to each other in seeking causal connections in an ordered nature, and differed from religion with its belief in spiritual beings, rather than an impersonal power, as having an effect on the world. FRAZER (1890) broadly followed Tylor's distinction between magic, religion, and science but saw them, in this order, as making up an evolutionary continuum. Much later, Lévi-Strauss (1966, 1969b, 1973, 1978) was to revert in part to Tylor's insight and to demonstrate through detailed analyses of myths, ART, and custom, that magic, science, and religion were indeed to be regarded together as premised on the inherent human capacity for logical classification.

Durkheim's major study The elementary forms of the religious life (1915) did not concern itself with the truth or falsity of religious beliefs, but instead insisted that the many religions throughout the world and history were based on a human need and so could not be regarded as illusory. He found inadequate Tylor's definition of religion as belief in godlike entities and argued that a broader concept was required, namely that of the SACRED. All things classified by humans were either sacred or profane. The critical feature of the sacred was that it united worshipers in a single moral community.          

Religion, therefore, had its basis in a social group, not individual psyches. The sacred had continuing rather than occasional effects on such groups because it derived from an early form of social differentiation, namely that of exogamous CLANS, each of which was symbolized by a specific animal or plant totem. These objects were not intrinsically sacred but drew their sacredness by virtue of a special ongoing relationship with what they symbolized.

Anthropology had for a long time followed the convention of making a distinction between the world religions and others supposedly not so globally comprehensive. A related but not isomorphic distinction is that between religions premised on a belief in a High God, perhaps the only permitted spiritual being, and Polytheism (many gods), sometimes expressed as a pantheon or assembly of gods, not necessarily hierarchically arranged. These distinctions are of limited usefulness. In what sense are the Semitic religions more globally comprehensive than, say, Hinduism and Buddhism? Each caters broadly for major areas of the world, but with significant minorities everywhere; similarly, since Taoism is practiced by vast numbers of people in China (Feuchtwang 1992), can it not be regarded as numerically if not geographically of equal significance? More importantly, we find influences of different religions on each other as a result of conquest and contact, making demarcation more a feature of the claims of a religion's priesthood than of worshipers' belief and practice.          

As regards religions defined as based on a central belief in a High God, both Buddhism, for the reasons already given, and Hinduism, with its hierarchy of major and minor gods and of lowly spirits, cannot be covered by such a rigid criterion. Given the role of Satan in the Semitic religions, especially in those Manichaean or dualistic versions that cast the Devil's evil as a force of potentially equal strength to that of God's goodness, we have to ask whether Satan is not really another deity, albeit of a negative kind, and whether these religions are not really duo-theistic rather than simply examples of monotheism.            

A more useful, though still shaky, distinction is between those religions that acknowledge dependence on written texts or scriptures that are held to be important and, in some cases, final arbiters of moral authority, and those that do not rely on written texts. Sacred texts presuppose a clergy able to read and interpret them and so set up a hierarchy of priests and worshipers who may sometimes only have access to their god(s) through such priests. Religious fundamentalists (L. Caplan 1987) argue that worshipers have strayed from a "true" understanding of the texts, which must therefore be followed strictly in order to restore people to their religion.          

Those religions that do not have written texts, sometimes called "animistic," "pantheistic," and "polytheistic" and most commonly found in Africa (Parkin 1991), Amazonia (J. Kaplan 1975), Papua New Guinea (Gell 1975), Aboriginal Australia (Berndt 1974), and parts of Malaysia (S. Howell 1984), may nevertheless have beliefs in a High God, though he or she tends to be of limited significance and is sometimes refracted as an immanent divine force in lesser spirits and objects of the environment, as among the Nuer of Sudan (Evans-Pritchard 1956). Priestly hierarchies are not absent in such nontextual religions, but less formal relations may obtain between priest and worshiper, who may also pray directly to ancestors or speak and negotiate with spirits through a medium or shaman. Such distinctions between textual and nontextual, and world and local, religions are shaky because, throughout the world, it is the interpenetration of the two that is the lived experience of most people, as Kapferer (1983) showed in an account of the interrelationship between demons and Buddhism in Sri Lanka. In all religions, too, sacrifice and offerings to godlike entities or spirits (even in Buddhism the nat spirits receive offerings) are a feature, sometimes taking more the form of PRAYERS and homage than the preferment of goods and immolation of animals.

Major theories in brief:

Major theories of religion and their brief subject matters are as follows:

Functionalists:

Basic needs theories – religion has been seen as a response to social needs like solidarity, value consensus, harmony and integration.

Durkheim: Elementary forms of religious life

• Sacred profane distinction as the basis for social integration
• Totemic clans are symbolic representatives of society hence worshipping totem is worshipping society and maintaining harmony
• ‘Collective conscience’ is formulated through religion through shared values and moral beliefs – religion fosters collective conscience.

Malinowski:

• Religion is linked with life crises such as major life stages like birth, puberty, marriage and death. These crises are surrounded with religious rituals
• Religion helps relieving anxiety with the uncontrollability of the world by people – fishing and canoe preparation rituals of Trobriand Islanders as Malinowski explains

Parsons

• Human actions are guided by norms and values – religion is crystallised forms of such norms and values.
• Religion functions to create provision of meaning to events that people do not expect or feel ought not happen.

Marxists:

• Generally sees religion as a distortion of meaning or a form of mystification.
• Marx argued that through religion people conceive their real world as something foreign.
• It is not simply the effects of oppression, rather it is an instrument of that oppression.
• Religion is a mechanism of social control to maintain existing class vis-a-vis power relationships.

Gender studies and feminists:

• Inclined with Marixist perspective which sees religion as a system of social control and reinforcement of existing power relationships, but it adds to this the dimensions of patriarchy. It sees religion as a product of patriarchy.
• Simone de Beauvoir in Second Sex provides radical feminist perspective for the existence of religion. For her, religion acts for women in similar ways to those in which Marx suggested reigion could act for oppressed classes. For her men use religion to control over women.

Rational choice theorists:

• Stark and Bainbridge (1985) believes that religion helps meeting universal human needs. In other words people do what they believe could bring rewards and avoid what they believe entail costs. Religion, therefore, bridges a critical gap between what people want and what they get or can get. Therefore, even though people want an eaternal life or reincarnation and there is not evidence of its possibility therefore, people embrace religion.

 

 

Interfaces 1 – Anthropology and Economics

Introduction: 1

Brief history: 1

First phase – the formalist-substantive debate (1870s to 1940s): 1

Second phase – methodological debate (1945- 1975): 2

The third phase – the neo-liberal paradign (1975- till date): 2

Enduring issues: 2

Informal economy: 2

One World Capitalism: 3

Money economy and crisis: 3

Approaches: 3

Marxist approach. 3

Cultural ecology to political economy. 3

Exchange and value: 4

See also: 4

 

Introduction:

The interface between anthropology and economics is as old as the discipline itself. ethnographic monographs have dealt with the economies of the people under discussion as a matter of course. The evolutionists were fundamentally interested in levels of technology and environmental “adaptations,” and functionalists interpreted all social systems in terms of the satisfaction of basic human needs. Subsequently, anthropologists influenced by Marx would see a given society’s “mode of production” as determinant, at least in the last instance, of politics, law, and ideology. Even though none of these theoretical paradigms dominates the field today, it is generally accepted that compelling accounts of social and symbolic behavior must relate them to the material organization of society. Economics is such an integral part of anthropological studies that a separate branch of economic anthropology has been developed.

Brief history:

The interface between economics and anthropology follows a three phase of development.

First phase – the formalist-substantive debate (1870s to 1940s):

The purpose of economic anthropology in the nineteenth century was to test the claim that a world economic order must be founded on the principles that underpinned Western industrial society. The search was on alternatives that might support a more just economy, wheather liberal, socialist, anarchist or communist. Since, society was understood to have not yet reach its final form, there was great interest in origins and evolution. Anthropology was thus the most inclusive way of thinking about economic possibilities. Therefore, in the first phase most anthropoligists were interested in whether the economic behaviour of the ‘savages’ was underpinned by the same notions of  ‘raitonality’ that were taken to motivate economic action in the West. The result was the famous formalist-substantivist debate. Formalist-Substantivist Debate is the dispute in Economic Anthropology between those scholars who argue that formal rules of neoclassical economic theory derived from the study of capitalist market societies can be used to explain the dynamics of premodern economies ("formalists") and those who argue that goods and services in the substantive economy are produced and distributed through specific cultural contexts ("substantivists"). Formalists contend that because all economies involve the rational pursuit of, access to, and use of, scarce resources by self-interested, maximizing social actors, formal economic rules can be used to explain them (H. Schneider 1974). Substantivists, by contrast, contend that different forms of exchange have different sets of rules and expectations (Dalton 1961). Following Karl Polanyi the substantivists argue that there are three major forms of exchange: reciprocity, redistribution, and market exchange (K. Polanyi et al. 1957). By this view, the rational, maximizing strategizing that lies at the heart of neoclassical economics and formalist economic anthropology is characteristic only of market economies.

Second phase – methodological debate (1945- 1975):

In this phase the debate was whether mainstream approaches and methodologies of studying economics was adequate for studying economics of pre-industrial – especially ‘tribal’ society or not. Formalists held that the tools of mainstream economics were adequate to this task, while, ‘substantivists’ were of the opinion that institutional approaches is more apt to study a substantive economy (Le Clair and Schneider 1968). Substantivists argued that economic life of substantive societies are embedded in other social institutions, ranging from the household to government and religion (Hart 2008).

The third phase – the neo-liberal paradign (1975- till date):

The formalist-substantivist debate has been replaced by more enduring issues such as Marxist approach (Seddon 1978) and Feminists approach (Moore 1988). Eventually, with globalisation and neo-liberal opening up of markets in post-colonial nations anthropologists started to include more aboutfill range of human economies and not just the exotic economics. We all now live in one world driven by capitalism, so anthropologists have studied that. There was a marked shift back home to the Western heartlands : but in real sense of a shrinking world, anthropologists are encouraged to develop new ways of studying ‘globalisation’ everywhere (Eriksen 2007).

Enduring issues:

Anthropologists today are dealing with the following issues with increasing close working relationship with economics:

Informal economy:

Is an outcome of attempts to see what happens to the rural people who migrates to the cities (Hart 1973). Anyone who visits the sprawling cities of what once called ‘the Third World’ can see that their streets are teeming with life, a constantly shifting crowd of hawkers, porter, taxi drivers, beggers, pimps, pickpockjeters, hustlers -  all of them getting by without the benefit o a ‘real jon’. Ethnographic study of this phenomenon generated the principal contribution made by anthropologists to development studies and economics.

One World Capitalism:

This results from a shift in the centre of production from so called developed nations to countries with cheaper labour like China, India and Brazil. This is most important feature of recent decade. In the neoliberal homelahds, a wave of outsourcing, downziging and casualization of the labour force undercut the political power of the unions and implied that the Western masses now participated in the capitalism primarily as consumers rather than producers.

Money economy and crisis:

The traditional substantivist understanding of the function of money in economies of pre-industrial societies have gathered enough evidence to teach the ‘modern’ money based economics what do to avert financial and economic crisis. Anthropologists have unearthed in what ways money based economics is seen as informal and contractual by the ‘pre-modern’ societies and that they have developed their own mode of economic practices coupling with money and their traditional means of subsistence economy.

Approaches:

Marxist approach

The Marxist anthropologists of the 1960s and 1970s made much more profound theoretical attempts to wrestle with noncapitalist economies. Althusser’s structuralist reading of Marx identified the analytic tools that might be extracted from Marx’s study of the rise of industrial capitalism and applied to alternative social formations. Meillassoux is considered the first anthropologist to analyze a precapitalist society in Marxist terms with his study of the Guro of Côte d’Ivoire (1964). Rather than applying Marx’s unsatisfactory prefabricated constructs of “Asiatic” or “slave”mode of production, he identified a lineage mode of production by analyzing the direction of surplus extraction in Guro society. In this work and in his subsequent Maidens, Meal, and Money (1981), Meillassoux pointed to the central importance of biological reproduction as a means of production in a situation of abundant land and relatively capital-poor technology.

Cultural ecology to political economy

With some exceptions, American anthropologists never adopted a Marxist problematic in the way that French and some British anthropologists did. There was, however, a turn to materialist principles of explanation in the 1960s and 1970s, as the ecological determinisms of an earlier period (Julian Steward, Leslie White) were revisited. Orlove categorized this work as neoevolutionist (Elman Service, Marshall Sahlins) and neofunctionalist (Marvin Harris, Andrew Vayda, Roy Rappaport). The latter group tended to view human societies and their environments as interactive systems, taking inspiration from the systems theory.Marshall Sahlins described a state of primitive abundance, calculating the resources required for hunters and gatherers to supply their needs and observing that their societies did not induce scarcity of want-satisfying means. Marvin Harris and Elman Service worked out different versions of the evolution of human society and culture in terms of adaptations to environmental constraints, the former tending to a techno-environmental determinism. Roy Rappaport derived the ecologically adaptive functions of various religious and ritual observances. Although materialist and evolutionary, none of this work was historical or dialectical.

Eric Wolf emphatically introduced history when he turned to dependency and world systems theory for a reappraisal of anthropology’s modus operandi. Dependency theory had been elaborated by radical economists working in Latin America and Africa who argued, against development and modernization theory, that global integration was serving to underdevelop peripheral regions of the globe at the expense of the capitalist “core.”Wallerstein examined the ways European imperialist expropriations had financed the industrial revolution at the expense of the colonies. The new attention to global interconnection took anthropology by storm.

Exchange and value:

In The Social Life of Things, Appadurai made an appeal for the utility of examining exchange independently of production (although it might be argued that this is what non-Marxist anthropology has been doing since Malinowski reported on the kula ring or since Paul Bohannan brought back proof of Polanyi’s ideas about the social embeddedness of trade from the Tiv). For a Marxist anthropologist, to look at exchange without considering production is to participate in ideological mystification. For most anthropologists, however, exchange processes offer a rich field for examining the cultural construction of meaning and value. Much anthropological and ethnohistorical work has addressed the historical exchange of objects across cultural space, where the meanings of the objects transacted are a matter of contest. In the early part of the century, Mauss drew widely on existing ethnographic sources to describe a kind of exchange in “archaic” societies that was essentially the opposite of the commodity fetishism of capitalist exchange. Anthropologists have taken up Mauss’s ideas about the relationships of debt and obligation created through gift exchange as a fundamental mechanism of social cohesion. Apart from Gregory’s attempt to ground gifting in specific social relations of production and reproduction, most of the theoretical impact of gifting seems to have been registered outside of the subdiscipline of economic anthropology.

See also:

Political economy in Anthropology: https://sumananthromaterials.blogspot.in/2011/10/political-economy-in-anthropology.html

Economic Anthropology: https://sumananthromaterials.blogspot.in/2011/09/economic-anthropology.html

Branches of Social-Cultural Anthropology: https://sumananthromaterials.blogspot.in/2014/11/branches-of-social-cultural-anthropology.html

Research Design

Research Design

Section 1.01     Research question: 2

(a)         Descriptive research: 2

(b)         Explanatory research: 3

(c)         Framing a research question: 3

(i)     Descriptive research questions: points to remember. 3

(ii)         Explanatory research questions: points to remember. 3

Article II. 4

Section 2.02     Range of research designs: 5

(i)     Experimental designs: 5

(ii)         Longitudinal design: 5

(iii)        Cross sectional design: 5

(iv)        Case studies: 5

Section 2.03     Research method and research design: 5

Section 2.04     Importance of research design: 6

(i)     Identifying plausible rival hypothesis (Threats to the conclusions): 7

1)      Theoretical and substantive rivals: 7

2)      Technical or methodological rivals: 7

Section 2.05     A Brief understanding of different research designs: 9

1.      Experimental designs: 9

Analysis of experimental data: 9

2.      Longitudinal designs: 10

Purposes of longitudinal designs: 10

Types of longitudinal designs: 10

Analysis of experimental data: 11

3.      Cross sectional designs: 12

4.      Case Study Designs: 12

What is a case?. 12

Case study and theory: 13

Explanatory case study: 13

Descriptive case studies: 14

Dimensions of case study design: 14

Types of case studies: 14

Case study analysis. 15

Analysing descriptive case studies: 16

Explanatory case studies: 16

Analysis for theory building: analytic induction. 19

 

Research design is analogous to construction of a building. Before starting the procedures, making estimates, purchasing materials, setting up dates for completion of project, it is important to understand what sort building do I need. Similarly research needs a design or a structure before data collection or analysis can commence. A research design is not just a work plan.

The function of research design is to ensure that the evidence obtained enables us to answer the initial question as unambiguously as possible (Vaus, 2001: 9).

Obtaining relevant evidence entails specifying the type of evidence needed to answer the research question, or to test a theory, to evaluate a programme, or to accurately describe some phenomenon. In other words, when designing research we need to ask: given this research question (or theory), what type evidence is needed to answer the question (or test the theory) in a convincing way?

Section 1.01                      Research question:

Research design begins with framing research question ends with analysing the data and presenting reports.

Research questions are fundamentally of two types:

1. What is going on? (descriptive research question)
2. Why is it going on? (explanatory research question)
    

(a)   Descriptive research:

Descriptive research involves accurate description of a phenomenon. Good description is needed before preparing for explanatory research question. For example, before asking Why the gap between rich and poor is increasing, it is important first to understand whether the gap is actually increasing or not.

Much of the evaluation programmes, government sponsored researches are descriptive in nature. Questions such as “how secular is the society?” “How much poverty is there in the community?” are descriptive but significantly abstract.

(b)   Explanatory research:

Explanatory research focuses on why questions. For example, after determining that the crime rate is increasing in the society, one might search for causes of such increase. This is then explanatory research.

Causation or establishing Causal connection is fundamental to explanatory research. Establishing causal connection requires stating factor X (gender) affects factor Y(Income).

The causal connection may be deterministic or probabilistic in nature.

A causation is deterministic where X is said to cause Y if, and only if X invariably produces Y. That is when X is present then Y will necessarily, inevitably and infallibly occur (Cook and Campbell, 1979). In social science however, because of complexity of human behaviour and the subjective, meaningful and voluntaristic components of human behaviour mean that it will never be possible to arrive at causal statements of the type.

(c)    Framing a research question:

Research begins with a research question. At first, it is important to make the research question as unambiguous as possible.

                (i)     Descriptive research questions: points to remember

1. Scope of the core concept (What aspect of the concept the research tends to focus on)
2. Time frame of the description (Whether contemporary or change over time)
3. Geographical location
4. Degree of generalisability (whether pattern identification is the aim)
5. Degree of abstraction (whether the description indicates to some abstract concepts, divorce rate with secularism, isolation, etc.)
6. Unit of analysis (individual, family, society, phenomena)

              (ii)     Explanatory research questions: points to remember

Explanatory research questions demand further specifications of the focus “so the research question must be clear about the style of explanatory research and identify which causes or consequences it will investigate” (Vaus, 2001: 19). Some terms are frequently used in explanatory researches, these are:

a)         Dependent variable:

It is a variable which depends on something else, usually treated as the effect in the causal model. It is usually designated as Y variable.

b)         Independent variable:

Presumed cause is the independent variable. It is also called as predictor variable, experimental variable or the explanatory variable. It is designated as X.  (Education (X) – income (Y)).

c)         Intervening variable:

Variables that come between dependent and independent variables are intervening variables (Z). They are the means by which X produces Y.

 

d)          

e)         Extraneous variables:

X

Two variables may be correlated without being causally related. This correlation may be due to the two factors being outcomes of a third factor. This is also symbolised as Z.

f)           

g)          

h)          

i)           Searching for causes or effects:

Changes in divorce rate since World War II (X)

The least focus explanatory research starts with identification of a core phenomenon and then searches for possible causes. The core phenomenon may be changes in divorce rate after World War II and the possible causes may be changing values, decline in religion, changing population mix, economic changes, legal reforms etc. Alternatively one may search for consequences of rising divorce rate.

 

 

 

Article II.    

The causal propositions can be Simple – an outcome of highly focused research question, or can be Complex which is an outcome of more exploratory research.

Taking different, competing approaches for explaining phenomena is another way of framing a research question. Different approaches are compared to find out which one is best fitted to facts.

a)         Ideographic and Nomothetic explanations:

Ideographic explanation involves examination of relatively a few (hence partial) causal factors in large number of cases. Nomothetic explanations on the other hand focus on a particular case or a few of cases to draw nearly complete explanations.

Section 2.02                      Range of research designs:

There are four types of research designs:

                (i)     Experimental designs:

1. One pretest
2. Two groups: experimental groups (exposed to the treatment), control group (not exposed to the treatment)
3. Random allocation to the groups before the pre-test
4. One intervention (test/treatment)
5. One pos-intervention measure on the outcome variables.

              (ii)     Longitudinal design:

1. One group
2. One pre-intervention measure on the outcome variable
3. One intervention where everyone receives the treatment
4. One post intervention measurement on the outcome variable.

            (iii)     Cross sectional design:

1. Instead of interventions the cross sectional design relies on existing variations in the independent variables in the sample.
2. At least on independent variable with at least two categories is present.
3. Data are collected at one point of time
4. There is no random allocation of groups.

            (iv)     Case studies:

1. Less depends on comparison more on exhaustive analysis of individual cases.
2. Might consist of single case study or multiple case studies which test a theory from multiple angles.
3. Treat a single case study as a single experiment.

Section 2.03                      Research method and research design:

For Yin (1989) design deals with a logical problem and not a logistical problem. Research design concentrates on nature of evidence and not the methods of data collection. Design is often confused with methods of data collection. For instance Case study is a research design where as methods of data collection may include participant observation, questionnaire, interview etc. Research design should not equate to either quantitative or qualitative method. Yin (1993) for example strongly recommends researcher not to equate case study with qualitative method. Marsh (1982) similarly points out the possibility of quantitative survey in providing information and explanations that are adequate at the level of meaning.

 

 

 

Section 2.04                      Importance of research design:

The need for research design stems from a sceptical approach to research and a view that scientific knowledge must always be provisional. The purpose of research design is to reduce the ambiguity of much research evidence. The prime importance of doing social scientific research is to seek for alternative ways of explaining a particular phenomenon. A proper research design helps in minimising the chance of drawing incorrect causal inferences from data.

                (i)     Identifying plausible rival hypothesis (Threats to the conclusions):

It is important to identify rival ways of accounting for the phenomena under study before carrying out the research. Vaus (2001) identifies two main types of rival hypothesis, first, theoretical and substantive rivals, and second, technical or methodological rivals.

1)        Theoretical and substantive rivals:

Theoretical literature helps in identifying possible theoretical explanations of a particular phenomenon. It requires a close reading of available theories and then asking oneself how different theories would explain the research question. (How feminists explain this issue? What might conflict theorists say?)

Other researchers’ account must be incorporated for having a clear understanding of the competing explanations.

Taking practitioners’, key informants’, policy makers’, advocates’ perspective is crucial as ‘insiders’ practical knowledge of the field is invaluable.

Self experience is also very important.

Lateral thinking, i.e. looking beyond the purview of literature solely devoted to the topic often brings fresh perspectives (Page – 24)

2)        Technical or methodological rivals:

Several technical or methodological factors may undermine conclusions drawn from a particular research, a good research design can minimise this threat.

Goldenberg (1992) outlines the types of methodological rivals. These are Situations including the context of data collection, attributes of the researcher and research participant, subjectivities of the researcher and research participant, sampling of items i.e. whether concepts are well measured, nature of sample, i.e. degree of generalisability, format of data collection – appropriate methods, analysis errors.

a)         Operationalisation:

Most social science research involves use of concepts (tap concepts) upon which observations are made. If the research is on effect of marital breakdown we need first to work out what is meant by marital breakdown.

We use concepts that are not readily observable. Therefore, we need to translate concepts to something observable and recordable. A clear definition of concepts we use is an important component of research design, which in turn requires developing nominal and operational definitions. Because of the abstract nature of concepts, e.g. social class, marital happiness, it becomes necessary to develop indicators of them.

b)         Clarifying concepts – nominal definitions:

Several concepts do not have a fixed or correct meaning. For example the concept of marriage breakdown can be seen from legal, emotional and logistics perspectives. Nominal definition specifies the meaning of the concept but remains abstract. Since, different definitions produce different findings, consequently defining concepts is crucial.

In order to arrive at nominal definition of the concept following steps can be followed:

1. Obtain a range of definitions from literature
2. Decide on a definition either by selecting a definition or by selecting relevant components from several existing definitions.
3. Delineate dimensions and subdimensions of the definition. For example the concept of child well being may have economic, psychological, physical, educational, social etc. Furthermore, the social dimension of child well being might have further subdimensions like relationship with peer, mother, father, etc. However, determining the dimensions and sub dimensions depends on the research question and nature of enquiry (Page 25 – 26).

c)         Clarifying concepts – Operational definition:

Operational definition is the observations to measure the concept. Operational definition is the way in which concepts are measured. For example, marriage breakdown as a concept can be measured in terms of quality of relationships. It is then studied on the basis of levels of conflict, types of communication, signs of lack of affection and level of cooperation or lack of cooperation.

Once the operational definition of the concept is developed we come to final stage of operationalisation. This entails the precise way in which indicators will be measured. This might involve developing questions for a questionnaire or identifying what and how observations will be made.

Section 2.05                      A Brief understanding of different research designs:

1.     Experimental designs:

Apart from the physical and biological sciences, it is difficult for social sciences and humanities to conduct experiments. However, despite of several difficulties, social sciences often make experiments.

Classic experimental design deals with an independent and a dependent variable. Whether we can infer the impact of intervention over the dependent variable depends on how well we can make experimental designs.

The designs involve two groups, viz. control group, i.e. where no intervention is given, and experimental group, i.e. where intervention is done. People are allotted randomly to these groups. One pre-test – intervention (to the experimental group) – one post test. The pre-test and post-test variation between the two groups is attributed to the intervention.

There are three contexts in which experiments are possible, these are, a) laboratory context, b) field context (usually development related inputs and then impact assessment), and c) natural context (ongoing experiments in the social world)

Analysis of experimental data:

Choices of statistics

There are several statistical techniques for the analysis of data coming out of experimental designs. The core of experimental analysis is the comparison of groups. The difference between control group and experimental group is the primary focus of experiments.

There are two major types, viz. descriptive statistics, and inferential statistics.

DESCRIPTIVE STATISTICS	INFERENTIAL STATISTICS
Summarising the data	Extrapolation of the findings to wider population / generalisation
	Probability sample is necessary pre-requisite

 

Level of selection:

Level of measurement of variables is critical in selecting particular statistical analysis. There are three main levels at which variables are measured:

Interval or ratio variable:

• Categories can be ranked from low to high in some meaningful way.
• It is possible to specify the amount of differences between the categories.
  Example: measuring age in terms of years, IQ test, income in rupees, etc.
  Ordinal variable:
• Categories can be ranked from low to high.
• Can not specify the exact difference between categories.

Example: age in social categories, like childhood, adolescence, young adult, middle aged and elderly. We cannot specify exact differences between these categories.

Nominal variable:

• Different categories do not have a set rank order.
  Example: religious affiliation

 

2.     Longitudinal designs:

There are different types of longitudinal designs which ultimately aim at measuring change over time. In consequence, it requires taking measurements in at least two time points.

To make longitudinal designs, it requires making certain critical decisions.

1. Should the same cases be followed?
   It requires to make choices between trend studies and panel studies.
   Trend studies: require taking data from comparable samples and not the same people over different period of time.
   Panel studies: require repeated survey over the same people.
2. How many times do I need to collect data?
   Although panel and trend studies require collecting data on two or several occasions. However, retrospective panel design does not require collecting data at different occasions. It depends on the memories of the informants.

Purposes of longitudinal designs:

1. Describing patterns of change and stability
2. Establishing temporal order.
   Longitudinal designs help in tracking the order in which events take place. While cross sectional study can establish the link between mental state and employment, longitudinal study can track the range of emotional state before, immediately after and then in specific intervals of employment.
3. Establishing developmental (age) effects: effect of age over political, religious conservatism
4. Establishing historical (period) effects: while doing a research on political or religious conservatism, it is important to not the effects of historical events. Studying people at different time can look at the impact of historical events over people.
5. Life course or career analysis.

Types of longitudinal designs:

Simple prospective panel design:

Requires collection of data at two points of time from the same sample.

Multiple point prospective panel designs:

Everything is same as above except that it involves multiple points of time. It is useful in:

1. Examine short and long term effects
2. Track when changes occur.
3. Plot the shape of any change.
4. Factors that precede any change.

Retrospective designs:

It depends on the possibility of reconstructing data over time by collecting all information at one point of time. 

It may be done by:

1. Retrospective panel design
2. Record linkage designs

Analysis of experimental data:

Since longitudinal design strives at understanding the change over time, measuring change is the most important component of its measure. There are certain issues to be kept in mind before going for the analysis:

1. Differentiate between aggregate and individual change:
   A change may be at aggregate level, or individual level. Even when there is no change in over all aggregate level, there may be individual level changes. For example, in a study of employment and unemployment, over time same number of people may change their status from employed to unemployed and from unemployed to employed. Thus, there will be change at aggregate, but at individual level significant change is found.
   To measure aggregate level change, we need to take aggregate measures, such as group mean, group variance, etc. To measure individual level change we need individual panel data to measure.
2. Qualitative and quantitative change:
   The type of analysis to be undertaken depends on the type of change being considered. If the study involves qualitative change (Nominal variable, for example) the analysis will be different from analysis which looks into quantitative change (Continuous variable, for example)
    
   Raw change score:

1. Quantitative dependent variable.
2. Calculate change scores for each person by substracting wave 1 scores from wave 2 scores and treating the difference as reflecting change.
   Residual change scores:
   Raw change score cannot identify the amount of change resulted from initial score. For example we can expect more change among the people who had initial extreme scores. One way to remove this effect is:

1. Residualise or regressed change scores
2. Identify cases where a person has changed more than would have been expected on the basis of their initial scores.
3. Regression analysis is done to predict wave 2 scores from wave 1 scores on the basis of a correlation of wave 1 and wave 2 scores.
4. Subtraction of predicted wave 2 score from actual wave 2 score. The remaining part is the residual gain score – the amount of gain that is not due to the influence of the initial wave 1 score.
   Percentage change:

1. Calculate the percentage change in the initial score.
2. The formula is the following
   Wave 2 score – wave 1 score
                                                                  X100
                                                Wave 1 score
   Distinguishing between real change and lack of reliability:
   Replicate the analysis using a separate measure to look for consistency
    

3.     Cross sectional designs:

Three distinctive features characterise Cross sectional designs: a) no time dimension, b) reliance on existing differences rather than change following intervention, and c) groups based on existing differences rather than random allocation.

Therefore:

1. Cross sectional designs essentially depends on the differences between groups rather than a change.
2. Groups are constructed on the basis of existing differences in the sample. The sample is divided up into groups according to the category of the independent variable to which they happen to belong.
3. Obtaining time dimension is possible if the design involves collecting information at a number of different time points but from a different sample at each time point.

4.     Case Study Designs:

1. Case study has been ignored or treated as soft options.
2. Some believe that case studies must be treated as a method for generating hypothesis to be tested eventually by rigorous research design.
3. It is important to understand that case studies have been fundamental to the substantive and methodological development of the social sciences. In social anthropology studies of tribes has been case studies.
4. Yin (1989) points out that unlike other research strategies, the potential catalogue for developing a research design for case studies is yet to be developed.

What is a case?

Units of analysis:

1. A case can be treated as unit of analysis. It is the unit that we seek to understand as a whole. 
2. The unit may be individuals, events, place, organisations, decisions or even a time period. (220)
   Holistic embedded units of analysis:
   It is important to distinguish between holistic and embedded units.
   Example:
   School = as a whole
   School having different subunits or elements:

1. Staff
   1. Teaching staff
   2. Non teaching staff.
2. Students
3. Guardians (220)
   A well designed case study will avoid examining just some of the constituent element. It will build up a picture of the case by taking into account information gained from many levels. The final case study will tell us more than, and something qualitatively different from, that which any constituent element of the case could tell us. While doing research with all the subunits of a case, we must be able to tell a much fuller, more complex understanding of the whole than would the perspective provided by any particular element of the case (221).
    

Case study and theory:

Case studies are essentially theoretical. It may be used to test or build a theory.

 

Explanatory case study:

The case studies are different from other designs as they seek to achieve both fuller and detailed explanations of phenomena. They seek to achieve both ideographic (fuller explanation and understanding of a case) and nomothetic (explanation of a phenomena by studying different cases) explanations.

Theory testing:

This approach is seen by Yin (1989) as being at the heart of case studies, begins with a theory, or a set of rival theories, regarding a particular phenomenon.

For example, the study may begin with the following question:

“What is the effect of devolved, school based control of staffing on the quality of education in a school?”

A devolved system means, that the school has the authority to recruit, control the salary and other incentives of its staffs.

We may take a school as a case where the devolved system has been introduced. We then will thoroughly investigate the school, its embedded elements and also would try to use the historical data to see if there is any link between devolution and quality of education. The point of this case study is to see if the theory works in a practical situation. What modification is needed? Does the theory require any refinement? Is the theory applicable only to specific circumstances?

Theory building case studies:

Using a theory building approach to case studies we select cases to help develop and refine the propositions and develop a theory that fits the cases we study.

For example, we might begin with simple proposition that devolve system improves the quality of education. Then we may select a school where devolve system is introduced. If it indeed yields good result, then the theory is true. We can compare two schools where the same system has resulted differently. We may then try to find out the reasons for such variation.

The differences between a theory testing and building approach is that in the former we begin with a set of quite specific propositions and then see if these work in real world situations. In the theory building model we begin with only a question and perhaps a basic proposition, look at real cases and end up with a more specific theory or set of propositions as a result of examining actual cases.

Clinical case studies:

Try to build up a full picture of the case so that we can evaluate which explanation best fits the facts of the case.

Descriptive case studies:

1. Good description is essential prerequisite of good explanation.
2. Description cannot be atheoretical. We always select and organise that which we describe. Descriptions will highlight aspects of the case. It will be more like a painting of a landscape than a photograph. It will be an interpretation rather than a mirror image.
3. Descriptive case studies may consist of a single or multiple cases. One way of reporting multiple case studies is to use typologies and ideal types. Typologies may be theoretically or empirically derived. A theoretically derived typology is one that is logically or theoretically possible. For example, Merton (1968) develops a typology of types of deviants based on the notions of cultural goals and institutionalised means of achieving those goals.

Accepts means of achieving the goals		Acceptance of cultural goals
		Accepts	Rejects
	Accepts	Conformist	Rituallists
	Rejects	Innovator	Retreatists

 

1. Another way of achieving typologies is Inductive typologies, in which we start with a question and then examine cases in the light of the question. A comparison of cases can then highlight clusters of similar cases.
   
   
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    

Dimensions of case study design:

1. Single or multiple – usually strategically selected multiple cases give a tough test to a theory.
2. Parallel or sequential – parallel design is one where all case studies are done simultaneously, usually by a number of researchers. In a sequential design, one case study follows another. Sequential design is effective for finding out issues to probe deeper.
3. Retrospective or prospective – retrospective design uses historical report, i.e., events are studied or data is collected afterwards. A prospective design goes on a considerable period of time, usually participation is needed.

Types of case studies:

• Descriptive or explanatory
• Theory testing or theory building
• Single or multiple case
• Holistic nor embedded units of analysis
• Paralle or sequential case studies
• Retrospective or prospective.
   
   

Explanatory?			Descriptive				Explanatory
Time			Retrospective		Prospective		Retrospective		Prospective
Case order			Parallel	Sequential	Parallel	Sequential	Parallel	Sequential	Parallel	Sequential
Cases	Units	Theory
Single case	Embedded units	Testing
		Building
	Holistic	Testing
		Building
Multiple cases	Embedded units	Testing
		Building
	Holistic	Testing
		Building

 Variations of case study designs (Vaus, 2001: 229)

Case study analysis

Methods for analysing case study is less systematically developed than are the techniques for analysing data collected with other types of research designs.

 

1. Statistical analysis:
   Case studies use statistics in a different way. Since, the aim of a case study is fuller and complex understanding of a phenomena, case study do not count number of occurrences of a given variable. However, a case may be statistically described. For example if we take a place as a case and population as embedded elements, we might need to describe the population statistically.
2. Meaning and context:
   Many social scientists argue for the importance of incorporating contextual meaning in analysis. Case studies provide lucrative options of incorporating contextual factors in research design.

Analysing descriptive case studies:

1. Theoretical dimension:
   Several scholars argue for the possibility of doing research without any theoretical orientation. This view suggests that facts must be allowed to speak for itself. However, Vaus (2001) in this book strongly denies any existence of such an approach.
    
   He states that
   “such an approach is both undesirable and impossible. Any description of any case always involves a selection of facts. This selection will be based on what we see as relevant and important. The very act of selecting means that we are making decisions about what is relevant. This selection process will be heavily influenced by our implicit theories. Furthermore, any reporting of a case will involve ordering the selected facts. The inevitable selectivity and ordering will mean that all descriptions are our descriptions, rather than the description of the case.”  (2001:251)
2. Ideal type analysis:
   Constructing ideal types based on theoretical and literature review is a way of describing cases. The analytic strategy is to use this ideal type as a template to guide the analysis of an actual case. We can use the template to see how closely our actual case fits the template.
   The use of the ideal type provides a way of looking at and organising the analysis for the descriptions of actual cases. Using this approach we avoid description that simply describes whatever we happen to find out about the case or simply reports the features that catch our attention.
3. Typologies:
   Typology is a set of types. We may construct types of different personalities, forms of government, types of organisational structure or types of marriages. This set of type may be based on ideal types or can be derived empirically. This approach helps in constructing an overall picture of a case taking a wide range of characteristics in account and not just the traits.
4. Cluster analytical approaches:
   These approaches involve identifying a set of variables we want to use as the basis for our typology. For example, in a study of an organisation we might have collected from out case studies information about the way decisions are made, the way in which rules and regulations are used, the degree of hierarchy, degree of rationality etc. In a set of case studies we could then group cases that had similar constellations of characteristics.
5. Time ordered descriptions:
   Time can be taken as a variable on the basis of which a case may be described. Histories of events, organisations, policies, or whatever the unit of analysis might be, represent a way of describing a case where the emphasis is on the sequence of events.

Explanatory case studies:

Theory plays an even more crucial role is explanatory case studies. Explanatory case studies are used either in theory building or theory testing.

When multiple case studies are used we may go for a two step analysis. First, we need to understand each case as a whole, and second, we can go for comparing these cases (Yin, 1989; Stake, 1994).

Theory testing analysis:

Theory testing can be done by a number of different ways. Yin (1989) outlines two approaches for doing this, a) Pattern matching and b) time series analysis.

Pattern matching:

Pattern matching is a form of theory testing in which we establish a detailed set of predictions before the case study is conducted. These predictions stem from a theoretical model and therefore represent a clear theory testing approach. The analysis could proceed by establishing a set of alternative patterns we would predict on the basis of competing theories.

The basic principal is that the more elaborate the predicted pattern (so long as it still follow logically from theory) the tougher the test of a theory. After the prediction of particular patterns we need to conduct the case study to see if the case does, in fact, match the predicted pattern. If the case matches the predicted pattern then the case supports the theory in the same way that a successful experiment supports a theory. If, however, the case does not match the predicted pattern the theory requires modification. Yin (1989) argues that on the basis of the degree of complexity of variables, i.e. with the increasing number of dependent and independent variables there are different types of pattern matching.

Simple patterns:

Simplest level pattern matching involves one independent variable with two values (e.g. male and female) and one dependent variable with two possible values (behaves in one of the two particular manners).

Example:

If we site the example of possible impact of devolve management over school’s performance, we have the devolve management system Xa and school’s better performance Yb.

Our prediction is

When Xa (devolve system/local based staffing system) exists then Yb (Better school performance/ high level of teachers’ commitment) will follow.

We would also expect that when Xb (centralised system) exists then Ya (lesser school performance/ low level of teachers’ commitment) will follow.

 

Dependent variable	Independent variable
		Xa	Xb
	Ya	Pattern 1	Pattern 2
	Yb	Pattern 3	Pattern 4

Table 1 Simple patterns: pattern matching for two variables each with two categories.

 

Additionally we may test alternative theories through case study. With the same issue of types of school administration we can have two theories.

1. Theory A: Local control will lead to higher commitment to work because effort and ‘fit’ is seen and rewarded (and lack of effort and not fitting in with school needs is punished)
2. Theory B: local control makes people feel more demoralised and vulnerable to local politics and prejudices, and does not recognise wider professional development etc. This leads to a lack of commitment and a lack of professionalism and to playing politics to win favour rather than fostering performance.
    
   Complex patterns with multiple variables:
   A more complex set of predictions is possible while using multiple variables. For example, if we use different variables of parental authority style and child’s level of anxiety.
    

Dependent variables
Independent variables	Parental authority style		Authoritarian		Authoritative		Permissive
	Child anxiety level		Low	High	Low	High	Low	High
	Child   behaviour	Compliant	Pattern 1	Pattern 2	Pattern 3	Pattern 4	Pattern 5	Pattern 6
		Rebellious	Pattern 7	Pattern 8	Pattern 9	Pattern 10	Pattern 11	Pattern 12
		Child sets own limits	Pattern 13	Pattern 14	Pattern 15	Pattern 16	Pattern 17	Pattern 18
		Tests parental limits	Pattern 19	Pattern 20	Pattern 21	Pattern 22	Pattern 23	Pattern 24

Table 2 logical patterns with two independent variables and one dependent variable

Theory testing:

For theory testing we need to specify theoretical proposition to test it. If the proposition is not supported by a case study then the next step is to refine the theory so that it can take account of the exception provided by the case. In this way the proposition vocers a wider and wider set of cases and becomes more powerful/ This process is called analytic induction.

 

Time series analysis:

Vaus (2001) argues that even though Yin (1989) treats time series analysis to be different from pattern matching, its logic is same. For Vaus, treating time series analysis as a variation to the pattern matching is more logical. The analytic strategy involves predicting a particular pattern of change over time. This type of pattern analysis can take one of two forms: trend analysis and chronological analysis.

Trend analysis:

Trend analysis is an examination of the direction of change in a particular variable or a set of variables. We address the question of whether the trend is upward (steep or gradual), shows no change, variable (up and down) or downward (steep or gradual).

Based on number of dependent and independent variables, predicted trends can range from the simple to the highly complex. 

 

Chronological analysis:

Chronological analysis involves predicting a sequence of events involving a number of different events or variables. Examples of a staged version of chronological analysis might be models that propose predictable stages in becoming a marijuana user (Becker, 1966), stages in the disintegration of intimate relationships (Vaughn, 1986), stages in the process of adjustment of retirement (Atchley, 1976) or changes in the relationships between adults and their parents as parents age (Marsden and Abrams, 1987). Yin (1989) indicates four types of ways in which events might be predicted to change in relation to each other.

• Some events must always occur before other events, with the reverse sequence being impossible
• Some events must always be followed by other events, on a contingency basis
• Some events can only follow other events after a specified passage of time;
• or certain time periods  in a case study may be marked by classes of events that differ substantially from those of other time periods [stages].
   
  Replication and generalisation:
  Generalisation from the case study depends on the replication logic of experiments rather than the statistical logic of surveys. We gain confidence in experimental results not just from the elegance of the experiment but from out capacity to predictably replicate results and to predictably fail to replicate results.
   
  We gain confidence in case study findings when we can accurately predict which types of cases will display particular patterns and which cases will not display specific patterns. Before strive for generalisability we need to ask the following questions:

1. Does the full set of outcome characteristics occur when the presumed causal factor is present? If so we have confirmation of our theory.
2. We would then find another case where the presumed causal factor is present and see whether the full set of outcomes is also present in that case. If so we have a literal replication of the previous case and further confirmation of out theory.
3. Do we get cases where the presumed causal factor is present but only some of the predicted outcome characteristics are present? If we find such cases then we have failed to replicate the theory and we would either reject or modify the theory. If we could find no cases where the cause was present and the full set of outcomes was not present then we have a theoretical replication.
4. We would then seek to find a case in which the presumed causal factor is not present. We would expect that the full set of outcomes would not occur when the cause was not present. That is, we should not find cases where we have the effects without our presumed cause. If we fail to find any such cases we have achieved further theoretical replication. (Vaus: 262 – 263)

Analysis for theory building: analytic induction

Analytic induction is ‘a strategy of analysis that directs the investigator to formulate generalisations that apply to all instances of the problem’ (Denzin, 1978:191). It is a method that can used to achieve descriptive generalisations or to arrive at causal explanations. It is a strategy that moves from individual cases and seeks to identify what the cases have in common. The common element provides the basis of theoretical generalisation. The modes of generalisations practiced by other research designs are based on statistical and probability calculations. WE estimate whether one group is more likely than other groups to behave in a particular way. Analytic induction, however, seeks to achieve universal generalisations.

Denzin (1978:192) summarises six key steps in the process of analytic induction:

1. Specify what it is you are seeking to explain (the dependent variable)
2. Formulate an initial and provisional possible explanation of the phenomenon you are seeking to explain (Your theory)
3. Conduct a study of a case selected to test your theory.
4. Review (and revise if necessary) your provisional theory in the light of the case or exlude the case as inappropriate.
5. Conduct further case studies to test the (revised) proposition and reformulate the proposition as required.
6. Continue with case studies (including looking for cases that might disprove the proposition) and revise the proposition until you achieve a causal proposition that accounts for all the cases.