READING SCRAPS IN QUALITATIVE RESEARC

INTRODUCTION TO QUALITATIVE RESEARCH

Qualitative research is a method of inquiry appropriated in many different academic disciplines, traditionally in the social sciences, but also in market research and further contexts.[1]

Qualitative researchers aim to gather an in-depth understanding of human behavior and the reasons that govern such behavior. The qualitative method investigates the why and how of decision making, not just what, where, when. Hence, smaller but focused samples are more often needed, rather than large samples.

Qualitative methods produce information only on the particular cases studied, and any more general conclusions are only hypotheses (informative guesses). Quantitative methods can be used to verify, which of such hypotheses are true.

The phrase 'qualitative research' was until the 1970s used only to refer to a discipline of anthropology or sociology. During the 1970s and 1980s qualitative research began to be used in other disciplines, and became a significant type of research in the fields of education studies, social work studies, women's studies, disability studies, information studies, management studies, nursing service studies, political science, psychology, communication studies, and many other fields. Qualitative research occurred in the consumer products industry during this period, with researchers investigating new consumer products and product positioning/advertising opportunities. The earliest consumer research pioneers including Gene Reilly of The Gene Reilly Group in Darien, CT, Jerry Schoenfeld of Gerald Schoenfeld & Partners in Tarrytown, NY and Martin Calle of Calle & Company, Greenwich, CT, also Peter Cooper in London, England, and Hugh Mackay in Mission, Australia. There continued to be disagreement about the proper place of qualitative versus quantitative research. In the late 1980s and 1990s after a spate of criticisms from the quantitative side, new methods of qualitative research evolved, to address the perceived problems with reliability and imprecise modes of data analysis. During this same decade, there was a slowdown in traditional media advertising spending, so there was heightened interest in making research related to advertising more effective.

In the last thirty years the acceptance of qualitative research by journal publishers and editors has been growing. Prior to that time many mainstream journals were prone to publish research articles based upon the natural sciences and which featured quantitative analysis.

Distinctions from quantitative research

(In simplified terms - Qualitative means a non-numerical data collection or explanation based on the attributes of the graph or source of data. For example, if you are asked to explain in qualitative terms a thermal image displayed in multiple colours, then you would explain the colour differences rather than the heat's numerical value.)

First, cases can be selected purposefully, according to whether or not they typify certain characteristics or contextual locations. Secondly, the role or position of the researcher is given greater critical attention. This is because in qualitative research the possibility of the researcher taking a 'neutral' or transcendental position is seen as more problematic in practical and/or philosophical terms. Hence qualitative researchers are often exhorted to reflect on their role in the research process and make this clear in the analysis. Thirdly, while qualitative data analysis can take a wide variety of forms it tends to differ from quantitative research in the focus on language, signs and meaning as well as approaches to analysis that are holistic and contextual, rather than reductionist and isolationist. Nevertheless, systematic and transparent approaches to analysis are almost always regarded as essential for rigor. For example, many qualitative methods require researchers to carefully code data and discern and document themes in a consistent and reliable way.

Perhaps the most traditional division in the way qualitative and quantitative research have been used in the social sciences is for qualitative methods to be used for exploratory (i.e., hypothesis-generating) purposes or explaining puzzling quantitative results, while quantitative methods are used to test hypotheses. This is because establishing content validity - do measures measure what a researcher thinks they measure? - is seen as one of the strengths of qualitative research. While quantitative methods are seen as providing more representative, reliable and precise measures through focused hypotheses, measurement tools and applied mathematics. By contrast, qualitative data is usually difficult to graph or display in mathematical terms.

Qualitative research is often used for policy and program evaluation research since it can answer certain important questions more efficiently and effectively than quantitative approaches. This is particularly the case for understanding how and why certain outcomes were achieved (not just what was achieved) but also answering important questions about relevance, unintended effects and impact of programs such as: Were expectations reasonable? Did processes operate as expected? Were key players able to carry out their duties? Were there any unintended effects of the program? Qualitative approaches have the advantage of allowing for more diversity in responses as well as the capacity to adapt to new developments or issues during the research process itself. While qualitative research can be expensive and time-consuming to conduct, many fields of research employ qualitative techniques that have been specifically developed to provide more succinct, cost-efficient and timely results. Rapid Rural Appraisal is one formalised example of these adaptations but there are many others.

Data Collection

Qualitative researchers may use different approaches in collecting data, such as the grounded theory practice, narratology, storytelling, classical ethnography, or shadowing. Qualitative methods are also loosely present in other methodological approaches, such as action research or actor-network theory. Forms of the data collected can include interviews and group discussions, observation and reflection field notes, various texts, pictures, and other materials.

Qualitative research often categorizes data into patterns as the primary basis for organizing and reporting resultsQualitative researchers typically rely on the following methods for gathering

information: Participant Observation, Non-participant Observation, Field Notes, Reflexive Journals, Structured Interview, Unstructured Interview, Analysis of documents and materials.

The ways of participating and observing can vary widely from setting to setting. Participant observation is a strategy of reflexive learning, not a single method of observing. In participant observation researchers typically become members of a culture, group, or setting, and adopt roles to conform to that setting. In doing so, the aim is for the researcher to gain a closer insight into the culture's practices, motivations and emotions. It is argued that the researchers' ability to understand the experiences of the culture may be inhibited if they observe without participating.

Some distinctive qualitative methods are the use of focus groups and key informant interviews. The focus group technique involves a moderator facilitating a small group discussion between selected individuals on a particular topic. This is a particularly popular method in market research and testing new initiatives with users/workers.

One traditional and specialized form of qualitative research is called cognitive testing or pilot testing which is used in the development of quantitative survey items. Survey items are piloted on study participants to test the reliability and validity of the items.

In the academic social sciences the most frequently used qualitative research approaches include the following:

1. Ethnographic Research, used for investigating cultures by collecting and describing data that is intended to help in the development of a theory. This method is also called “ethnomethodology” or "methodology of the people". An example of applied ethnographic research, is the study of a particular culture and their understanding of the role of a particular disease in their cultural framework.

2. Critical Social Research , used by a researcher to understand how people communicate and develop symbolic meanings.

3. Ethical Inquiry , an intellectual analysis of ethical problems. It includes the study of ethics as related to obligation, rights, duty, right and wrong, choice etc.

4. Foundational Research, examines the foundations for a science, analyses the beliefs and develops ways to specify how a knowledge base should change in light of new information.

5. Historical Research, allows one to discuss past and present events in the context of the present condition, and allows one to reflect and provide possible answers to current issues and problems. Historical research helps us in answering questions such as: Where have we come from, where are we, who are we now and where are we going?

6. Grounded Theory , is an inductive type of research, based or “grounded” in the observations or data from which it was developed; it uses a variety of data sources, including quantitative data, review of records, interviews, observation and surveys.

7. Phenomenological Research , describes the “subjective reality” of an event, as perceived by the study population; it is the study of a phenomenon.

8. Philosophical Research, is conducted by field experts within the boundaries of a specific field of study or profession, the best qualified individual in any field of study to use an intellectual analyses, in order to clarify definitions, identify ethics, or make a value judgment concerning an issue in their field of study.

Data analysis

Interpretive techniques

The most common analysis of qualitative data is observer impression. That is, expert or bystander observers examine the data, interpret it via forming an impression and report their impression in a structured and sometimes quantitative form.

Coding

Coding is an interpretive technique that both organizes the data and provides a means to introduce the interpretations of it into certain quantitative methods. Most coding requires the analyst to read the data and demarcate segments within it. Each segment is labeled with a “code” – usually a word or short phrase that suggests how the associated data segments inform the research objectives. When coding is complete, the analyst prepares reports via a mix of: summarizing the prevalence of codes, discussing similarities and differences in related codes across distinct original sources/contexts, or comparing the relationship between one or more codes.

Some qualitative data that is highly structured (e.g., open-end responses from surveys or tightly defined interview questions) is typically coded without additional segmenting of the content. In these cases, codes are often applied as a layer on top of the data. Quantitative analysis of these codes is typically the capstone analytical step for this type of qualitative data.

Contemporary qualitative data analyses are sometimes supported by computer programs. These programs do not supplant the interpretive nature of coding but rather are aimed at enhancing the analyst’s efficiency at data storage/retrieval and at applying the codes to the data. Many programs offer efficiencies in editing and revising coding, which allow for work sharing, peer review, and recursive examination of data.

A frequent criticism of coding method is that it seeks to transform qualitative data into quantitative data, thereby draining the data of its variety, richness, and individual character. Analysts respond to this criticism by thoroughly expositing their definitions of codes and linking those codes soundly to the underlying data, therein bringing back some of the richness that might be absent from a mere list of codes.

Recursive abstraction

Some qualitative datasets are analyzed without coding. A common method here is recursive abstraction, where datasets are summarized, those summaries are then further summarized, and

so on. The end result is a more compact summary that would have been difficult to accurately discern without the preceding steps of distillation.

A frequent criticism of recursive abstraction is that the final conclusions are several times removed from the underlying data. While it is true that poor initial summaries will certainly yield an inaccurate final report, qualitative analysts can respond to this criticism. They do so, like those using coding method, by documenting the reasoning behind each summary step, citing examples from the data where statements were included and where statements were excluded from the intermediate summary.

Mechanical techniques

Some techniques rely on leveraging computers to scan and sort large sets of qualitative data. At their most basic level, mechanical techniques rely on counting words, phrases, or coincidences of tokens within the data. Often referred to as content analysis, the output from these techniques is amenable to many advanced statistical analyses.

Mechanical techniques are particularly well-suited for a few scenarios. One such scenario is for datasets that are simply too large for a human to effectively analyze, or where analysis of them would be cost prohibitive relative to the value of information they contain. Another scenario is when the chief value of a dataset is the extent to which it contains “red flags” (e.g., searching for reports of certain adverse events within a lengthy journal dataset from patients in a clinical trial) or “green flags” (e.g., searching for mentions of your brand in positive reviews of marketplace products).

A frequent criticism of mechanical techniques is the absence of a human interpreter. And while masters of these methods are able to write sophisticated software to mimic some human decisions, the bulk of the “analysis” is nonhuman. Analysts respond by proving the value of their methods relative to either a) hiring and training a human team to analyze the data or b) letting the data go untouched, leaving any actionable nuggets undiscovered.

Paradigmatic differences

Contemporary qualitative research has been conducted from a large number of various paradigms that influence conceptual and metatheoretical concerns of legitimacy, control, data analysis, ontology, and epistemology, among others. Research conducted in the last 10 years has been characterized by a distinct turn toward more interpretive, postmodern, and critical practices[6]. Guba and Lincoln (2005) identify five main paradigms of contemporary qualitative research: positivism, postpositivism, critical theories, constructivism, and participatory/cooperative paradigms. Each of the paradigms listed by Guba and Lincoln are characterized by axiomatic differences in axiology, intended action of research, control of research process/outcomes, relationship to foundations of truth and knowledge, validity (see below), textual representation and voice of the researcher/participants, and commensurability with other paradigms. In particular, commensurability involves the extent to which paradigmatic concerns “can be retrofitted to each other in ways that make the simultaneous practice of both possible”[8]. Positivist and postpositivist paradigms share commensurable assumptions but are

largely incommensurable with critical, constructivist, and participatory paradigms. Likewise, critical, constructivist, and participatory paradigms are commensurable on certain issues (e.g., intended action and textual representation).

Validation

A central issue in qualitative research is validity (also known as credibility and/or dependability). There are many different ways of establishing validity, including: member check, interviewer corroboration, peer debriefing, prolonged engagement, negative case analysis, auditability, confirmability, bracketing, and balance. Most of these methods were coined, or at least extensively described by Lincoln and Guba (1985)

Academic research

By the end of the 1970s many leading journals began to publish qualitative research articles [3]

and several new journals emerged which published only qualitative research studies and articles about qualitative research methods.

In the 1980s and 1990s, the new qualitative research journals became more multidisciplinary in focus moving beyond qualitative research’s traditional disciplinary roots of anthropology, sociology, and philosophy.

The new millennium saw a dramatic increase in the number of journals specializing in qualitative research with at least one new qualitative research journal being launched each year.

In statistics, a sample is a subset of a population. Typically, the population is very large, making a census or a complete enumeration of all the values in the population impractical or impossible. The sample represents a subset of manageable size. Samples are collected and statistics are calculated from the samples so that one can make inferences or extrapolations from the sample to the population. This process of collecting information from a sample is referred to as sampling.

The best way to avoid a biased or unrepresentative sample is to select a random sample, also known as a probability sample. A random sample is defined as a sample where the probability that any individual member from the population being selected as part of the sample is exactly the same as any other individual member of the population. Several types of random samples are simple random samples, systematic samples, stratified random samples, and cluster random samples.

A sample that is not random is called a nonrandom sample or a nonprobability sample. Some examples of nonrandom samples are convenience samples, judgment samples, purposive samples, quota samples, snowball samples, and quadrature nodes in quasi-Monte Carlo methods.

In the social sciences, quantitative research refers to the systematic empirical investigation of quantitative properties and phenomena and their relationships. The objective of quantitative

research is to develop and employ mathematical models, theories and/or hypotheses pertaining to phenomena. The process of measurement is central to quantitative research because it provides the fundamental connection between empirical observation and mathematical expression of quantitative relationships.

Quantitative research is used widely in social sciences such as sociology, anthropology, and political science. Research in mathematical sciences such as physics is also 'quantitative' by definition, though this use of the term differs in context. In the social sciences, the term relates to empirical methods, originating in both philosophical positivism and the history of statistics, which contrast qualitative research methods.

Qualitative methods produce information only on the particular cases studied, and any more general conclusions are only hypotheses. Quantitative methods can be used to verify, which of such hypotheses are true.

Quantitative research is generally made using scientific methods, which can include:

The generation of models, theories and hypotheses The development of instruments and methods for measurement

Experimental control and manipulation of variables

Collection of empirical data

Modeling and analysis of data

Evaluation of results

In the social sciences particularly, quantitative research is often contrasted with qualitative research which is the examination, analysis and interpretation of observations for the purpose of discovering underlying meanings and patterns of relationships, including classifications of types of phenomena and entities, in a manner that does not involve mathematical models. Approaches to quantitative psychology were first modelled on quantitative approaches in the physical sciences by Gustav Fechner in his work on psychophysics, which built on the work of Ernst Heinrich Weber. Although a distinction is commonly drawn between qualitative and quantitative aspects of scientific investigation, it has been argued that the two go hand in hand. For example, based on analysis of the history of science, Kuhn (1961, p. 162) concludes that “large amounts of qualitative work have usually been prerequisite to fruitful quantification in the physical sciences”[1]. Qualitative research is often used to gain a general sense of phenomena and to form theories that can be tested using further quantitative research. For instance, in the social sciences qualitative research methods are often used to gain better understanding of such things as intentionality (from the speech response of the researchee) and meaning (why did this person/group say something and what did it mean to them?) (Kieron Yeoman).

The study of organizational storytelling, sometimes called “Narrative Knowledge,” attempts to recount events in the form of a story within the context of an organization.[1] It is an emerging discipline in the fields of management, strategy and organization studies.

Storytelling has long been a feature of human societies, groups and organizations. Stories are pithy narratives with plots, characters and twists that can be full of meaning. While some stories may be pure fiction, others are inspired by real events. Their relation to such events, however, is tenuous – in stories, accuracy is almost always sacrificed for effect. Stories entertain, inform, advise, warn and educate. They often pass moral judgements on events, casting their characters in roles like hero, villain, fool and victim. They are capable of stimulating strong emotions of sympathy, anger, fear, anxiety and so forth.

Whether in or out of organizations, people often recount experiences in story-like forms and listen to stories of others. By placing themselves at the centre of our stories, they seek to make sense of these experiences, whether happy, trying or painful. Organizational theorists have now become aware that much learning in organizations takes place through storytelling; this is sometimes referred to as narrative knowledge. They have also realized that there is much we can learn by studying the stories that people tell about each other and about the organization as a whole. Stories can open windows into the cultural, political and emotional lives of organizations, allowing people to express deep and sometimes hidden or conflicting emotions.

In recent years, numerous consultants have turned to stories as vehicles for enhancing organizational communication, performance and learning, as well as the management of change. While the success of these approaches is qualified, there can be little doubt that, in the hands of imaginative leaders, educators, gurus and prophets, stories are powerful devices for managing meaning.

Storytelling and research into organizations

Organizational theory has been late in taking an interest in stories that people tell in and about organizations. (Denning 2007) The functions of stories for group cohesion or for relieving tedium and tension have been noted, but it is only recently that the importance of stories in organizational research has started to be recognised. In the first place, there is a recognition that organizations are not story-free bureaucratic spaces; storytelling is an important organizational phenomenon in its own right, which merits research attention. It is now becoming acceptable to talk of organizational lore which may be studied in ways similar to the study of folklore. As the study of language, discourse and text have assumed centre-place in their discipline, organizational theorists have turned to stories, jokes and myths, the stock in trade of ethnographers and folklorists, as vital ingredients of organizations.

The study of organizational storytelling, however, goes beyond the analysis of folklore, interesting as this is in its own right. By collecting stories in a particular organization, by listening and comparing different accounts, by investigating how narratives are constructed around specific events, by examining which events in an organization's history generate stories and which ones fail to do so, we gain access to deeper organizational realities, closely linked to their members' experiences. In this way, stories enable us to study organizational politics, culture and change in uniquely illuminating ways, revealing how wider organizational issues are viewed, commented upon and worked upon by their members.

In telling a story, the requirements of accuracy and veracity are relaxed in the interest of making a symbolic point. Poetic license is the prerogative of storytelling. At the same time, by shrouding a point in symbolic terms, stories are able to evade censors, both internal and external, and express views and feelings which may be unacceptable in straight talk. Criticizing one's superior may be frowned upon in most organizations, but a joke at his/her expense is less so. A story or a tale is a way of 'testing the water' to see whether others feel like the story teller, reading the same meaning into events. The teller of a joke or a story can always fall back on the defence "It was only a joke/story!".

Stories in organizations are defined in different ways. Some definitions extend stories in different directions, seeking to encompass many types of meaningful text or discourse under the category of a story. A company logo, the shining surface of a car, a piece of graffiti and an academic textbook may then all be seen as stories. Gabriel has argued that such definitions do not do justice to the specific qualities inherent in stories understood in a narrower way. He accordingly defines stories as

"narratives with plots and characters, generating emotion in narrator and audience, through a poetic elaboration of symbolic material. This material may be a product of fantasy or experience, including an experience of earlier narratives. Story plots entail conflicts, predicaments, trials and crises which call for choices, decisions, actions and interactions, whose actual outcomes are often at odds with the characters' intentions and purposes." (Gabriel 2000:239)

Thus, stories are seen as emotionally and symbolically charged narratives; they do not present information or facts about 'events', but they enrich, enhance and infuse facts with meaning. This is both their strength and a potential weakness. For stories will often compromise accuracy in the interest of making a point or generating an emotion; they may focus on the incidental details, remaining stubbornly silent about what a researcher may regard as vital clues; they may contain inconsistencies, imprecisions, lacunae, non-sequiturs, illogicalities and ambiguities. Ultimately, the truth of a story lies not in its accuracy but in its meaning.

Researchers who want to use stories as a research instrument must be prepared to sacrifice at least temporarily some of the core values of their trade and adopt instead a rather alien attitude towards their respondents and their texts. They must rid themselves of the assumption that quality data are objective, reliable, accurate etc. and must be prepared to engage with the emotions and the meanings which reside in the text. The very recognition that a narrative constitutes or is moving towards becoming a story rather than being a factual account depends on such an emotional engagement. Faced with distortions and ambiguities, researchers must resist the temptation of 'setting the record straight'; instead, they must learn to relish the text, seeking to establish the narrative needs, and through them the psychological and organizational needs, which distortions, ambiguities and inaccuracies serve.

In this way, organizational researchers become fellow-travellers on the narrative, engaging with it emotionally, displaying interest, empathy and pleasure in the storytelling process. They do not risk alienating the storyteller by seeming to doubt the narrative or by placing him under cross-examination, but conspires to detach the narrative from the narrowness of the discourse of facts, guiding it instead in the direction of free-association, reverie and fantasy. Contradictions and

ambiguities in the narrative are accepted with no embarrassment. Ambiguity lies at the heart of many stories, displaying an individual's ambivalent feelings or partial knowledge or understanding. While the researcher may ask for clarification of particular aspects of the story, the storyteller must feel that such clarification is asked in the interest of increased pleasure and empathy rather than in the form of pedantic inquiry.

The study of organizational storytelling is an emerging discipline in the fields of management, strategy and organization studies. As an emerging discipline it is contested ground; some practitioners have been more interested in describing it is a purposeful tool to be used by business people, leaders and managers. Some academics are cynical about attempts to turn storytelling into a communication tool at the disposal of those who already have power. They argue that contrived or manufactured stories tend to generate anti-stories, provoking cynicism, mistrust and ridicule.

Overall, when storytelling is skilful and authentic, it can be used to lead downwards, upwards and sideways in a variety of hierarchical settings, including organizations, politics, schools or families. It can be used to achieve a variety of purposes, including sparking action, communicating who you are, transmitting the brand, sharing knowledge, getting collaboration, transmitting values, taming the grapevine or leading people into the future. Given the scarcity of alternative rhetorical devices to achieve these objectives, the choice is not so much whether or not to use storytelling, but rather whether or not to use it skillfully and authentically. These organizational stories capture attention, excite imagination, and while being not value neutral, they tend to moralize and pass-judgment. Organizational storytelling has become increasingly popular method of inquiry because it allows researchers to get a sense of the culture of an organization and to record otherwise tacit knowledge.

Ethnography (Greek ἔθνος ethnos = folk/people and γράφειν graphein = writing) is a qualitative research method often used in the social sciences, particularly in anthropology and in sociology.[1] It is often employed for gathering empirical data on human societies/cultures. Data collection is often done through participant observation, interviews, questionnaires, etc. Ethnography aims to describe the nature of those who are studied (i.e. to describe a people, an ethnos) through writing.[2] In the biological sciences, this type of study might be called a "field study" or a "case report," both of which are used as common synonyms for "ethnography".[3]

Ethnographic studies are usually holistic, founded on the idea that humans are best understood in the fullest possible context, including: the place where they live, the improvements they've made to that place, how they are making a living and providing food, housing, energy and water for themselves, what their marriage customs are, what language(s) they speak and so on. Ethnography has connections to genres as diverse as travel writing, colonial office reports, the play and the novel.[4] Many cultural anthropologists consider ethnography the essence of the discipline.[5] It would be a rare program in graduate cultural anthropology that didn't require an ethnography as part of the doctoral process.[6]

Evaluating Ethnography

Ethnographic methodology is not usually evaluated in terms of philosophical standpoint (such as positivism and emotionalism), ethnographies nonetheless need to be evaluated in some manner. While there is no consensus on evaluation standards, Richardson (2000, p. 254) [7] provides 5 criteria that ethnographers might find helpful.

1. Substantive Contribution: “Does the piece contribute to our understanding of social-life?”2. Aesthetic Merit: “Does this piece succeed aesthetically?”

3. Reflexivity: “How did the author come to write this text…Is there adequate self-awareness and self-exposure for the reader to make judgments about the point of view?”

4. Impact: “Does this affect me? Emotionally? Intellectually?” Does it move me?

5. Expresses a Reality: “Does it seem ‘true’—a credible account of a cultural, social, individual, or communal sense of the ‘real’?”

Data Collection methods

One of the most common methods for collecting data in an ethnographic study is direct, first-hand observation of daily participation. This can include participant observation. Another common method is interviewing, which may include conversation with different levels of form and can involve small talk to long interviews. A particular approach to transcribing interview data might be genealogical method. This is a set of procedures by which ethnographers discover and record connections of kinship, descent and marriage using diagrams and symbols. Questionnaires can be used to aid the discovery of local beliefs and perceptions and in the case of longitudinal research, where there is continuous long-term study of an area or site, they can act as valid instrument for measuring changes in the individuals or groups studied.

Differences across disciplines

The ethnographical method is used across a range of different disciples, primarily by anthropologists but also frequently by sociologists. Cultural studies, economics, social work, education, ethnomusicology, folklore, geography, history, linguistics, communication studies, performance studies and psychology are other fields which have made use of ethnography.

Cultural and social anthropology

Cultural anthropology and social anthropology were developed around ethnographic research and their canonical texts which are mostly ethnographies: e.g. Argonauts of the Western Pacific (1922) by Bronisław Malinowski, Coming of Age in Samoa (1928) by Margaret Mead, The Nuer (1940) by E. E. Evans-Pritchard, or Naven (1936, 1958) by Gregory Bateson. Cultural and social anthropologists today place such a high value on actually doing ethnographic research that ethnology—the comparative synthesis of ethnographic information—is rarely the foundation for a career.[citation needed] The typical ethnography is a document written about a particular people, almost always based at least in part on emic views of where the culture begins and ends. Using

language or community boundaries to bound the ethnography is common.[8] Ethnographies are also sometimes called "case studies." Ethnographers study and interpret culture, its universalities and its variations through ethnographic study based on fieldwork. An ethnography is a specific kind of written observational science which provides an account of a particular culture, society, or community. The fieldwork usually involves spending a year or more in another society, living with the local people and learning about their ways of life. Ethnographers are participant observers. They take part in events they study because it helps with understanding local behavior and thought. Classic examples is Carol Stack's All Our Kin, Jean Briggs's "Never in Anger," Richard Lee's "Kalahari Hunter-Gatherers," Victor Turner's "Forest of Symbols," David Maybry-Lewis's "Akew-Shavante Society," E.E. Evans-Pritchard's "The Nuer" and Claude Levi-Strauss's "Tristes Tropiques." Iterations of ethnographic representations in the classic, modernist camp include Bartholomew Dean’s recent (2009) contribution, Urarina Society, Cosmology, and History in Peruvian Amazonia.

A typical ethnography attempts to be holistic and typically follows an outline to include a brief history of the culture in question, an analysis of the physical geography or terrain inhabited by the people under study, including climate, and often including what biological anthropologists call habitat. Folk notions of botany and zoology are presented as ethnobotany and ethnozoology alongside references from the formal sciences. Material culture, technology and means of subsistence are usually treated next, as they are typically bound up in physical geography and include descriptions of infrastructure. Kinship and social structure (including age grading, peer groups, gender, voluntary associations, clans, moieties, and so forth, if they exist) are typically included. Languages spoken, dialects and the history of language change are another group of standard topics.[12] Practices of childrearing, acculturation and emic views on personality and values usually follow after sections on social structure. Rites, rituals, and other evidence of religion have long been an interest and are sometimes central to ethnographies, especially when conducted in public where visiting anthropologists can see them.

As ethnography developed, anthropologists grew more interested in less tangible aspects of culture, such as values, worldview and what Clifford Geertz termed the "ethos" of the culture. Clifford Geertz's own fieldwork used elements of a phenomenological approach to fieldwork, tracing not just the doings of people, but the cultural elements themselves. For example, if within a group of people, winking was a communicative gesture, he sought to first determine what kinds of things a wink might mean (it might mean several things). Then, he sought to determine in what contexts winks were used, and whether, as one moved about a region, winks remained meaningful in the same way. In this way, cultural boundaries of communication could be explored, as opposed to using linguistic boundaries or notions about residence. Geertz, while still following something of a traditional ethnographic outline, moved outside that outline to talk about "webs" instead of "outlines" of culture.

Within cultural anthropology, there are several sub-genres of ethnography. Beginning in the 1950s and early 1960s, anthropologists began writing "bio-confessional" ethnographies that intentionally exposed the nature of ethnographic research. Famous examples include Tristes Tropiques (1955) by Claude Lévi-Strauss, The High Valley by Kenneth Read, and The Savage and the Innocent by David Maybury-Lewis, as well as the mildly fictionalized Return to Laughter by Elenore Smith Bowen (Laura Bohannan). Later "reflexive" ethnographies refined

the technique to translate cultural differences by representing their effects on the ethnographer. Famous examples include "Deep Play: Notes on a Balinese Cockfight" by Clifford Geertz, Reflections on Fieldwork in Morocco by Paul Rabinow, The Headman and I by Jean-Paul Dumont, and Tuhami by Vincent Crapanzano. In the 1980s, the rhetoric of ethnography was subjected to intense scrutiny within the discipline, under the general influence of literary theory and post-colonial/post-structuralist thought. "Experimental" ethnographies that reveal the ferment of the discipline include Shamanism, Colonialism, and the Wild Man by Michael Taussig, Debating Muslims by Michael F. J. Fischer and Mehdi Abedi, A Space on the Side of the Road by Kathleen Stewart, and Advocacy after Bhopal by Kim Fortun.

Sociology

Sociology is another field which prominently features ethnographies. Urban sociology and the Chicago School in particular are associated with ethnographic research, with some well-known early examples being Street Corner Society by William Foote Whyte and Black Metropolis by St. Clair Drake and Horace R. Caton. Some of the influence for this can be traced to the anthropologist Lloyd Warner who was on the Chicago sociology faculty, and to Robert Park's experience as a journalist. Symbolic interactionism developed from the same tradition and yielded several excellent sociological ethnographies, including Shared Fantasy by Gary Alan Fine, which documents the early history of fantasy role-playing games. Other important ethnographies in the discipline of sociology include Pierre Bourdieu's work on Algeria and France, Paul Willis's Learning To Labour on working class youth, and the work of Elijah Anderson, Mitchell Duneier, and Loic Wacquant on black America. But even though many sub-fields and theoretical perspectives within sociology use ethnographic methods, ethnography is not the sine qua non of the discipline, as it is in cultural anthropology.

Communication Studies

Beginning in the 1960s and 70s, ethnographic research methods began to be widely employed by communication scholars. Studies such as Gerry Philipsen's analysis of cultural communication strategies in a blue-collar, working class neighborhood on the south side of Chicago, Speaking 'Like a Man' in Teamsterville, paved the way for the expansion of ethnographic research in the study of communication.

Scholar of communication studies use ethnographic research methods to analyze communication behaviors, seeking to answer the "why" and "how come" questions of human communication. [16]

Often this type of research results in a case study or field study such as an analysis of speech patterns at a protest rally or the way firemen communicate during "down time" at a fire station. Like anthropology scholars, communication scholars often immerse themselves, participate in and/or directly observe the particular wikt:social group being studied.[17]

Other fields

The American anthropologist George Spindler (Stanford University) was a pioneer in applying ethnographic methodology to the classroom.

Anthropologists like Daniel Miller and Mary Douglas have used ethnographic data to answer academic questions about consumers and consumption. In this sense, Tony Salvador, Genevieve Bell, and Ken Anderson describe design ethnography as being "a way of understanding the particulars of daily life in such a way as to increase the success probability of a new product or service or, more appropriately, to reduce the probability of failure specifically due to a lack of understanding of the basic behaviors and frameworks of consumers."[18]

Businesses, too, have found ethnographers helpful for understanding how people use products and services, as indicated in the increasing use of ethnographic methods to understand consumers and consumption, or for new product development (such as video ethnography). The recent Ethnographic Praxis in Industry (EPIC) conference is evidence of this. [citation needed] Ethnographers' systematic and holistic approach to real-life experience is valued by product developers, who use the method to understand unstated desires or cultural practices that surround products. Where focus groups fail to inform marketers about what people really do, ethnography links what people say to what they actually do—avoiding the pitfalls that come from relying only on self-reported, focus-group data.

Ethics

Gary Alan Fine argues that the nature of ethnographic inquiry demands that researchers deviate from formal and idealistic rules or ethics that have come to be widely accepted in qualitative and quantitative approaches to research. Many of these ethical assumptions are rooted in positivist and post-positivist epistemologies that have adapted over time, but nonetheless are apparent and must be accounted for in all research paradigms. These ethical dilemmas are evident throughout the entire process of conducting ethnographies, including the design, implementation, and reporting of an ethnographic study. Essentially, Fine maintains that researchers are typically not as ethical as they claim or assume to be — and that “each job includes ways of doing things that would be inappropriate for others to know”.[19]

Fine is not necessarily casting blame or pointing his finger at ethnographic researchers, but rather is attempting to show that researchers often make idealized ethical claims and standards which in actuality are inherently based on partial truths and self-deceptions. Fine also acknowledges that many of these partial truths and self-deceptions are unavoidable. He maintains that “illusions” are essential to maintain an occupational reputation and avoid potentially more caustic consequences. He claims, “Ethnographers cannot help but lie, but in lying, we reveal truths that escape those who are not so bold”.[20] Based on these assertions, Fine establishes three conceptual clusters in which ethnographic ethical dilemmas can be situated: “Classic Virtues,” “Technical Skills,” and “Ethnographic Self.”

Much debate surrounding the issue of ethics arose after the ethnographer Napoleon Chagnon conducted his ethnographic fieldwork with the Yanomamo people of South America.

Classic Virtues “The kindly ethnographer” – Most ethnographers present themselves as being more

sympathetic than they actually are, which aids in the research process, but is also deceptive. The identity that we present to subjects is different from who we are in other circumstances.

“The friendly ethnographer” – Ethnographers operate under the assumption that they should not dislike anyone. In actuality, when hated individuals are found within research, ethnographers often crop them out of the findings.

“The honest ethnographer” – If research participants know the research goals, their responses will likely be skewed. Therefore, ethnographers often conceal what they know in order to increase the likelihood of acceptance.[21]

Technical Skills “The Precise Ethnographer” – Ethnographers often create the illusion that field notes are

data and reflect what “really” happened. They engage in the opposite of plagiarism, giving credit to those undeserving by not using precise words but rather loose interpretations and paraphrasing. Researchers take near-fictions and turn them into claims of fact. The closest ethnographers can ever really get to reality is an approximate truth.

“The Observant Ethnographer” – Readers of ethnography are often led to assume the report of a scene is complete – that little of importance was missed. In reality, an ethnographer will always miss some aspect because they are not omniscient. Everything is open to multiple interpretations and misunderstandings. The ability of the ethnographer to take notes and observe varies, and therefore, what is depicted in ethnography is not the whole picture.

“The Unobtrusive Ethnographer” – As a “participant” in the scene, the researcher will always have an effect on the communication that occurs within the research site. The degree to which one is an “active member” affects the extent to which sympathetic understanding is possible.[22]

The Ethnographic Self “The Candid Ethnographer” – Where the researcher situates themselves within the

ethnography is ethically problematic. There is an illusion that everything reported has actually happened because the researcher has been directly exposed to it.

“The Chaste Ethnographer” – When ethnographers participate within the field, they invariably develop relationships with research subjects/participants. These relationships are sometimes not accounted for within the reporting of the ethnography despite the fact that they seemingly would influence the research findings.

“The Fair Ethnographer” – Fine claims that objectivity is an illusion and that everything in ethnography is known from a perspective. Therefore, it is unethical for a researcher to report fairness in their findings.

“The Literary Ethnographer” – Representation is a balancing act of determining what to “show” through poetic/prosaic language and style versus what to “tell” via straightforward, ‘factual’ reporting. The idiosyncratic skill of the ethnographer influences the face-value of the research.[23]

Seven principles should be considered for observing, recording and sampling data according to Denzin:

1. The groups should combine symbolic meanings with patterns of interaction.2. Observe the world from the point of view of the subject, while maintaining the distinction

between everyday and scientific perceptions of reality.

3. Link the group’s symbols and their meanings with the social relationships.

4. Record all behaviour.

5. Methodology should highlight phases of process, change and stability.

6. The act should be a type of symbolic interactionism.

7. Use concepts that would avoid casual explanations.

Depictions of what could tentatively be called "ethnographic" nudity have appeared both in serious research works on ethnography, ethnology, and anthropology, as well as in commercial documentaries and in the National Geographic magazine in the United States. These depictions are often a cause for controversy, as in some cases, media outlets may show nudity which occurs in a "natural" or spontaneous setting in news programs or documentaries, while blurring out or censoring the nudity in a dramatic work.

The ethnographic focus provided an exceptional framework for painters and photographers to depict peoples whose nudity was, or still is, acceptable within the setting of their traditional culture".

Detractors of ethnographic nudity often dismiss nude portrayal of "natives" as mere colonial gaze preserved as "ethnographic" imagery. On the other hand the works of some ethnographic painters and photographers, like Irving Penn, Casimir Zagourski, Hugo Bernatzik and Leni Riefenstahl are highly valued, having received world-wide acclaim for capturing what is perceived as a documentation of the dying mores of "paradises" subjecty to the onslaught of average modernity.[26]

Participant observation is a type of research strategy. It is a widely used methodology in many disciplines, particularly, cultural anthropology, but also sociology, communication studies, and social psychology. Its aim is to gain a close and intimate familiarity with a given group of individuals (such as a religious, occupational, or sub cultural group, or a particular community) and their practices through an intensive involvement with people in their natural environment, usually over an extended period of time. The method originated in field work of social anthropologists, especially Bronisław Malinowski and his students in Britain, the students of Franz Boas in the United States, and in the urban research of the Chicago School of sociology.

In anthropology, participant-observation is organized so as to produce a kind of writing called ethnography. It can be applied or academic in nature. A key principle of the method is that one may not merely observe, but must find a role within the group observed from which to participate in some manner, even if only as "outside observer." Overt participant-observation,

therefore, is limited to contexts where the community under study understands and permits it. Critics of overt participant observation argue that study is subsequently restricted to the public fronts socially constructed by actors. Gate-keepers ensure that known research never goes backstage, making covert strategies necessary especially when conducting studies on government entities or criminal organisations.

Method and practice

Such research usually involves a range of methods: informal interviews, direct observation, participation in the life of the group, collective discussions, analyses of personal documents produced within the group, self-analysis, and life-histories. Although the method is generally characterized as qualitative research, it can (and often does) include quantitative dimensions. Participant observation is usually undertaken over an extended period of time, ranging from several months to many years. An extended research time period means that the researcher will be able to obtain more detailed and accurate information about the people he/she is studying. Observable details (like daily time allotment) and more hidden details (like taboo behavior) are more easily observed and understandable over a longer period of time. A strength of observation and interaction over long periods of time is that researchers can discover discrepancies between what participants say—and often believe—should happen (the formal system) and what actually does happen, or between different aspects of the formal system; in contrast, a one-time survey of people's answers to a set of questions might be quite consistent, but is less likely to show conflicts between different aspects of the social system or between conscious representations and behavior.

History and development

Participant observation has its roots in anthropology and its use as a methodology can be attributed to Abū Rayhān Bīrūnī (973-1048), a Persian anthropologist who carried out extensive, personal investigations of the peoples, customs and religions of the Indian subcontinent. Like modern anthropologists, he engaged in extensive participant observation with a given group of people, learnt their language and studied their primary texts, and presented his findings with objectivity and neutrality using cross-cultural comparisons.

Participant observation was used extensively by Frank Hamilton Cushing in his study of the Zuni Indians in the later part of the nineteenth century, followed by the studies of non-Western societies by people such as Bronisław Malinowski, Edward Evans-Pritchard,[5] and Margaret Mead [6] in the first half of the twentieth century. It emerged as the principal approach to ethnographic research by anthropologists and relied on the cultivation of personal relationships with local informants as a way of learning about a culture, involving both observing and participating in the social life of a group. By living with the cultures they studied, these researchers were able to formulate first hand accounts of their lives and gain novel insights. This same method of study has also been applied to groups within Western society, and is especially successful in the study of sub-cultures or groups sharing a strong sense of identity, where only by taking part might the observer truly get access to the lives of those being studied. Since the

1980s, some anthropologists and other social scientists have questioned the degree to which participant observation can give veridical insight into the minds of other people. At the same time, a more formalized qualitative research program known as grounded theory, initiated by Glaser and Strauss, began gaining currency within American sociology and related fields such as public health. In response to these challenges, some ethnographers have refined their methods, either making them more amenable to formal hypothesis-testing and replicability, or framing their interpretations within a more carefully considered epistemology.

The development of participant-observation as a research tool has therefore not been a haphazard process, but instead has practiced a great deal of self-criticism and review. It has as a result become specialized. Visual anthropology can be viewed as a subset of methods of participant-observation, as the central questions in that field have to do with how to take a camera into the field, while dealing with such issues as the observer effect. Issues with entry into the field have evolved into a separate subfield. Clifford Geertz's famous essay on how to approach the multi-faceted arena of human action from an observational point of view, in Interpretation of Cultures uses the simple example of a human wink, perceived in a cultural context far from home.

Variations and Related Methods

A variant of participant observation is observing participation, described by Marek M. Kaminski, who explored prison subculture being a political prisoner in communist Poland in 1985. "Observing" or "observant" participation has also been used to describe fieldwork in sexual minority subcultures by anthropologists and sociologists who are themselves lesbian, gay, bisexual, or transgender; the different phrasing is meant to highlight the way in which their partial or full membership in the community/subculture that they are researching both allows a different sort of access to the community and also shapes their perceptions in ways different from a full outsider. This is similar to considerations by anthropologists such as Lila Abu-Lughod on "halfie anthropology", or fieldwork by bicultural anthropologists on a culture to which they partially belong. The sociological methods known as grounded theory (Glaser and Strauss) overlap significantly with the more formalized versions of participant observation.

A focus group is a form of qualitative research in which a group of people are asked about their perceptions, opinions, beliefs and attitudes towards a product, service, concept, advertisement, idea, or packaging. Questions are asked in an interactive group setting where participants are free to talk with other group members.

In marketing

In the world of marketing, focus groups are seen as an important tool for acquiring feedback regarding new products, as well as various topics. In particular, focus groups allow companies wishing to develop, package, name, or test market a new product, to discuss, view, and/or test the new product before it is made available to the public. This can provide invaluable information about the potential market acceptance of the product.

In social sciences

In the social sciences and urban planning, focus groups allow interviewers to study people in a more natural setting than a one-to-one interview. In combination with participant observation, they can be used for gaining access to various cultural and social groups, selecting sites to study, sampling of such sites, and raising unexpected issues for exploration. Focus groups have a high apparent validity - since the idea is easy to understand, the results are believable. Also, they are low in cost, one can get results relatively quickly, and they can increase the sample size of a report by talking with several people at once.[4]

Types of focus groups

Variants of focus groups include:

Two-way focus group - one focus group watches another focus group and discusses the observed interactions and conclusion

Dual moderator focus group - one moderator ensures the session progresses smoothly, while another ensures that all the topics are covered

Dueling moderator focus group - two moderators deliberately take opposite sides on the issue under discussion

Respondent moderator focus group - one or more of the respondents are asked to act as the moderator temporarily

Client participant focus groups - one or more client representatives participate in the discussion, either covertly or overtly

Mini focus groups - groups are composed of four or five members rather than 6 to 12

Teleconference focus groups - telephone network is used

Online focus groups - computers connected via the internet are used

Traditional focus groups can provide accurate information, and are less expensive than other forms of traditional marketing research. There can be significant costs however : if a product is to be marketed on a nationwide basis, it would be critical to gather respondents from various locales throughout the country since attitudes about a new product may vary due to geographical considerations. This would require a considerable expenditure in travel and lodging expenses. Additionally, the site of a traditional focus group may or may not be in a locale convenient to a specific client, so client representatives may have to incur travel and lodging expenses as well.

The use of focus groups has steadily evolved over time and is becoming increasingly widespread.

Benefits/strengths of focus group discussions

Group discussion produces data and insights that would be less accessible without interaction found in a group setting—listening to others’ verbalized experiences stimulates memories, ideas, and experiences in participants. This is also known as the group effect where group members engage in “a kind of ‘chaining’ or ‘cascading’ effect; talk links to, or tumbles out of, the topics and expressions preceding it” (Lindlof & Taylor, 2002, p. 182) [5]

Group members discover a common language to describe similar experiences. This enables the capture of a form of “native language” or “vernacular speech” to understand the situation

Focus groups also provide an opportunity for disclosure among similar others in a setting where participants are validated. For example, in the context of workplace bullying, targeted employees often find themselves in situations where they experience lack of voice and feelings of isolation. Use of focus groups to study workplace bullying therefore serve as both an efficacious and ethical venue for collecting data (see, e.g., Tracy, Lutgen-Sandvik, & Alberts, 2006)

Problems and criticism

However, focus groups also have disadvantages: The researcher has less control over a group than a one-on-one interview, and thus time can be lost on issues irrelevant to the topic; the data is tough to analyze because the talking is in reaction to the comments of other group members; observers/ moderators need to be highly trained, and groups are quite variable and can be tough to get together. (Ibid.) Moreover, the number of members of a focus group is not large enough to be a representative sample of a population; thus, the data obtained from the groups is not necessarily representative of the whole population, unlike the data of opinion polls.

Focus groups are "One shot case studies" especially if they are measuring a property-disposition relationship within the social sciences, unless they are repeated [7]. Focus groups can create severe issues of external validity, especially the reactive effects of the testing arrangement [8]. A fundamental difficulty with focus groups (and other forms of qualitative research) is the issue of observer dependency: the results obtained are influenced by the researcher, raising questions of validity. The issue evokes associations with Heisenberg’s famous Uncertainty Principle. As Heisenberg said, "What we observe is not nature itself, but nature exposed to our method of questioning." Indeed, the design of the focus group study (e.g. respondent selection, the questions asked, how they are phrased, how they are posed, in what setting, by whom, and so on) affects the answers obtained from respondents. In focus groups, researchers (and the moderators and observers of the focus group, if the researcher is not there) are not detached observers but always participants. Researchers must take this into account when making their analysis (Based on: Tjaco H. Walvis (2003), “Avoiding advertising research disaster: Advertising and the uncertainty principle”, Journal of Brand Management, Vol. 10, No. 6, pp. 403-409).

Another issue is with the setting itself. If the focus groups are held in a laboratory setting with a moderator who is a professor and the recording instrument is obtrusive, the participants may either hold back on their responses and/or try to answer the moderator's questions with answers

the participants feel that the moderator wants to hear. Another issue with the focus group setting is the lack of anonymity. With all of the other participants, there can not be any guarantee of confidentiality. Again we have to deal with the issues of the reactive effects of the testing arrangement (See above).

Douglas Rushkoff argues that focus groups are often useless, and frequently cause more trouble than they are intended to solve, with focus groups often aiming to please rather than offering their own opinions or evaluations, and with data often cherry picked to support a foregone conclusion. Rushkoff cites the disastrous introduction of New Coke in the 1980s as a vivid example of focus group analysis gone bad. In addition there is anecdotal evidence of focus groups rebelling, for instance the name for the Ford Focus, was created by a focus group which had grown bored and impatient and the irony of this was not picked up by the marketing team.

Jonathan Ive, Apple’s senior vice president of industrial design, also said that Apple had found a good reason not to do focus groups : "They just ensure that you don’t offend anyone, and produce bland inoffensive products."

The word paradigm (pronounced /ˈpæɹədaɪm/ or /ˈpɛɹədaɪm/; from Greek: παράδειγμα paradeigma meaning pattern, from Greek: paradeiknunai meaning to compare, composite from para- and the verb deiknunai "to show"), has been used in linguistics and science to describe distinct concepts.

Until the 1960s, the word was specific to grammar: the 1900 Merriam-Webster dictionary defines its technical use only in the context of grammar or, in rhetoric, as a term for an illustrative parable or fable. In linguistics, Ferdinand de Saussure used paradigm to refer to a class of elements with similarities.

From the 1960s onward, the word has referred to thought pattern in any scientific discipline or other epistemological context. The Merriam-Webster Online dictionary defines this usage as "a philosophical and theoretical framework of a scientific school or discipline within which theories, laws, and generalizations and the experiments performed in support of them are formulated; broadly : a philosophical or theoretical framework of any kind."[1]

Scientific paradigm

The historian of science Thomas Kuhn gave paradigm its contemporary meaning when he adopted the word to refer to the set of practices that define a scientific discipline at any particular period of time. Kuhn himself came to prefer the terms exemplar and normal science, which have more precise philosophical meanings. However in his book The Structure of Scientific Revolutions Kuhn defines a scientific paradigm as:

what is to be observed and scrutinized

the kind of questions that are supposed to be asked and probed for answers in relation to this subject

how these questions are to be structured

how the results of scientific investigations should be interpreted

Alternatively, the Oxford English Dictionary defines paradigm as "a pattern or model, an exemplar." Thus an additional component of Kuhn's definition of paradigm is:

how is an experiment to be conducted, and what equipment is available to conduct the experiment.

Thus, within normal science, the paradigm is the set of exemplary experiments that are likely to be copied or emulated. In this scientific context, the prevailing paradigm often represents a more specific way of viewing reality, or limitations on acceptable programs for future research, than the more general scientific method.

a currently accepted paradigm would be the standard model of physics. The scientific method would allow for orthodox scientific investigations into phenomena which might contradict or disprove the standard model; however grant funding would be proportionately more difficult to obtain for such experiments, depending on the degree of deviation from the accepted standard model theory which the experiment would be expected to test for. To illustrate the point, an experiment to test for the mass of neutrinos or the decay of protons (small departures from the model) would be more likely to receive money than experiments to look for the violation of the conservation of momentum, or ways to engineer reverse time travel.

One important aspect of Kuhn's paradigms is that the paradigms are incommensurable, meaning two paradigms cannot be reconciled with each other because they cannot be subjected to the same common standard of comparison. That is, no meaningful comparison between them is possible without fundamental modification of the concepts that are an intrinsic part of the paradigms being compared. This way of looking at the concept of "paradigm" creates a paradox of sorts, since competing paradigms are in fact constantly being measured against each other. (Nonetheless, competing paradigms are not fully intelligible solely within the context of their own conceptual frameworks). For this reason, paradigm as a concept in the philosophy of science might more meaningfully be defined as a self-reliant explanatory model or conceptual framework. This definition makes it clear that the real barrier to comparison is not necessarily the absence of common units of measurement, but an absence of mutually compatible or mutually intelligible concepts. Under this system, a new paradigm which replaces an old paradigm is not necessarily better, because the criteria of judgment is controlled by the paradigm itself, and by the conceptual framework which defines the paradigm and gives it its explanatory value.

A more disparaging term groupthink, and the term mindset, have somewhat similar meanings that apply to smaller and larger scale examples of disciplined thought. Michel Foucault used the terms episteme and discourse, mathesis and taxinomia, for aspects of a "paradigm" in Kuhn's original sense.

Simple common analogy: A simplified analogy for paradigm is a habit of reasoning, or "the box" in the commonly used phrase "thinking outside the box". Thinking inside the box is analogous with normal science. The box encompasses the thinking of normal science and thus the box is analogous with paradigm. "Thinking outside the box" would be what Kuhn calls revolutionary science. Revolutionary science is usually unsuccessful, and very rarely leads to new paradigms. However, when they are successful they lead to large scale changes in the scientific worldview.[citation needed] When these large scale shifts in the scientific view are implemented and accepted by the majority, it will then become "the box" and science will progress within it.

Paradigm shifts

Paradigm shifts tend to be most dramatic in sciences that appear to be stable and mature, as in physics at the end of the 19th century. At that time, physicist Lord Kelvin famously stated, "There is nothing new to be discovered in physics now. All that remains is more and more precise measurement." Five years later, Albert Einstein published his paper on special relativity, which challenged the very simple set of rules laid down by Newtonian mechanics, which had been used to describe force and motion for over two hundred years. In this case, the new paradigm reduces the old to a special case in the sense that Newtonian mechanics is still a good model for approximation for speeds that are slow compared to the speed of light. Philosophers and historians of science, including Kuhn himself, ultimately accepted a modified version of Kuhn's model, which synthesizes his original view with the gradualist model that preceded it. Kuhn's original model is now generally seen as too limited.

Kuhn himself did not consider the concept of paradigm as appropriate for the social sciences. He explains in his preface to "The Structure of Scientific Revolutions" that he concocted the concept of paradigm precisely in order to distinguish the social from the natural sciences (p.x). He wrote this book at the Palo Alto Center for Scholars, surrounded by social scientists, when he observed that they were never in agreement on theories or concepts. He explains that he wrote this book precisely to show that there are no, nor can there be any, paradigms in the social sciences. Mattei Dogan, a French sociologist, in his article "Paradigms in the [Social Sciences]," develops Kuhn's original thesis that there are no paradigms at all in the social sciences since the concepts are polysemic, the deliberate mutual ignorance between scholars and the proliferation of schools in these disciplines. Dogan provides many examples of the non-existence of paradigms in the social sciences in his essay, particularly in sociology, political science and political anthropology.

In The Structure of Scientific Revolutions, Kuhn wrote that "Successive transition from one paradigm to another via revolution is the usual developmental pattern of mature science." (p. 12)

Kuhn's idea was itself revolutionary in its time, as it caused a major change in the way that academics talk about science. Thus, it could be argued that it caused or was itself part of a "paradigm shift" in the history and sociology of science. However, Kuhn would not recognize such a paradigm shift. Being in the social sciences, people can still use earlier ideas to discuss the history of science.

Paradigm Paralysis

Perhaps the greatest barrier to a paradigm shift, in some cases, is the reality of paradigm paralysis: the inability or refusal to see beyond the current models of thinking [2]. This is similar to what psychologists term Confirmation bias.

Examples include Galileo's theory of a heliocentric universe, the discovery of electrostatic photography, xerography and the quartz clock.

Other uses

Handa, M.L. (1986) introduced the idea of "social paradigm" in the context of social sciences. He identified the basic components of a social paradigm. Like Kuhn, Handa addressed the issue of changing paradigm; the process popularly known as "paradigm shift". In this respect, he focused on social circumstances that precipitate such a shift and the effects of the shift on social institutions, including the institution of education. This broad shift in the social arena, in turn, changes the way the individual perceives reality.

Another use of the word paradigm is in the sense of Weltanschauung (German for world view). For example, in social science, the term is used to describe the set of experiences, beliefs and values that affect the way an individual perceives reality and responds to that perception. Social scientists have adopted the Kuhnian phrase "paradigm shift" to denote a change in how a given society goes about organizing and understanding reality. A “dominant paradigm” refers to the values, or system of thought, in a society that are most standard and widely held at a given time. Dominant paradigms are shaped both by the community’s cultural background and by the context of the historical moment. The following are conditions that facilitate a system of thought to become an accepted dominant paradigm:

Professional organizations that give legitimacy to the paradigm Dynamic leaders who introduce and purport the paradigm

Journals and editors who write about the system of thought. They both disseminate the information essential to the paradigm and give the paradigm legitimacy

Government agencies who give credence to the paradigm

Educators who propagate the paradigm’s ideas by teaching it to students

Conferences conducted that are devoted to discussing ideas central to the paradigm

Media coverage

Lay groups, or groups based around the concerns of lay persons, that embrace the beliefs central to the paradigm

Sources of funding to further research on the paradigm

The word paradigm is also still used to indicate a pattern or model or an outstandingly clear or typical example or archetype. The term is frequently used in this sense in the design professions. Design Paradigms or archetypes comprise functional precedents for design solutions. The best known references on design paradigms are Design Paradigms: A Sourcebook for Creative Visualization, by Wake, and Design Paradigms by Petroski.

This term is also used in cybernetics. Here it means (in a very wide sense) a (conceptual) protoprogramme for reducing the chaotic mass to some form of order. Note the similarities to the concept of entropy in chemistry and physics. A paradigm there would be a sort of prohibition to proceed with any action that would increase the total entropy of the system. In order to create a paradigm, a closed system which would accept any changes is required. Thus a paradigm can be only applied to a system that is not in its final stage.

Grounded theory (GT) is a systematic qualitative research methodology in the social sciences emphasizing generation of theory from data in the process of conducting research[1].

It is a research method that operates almost in a reverse fashion from traditional research and at first may appear to be in contradiction of the scientific method. Rather than beginning by researching and developing a hypothesis, the first step is data collection, through a variety of methods. From the data collected, the key points are marked with a series of codes, which are extracted from the text. The codes are grouped into similar concepts in order to make them more workable. From these concepts, categories are formed, which are the basis for the creation of a theory, or a reverse engineered hypothesis. This contradicts the traditional model of research, where the researcher chooses a theoretical framework, and only then applies this model to the studied phenomenon[2].

Four Stages of Analysis

Stage Purpose

Codes Identifying anchors that allow the key points of the data to be gathered

Concepts Collections of codes of similar content that allows the data to be grouped

Categories Broad groups of similar concepts that are used to generate a theory

Theory A collection of explanations that explain the subject of the research

Development

Grounded theory was developed by two sociologists, Barney Glaser and Anselm Strauss. Their collaboration in research on dying hospital patients led them to write the book Awareness of Dying. In this research they developed the constant comparative method later known as Grounded Theory; see The Discovery of Grounded Theory (Glaser & Strauss, 1967)

Split in methodology

Since their original publication in 1967, Glaser and Strauss have disagreed on 'how to do' GT, resulting in a split in the theory between Glaserian and Straussian paradigms. This split occurred most obviously after Strauss published Qualitative Analysis for Social Scientists (1987). Thereafter Strauss in 1990 published Basics of Qualitative Research: Grounded Theory Procedures and Techniques together with Juliet Corbin. This was followed by a rebuke by Glaser (1992) who set out, chapter by chapter, to highlight the differences in what he argued was original grounded theory and why, according to Glaser, what Strauss had written was not grounded theory in its intended form. This divergence in the GT methodology is a subject of much academic debate, which Glaser (1998) calls a "rhetorical wrestle".

According to Kelle (2005), "the controversy between Glaser and Strauss boils down to the question of whether the researcher uses a well defined 'coding paradigm' and always looks systematically for 'causal conditions,' 'phenomena/context, intervening conditions, action strategies' and 'consequences' in the data, or whether theoretical codes are employed as they emerge in the same way as substantive codes emerge, but drawing on a huge fund of 'coding families.' Both strategies have their pros and cons. Novices who wish to get clear advice on how to structure data material may be satisfied with the use of the coding paradigm. Since the paradigm consists of theoretical terms which carry only limited empirical content the risk is not very high that data are forced by its application. However, it must not be forgotten that it is linked to a certain micro-sociological perspective. Many researchers may concur with that approach especially since qualitative research always had a relation to micro-sociological action theory, but others who want to employ a macro-sociological and system theory perspective may feel that the use of the coding paradigm would lead them astray." [3]

The Glaserian strategy is not a qualitative research method, but claims the dictum "all is data". This means that not only interview or observational data but also surveys or statistical analyses or "whatever comes the researcher's way while studying a substantive area" (Glaser quote) can be used in the comparative process as well as literature data from science or media or even fiction. Thus the method according to Glaser is not limited to the realm of qualitative research, which he calls "QDA" (Qualitative Data Analysis). QDA is devoted to descriptive accuracy while the Glaserian method emphasizes conceptualization abstract of time, place and people. A grounded theory concept should be easy to use outside of the substantive area where it was generated.

Glaser

Most chapters in the first GT methodology "The Discovery of Grounded Theory" (6995 Google Scholar citations May 2007) (Glaser & Strauss, 1967) were written by Glaser, trained in methodology generation. Glaser alone wrote the second methodology "Theoretical Sensitivity" (Glaser, 1978) and has since written five more books on the method and edited five readers with a collection of GT articles and dissertations (see Literature at end). The Grounded Theory

Review is a peer-reviewed journal publishing grounded theories and articles on different aspects of doing GT.

Strauss and Juliet Corbin (Strauss & Corbin 1990) took GT in a different direction from what Glaser had outlined in Theoretical Sensitivity and the 1967 book. There was a clash of ideas between the discoverers and Glaser in 1992 wrote a book arguing against the Strauss & Corbin book chapter by chapter.

Hence GT was divided into Strauss & Corbin’s method, see grounded theory (Strauss) and Glaser’s GT with the original ideas from 1967 and 1978 still in operation. The following article deals with GT according to Glaser.

Goals of grounded theory

GT is a systematic generation of theory from data that contains both inductive and deductive thinking. One goal of a GT is to formulate hypotheses based on conceptual ideas. Others may try to verify the hypotheses that are generated by constantly comparing conceptualized data on different levels of abstraction, and these comparisons contain deductive steps. Another goal of a GT is to discover the participants’ main concern and how they continually try to resolve it. The questions you keep on asking in GT are "What’s going on?" and "What is the main problem of the participants and how are they trying to solve it?" These questions will be answered by the core variable and its subcores and properties in due course (see below). GT does not aim for the "truth" but to conceptualize what's going on by using empirical data. In a way GT resembles what many researchers do when retrospectively formulating new hypotheses to fit data. However, in GT the researcher does not pretend to have formulated the hypotheses in advance since preformed hypotheses are prohibited (Glaser & Strauss 1967).

If your research goal is accurate description, then another method should be chosen since GT is not a descriptive method. Instead it has the goal of generating concepts that explain people’s actions regardless of time and place. The descriptive parts of a GT are there mainly to illustrate the concepts.

In most behavioral research endeavors persons or patients are units of analysis, whereas in GT the unit of analysis is the incident (Glaser & Strauss 1967). There are normally at least several hundred incidents analyzed in a GT study since every participant normally reports many incidents. When comparing many incidents in a certain area, the emerging concepts and their relationships are in reality probability statements. Consequently, GT is not a qualitative method but a general method that can use any kind of data even if qualitative at the moment are most popular (Glaser, 2001, 2003). However, although working with probabilities, most GT studies are considered as qualitative since statistical methods are not used, and figures not presented. The results of GT are not a reporting of facts but a set of probability statements about the relationship between concepts, or an integrated set of conceptual hypotheses developed from empirical data (Glaser 1998). Validity in its traditional sense is consequently not an issue in GT, which instead should be judged by fit, relevance, workability, and modifiability (Glaser & Strauss 1967, Glaser 1978, Glaser 1998).

Fit has to do with how closely concepts fit with the incidents they are representing, and this is related to how thoroughly the constant comparison of incidents to concepts was done.

Relevance. A relevant study deals with the real concern of participants, evokes "grab" (captures the attention) and is not only of academic interest.

Workability. The theory works when it explains how the problem is being solved with much variation.

Modifiability. A modifiable theory can be altered when new relevant data is compared to existing data. A GT is never right or wrong, it just has more or less fit, relevance, workability and modifiability.

GT nomenclature

A concept is the overall element and includes the categories which are conceptual elements standing by themselves, and properties of categories, which are conceptual aspects of categories (Glaser & Strauss, 1967). The core variable explains most of the participants’ main concern with as much variation as possible. It has the most powerful properties to picture what’s going on, but with as few properties as possible needed to do so. A popular type of core variable can be theoretically modeled as a basic social process that accounts for most of the variation in change over time, context, and behavior in the studied area. "GT is multivariate. It happens sequentially, subsequently, simultaneously, serendipitously, and scheduled" (Glaser, 1998).

All is data is a fundamental property of GT which means that everything that gets in the researcher’s way when studying a certain area is data. Not only interviews or observations but anything is data that helps the researcher generating concepts for the emerging theory. Field notes can come from informal interviews, lectures, seminars, expert group meetings, newspaper articles, Internet mail lists, even television shows, conversations with friends etc. It is even possible, and sometimes a good idea, for a researcher with much knowledge in the studied area to interview herself, treating that interview like any other data, coding and comparing it to other data and generating concepts from it. This may sound silly since you don’t have to interview yourself to know what you know, but you don’t know it on the conceptual level! And GT deals with conceptual level data.

Open coding or substantive coding is conceptualizing on the first level of abstraction. Written data from field notes or transcripts are conceptualized line by line. In the beginning of a study everything is coded in order to find out about the problem and how it is being resolved. The coding is often done in the margin of the field notes. This phase is often tedious since you are conceptualizing all incidents in the data, which yields many concepts. These are compared as you code more data, and merged into new concepts, and eventually renamed and modified. The GT researcher goes back and forth while comparing data, constantly modifying, and sharpening the growing theory at the same time as she follows the build-up schedule of GT’s different steps.

Selective coding is done after having found the core variable or what is thought to be the core, the tentative core. The core explains the behavior of the participants in resolving their main

concern. The tentative core is never wrong. It just more or less fits with the data. After having chosen your core variable you selectively code data with the core guiding your coding, not bothering about concepts with little importance to the core and its subcores. Also, you now selectively sample new data with the core in mind, which is called theoretical sampling – a deductive part of GT. Selective coding delimits the study, which makes it move fast. This is indeed encouraged while doing GT (Glaser, 1998) since GT is not concerned with data accuracy as in descriptive research but is about generating concepts that are abstract of time, place and people. Selective coding could be done by going over old field notes or memos which are already coded once at an earlier stage or by coding newly gathered data.

Theoretical codes integrate the theory by weaving the fractured concepts into hypotheses that work together in a theory explaining the main concern of the participants. Theoretical coding means that the researcher applies a theoretical model to the data. It is important that this model is not forced beforehand but has emerged during the comparative process of GT. So the theoretical codes just as substantives codes should emerge from the process of constantly comparing the data in field notes and memos.

Memoing

Theoretical memoing is "the core stage of grounded theory methodology" (Glaser 1998). "Memos are the theorizing write-up of ideas about substantive codes and their theoretically coded relationships as they emerge during coding, collecting and analyzing data, and during memoing" (Glaser 1998).

Memoing is also important in the early phase of a GT study such as open coding. The researcher is then conceptualizing incidents, and memoing helps this process. Theoretical memos can be anything written or drawn in the constant comparison that makes up a GT. Memos are important tools to both refine and keep track of ideas that develop when you compare incidents to incidents and then concepts to concepts in the evolving theory. In memos you develop ideas about naming concepts and relating them to each other. In memos you try the relationships between concepts in two-by-two tables, in diagrams or figures or whatever makes the ideas flow, and generates comparative power. Without memoing the theory is superficial and the concepts generated not very original. Memoing works as an accumulation of written ideas into a bank of ideas about concepts and how they relate to each other. This bank contains rich parts of what will later be the written theory. Memoing is total creative freedom without rules of writing, grammar or style (Glaser 1998). The writing must be an instrument for outflow of ideas, and nothing else. When you write memos the ideas become more realistic, being converted from thoughts in your mind to words, and thus ideas communicable to the afterworld. In GT the preconscious processing that occurs when coding and comparing is recognized. The researcher is encouraged to register ideas about the ongoing study that eventually pop up in everyday situations, and awareness of the serendipity of the method is also necessary to achieve good results.

Sorting

In the next step memos are sorted, which is the key to formulate the theory for presentation to others. Sorting puts fractured data back together. During sorting lots of new ideas emerge, which

in turn are recorded in new memos giving the memo-on-memos phenomenon. Sorting memos generates theory that explains the main action in the studied area. A theory written from unsorted memos may be rich in ideas but the connection between concepts is weak.

Writing

Writing up the sorted memo piles follows after sorting, and at this stage the theory is close to the written GT product. The different categories are now related to each other and the core variable. The theoretical density should be dosed so concepts are mixed with description in words, tables, or figures to optimize readability. In the later rewriting the relevant literature is woven in to put the theory in a scholarly context. Finally, the GT is edited for style and language and eventually submitted for publication.

No pre-research literature review, no taping and no talk

GT according to Glaser gives the researcher freedom to generate new concepts explaining human behavior. This freedom is optimal when the researcher refrains from taping interviews, doing a pre research literature review, and talking about the research before it is written up. These rules makes GT different from most other methods using qualitative data.

No pre-research literature review. Studying the literature of the area under study gives preconceptions about what to find and the researcher gets desensitized by borrowed concepts. Instead, grounded theories in other areas, and GT method books increase theoretical sensitivity. The literature should instead be read in the sorting stage being treated as more data to code and compare with what has already been coded and generated.

No taping. Taping and transcribing interviews is common in qualitative research, but is counterproductive and a waste of time in GT which moves fast when the researcher delimits her data by field-noting interviews and soon after generates concepts that fit with data, are relevant and work in explaining what participants are doing to resolve their main concern.

No talk. Talking about the theory before it is written up drains the researcher of motivational energy. Talking can either render praise or criticism, and both diminish the motivational drive to write memos that develop and refine the concepts and the theory (Glaser 1998). Positive feedback makes you content with what you've got and negative feedback hampers your self-confidence. Talking about the GT should be restricted to persons capable of helping the researcher without influencing her final judgments.

The Grounded Theory Institute

Glaser founded the Grounded Theory Institute in 1999 as a non-profit web-based organization (www.groundedtheory.com), which describes itself on its webpage as "dedicated to the evolving methodology of Dr.Barney G. Glaser, Ph.D.". The Institute provides an online forum for the discussion of grounded theory, and publishes the journal, "The Grounded Theory Review." The Institute also includes the Sociology Press, which Dr. Glaser founded in 1970.

Strauss

Generally speaking, grounded theory is an approach for looking systematically at (mostly) qualitative data (like transcripts of interviews or protocols of observations) aiming at the generation of theory. Sometimes, grounded theory is seen as a qualitative method, but grounded theory reaches farther: it combines a specific style of research (or a paradigm) with pragmatic theory of action and with some methodological guidelines.

This approach was written down and systematized in the 1960s by Anselm Strauss (himself a student of Herbert Blumer) and Barney Glaser (a student of Paul Lazarsfeld), while working together in studying the sociology of illness at the University of California, San Francisco. For and with their studies, they developed a methodology, which was then made explicit and became the foundation stone for an important branch of qualitative sociology.

Important concepts of grounded theory are categories, codes and codings. The research principle behind grounded theory is neither inductive nor deductive, but combines both in a way of abductive reasoning (coming from the works of Charles Sanders Peirce). This leads to a research practice where data sampling, data analysis and theory development are not seen as distinct and disjunct, but as different steps to be repeated until one can describe and explain the phenomenon that is to be researched. This stopping point is reached when new data does not change the emerging theory anymore.

Differences

Grounded theory according to Glaser emphasizes induction or emergence, and the individual researcher's creativity within a clear frame of stages, while Strauss is more interested in validation criteria and a systematic approach. This methodical way of creating grounded theory (and still be acceptable to scientific standards) is explained in Strauss and Corbin (1990).

In an interview that was conducted shortly before Strauss' death, he named three basic elements every grounded theory approach should include (Legewie/Schervier-Legewie (2004)). These three elements are:

Theoretical sensitive coding, that is, generating theoretical strong concepts from the data to explain the phenomenon researched;

theoretical sampling, that is, deciding whom to interview or what to observe next according to the state of theory generation, and that implies to start data analysis with the first interview, and write down memos and hypotheses early;

the need to compare between phenomena and contexts to make the theory strong.

Criticism

Critiques of grounded theory have focused on its status as theory (is what is produced really 'theory'?), on the notion of 'ground' (why is an idea of 'grounding' one's findings important in qualitative inquiry -- what are they 'grounded' in?) and on the claim to use and develop inductive knowledge. These criticisms are summed up by Thomas and James. [4] These authors also suggest

that it is impossible to free oneself of preconceptions in the collection and analysis of data in the way that Glaser and Strauss say is necessary. They also point to the formulaic nature of grounded theory and the lack of congruence of this with open and creative interpretation - which ought to be the hallmark of qualitative inquiry. They suggest that the one element of grounded theory worth keeping is constant comparative method.

Grounded theory was developed in a period when other qualitative methods were often considered not scientific and became the main qualitative method accepted as academic enough. Thus, especially in American academia qualitative research is often equated to grounded theory. This is criticized by qualitative researchers using other methodologies (such as traditional ethnography, narratology, storytelling, etc.).

Hermeneutics (English pronunciation: /hɜrməˈnjuːtɨks/) is the study of interpretation theory, and can be either the art of interpretation, or the theory and practice of interpretation. Traditional hermeneutics — which includes Biblical hermeneutics — refers to the study of the interpretation of written texts, especially texts in the areas of literature, religion and law. Contemporary, or modern, hermeneutics encompasses not only issues involving the written text, but everything in the interpretative process. This includes verbal and nonverbal forms of communication as well as prior aspects that affect communication, such as presuppositions, preunderstandings, the meaning and philosophy of language, and semiotics.[1] Philosophical hermeneutics refers primarily to Hans-Georg Gadamer's theory of knowledge as developed in Truth and Method, and sometimes to Paul Ricoeur.[2] Hermeneutic consistency refers to analysis of texts for coherent explanation. A hermeneutic (singular) refers to one particular method or strand of interpretation. See also double hermeneutic.

Etymology

The folk etymology places the origin of the word Hermeneutics (Greek: hermeneutike) with Hermes, the mythological Greek deity whose role is that of messenger of the Gods. Besides being mediator between the gods themselves and god and humanity, he leads souls to the underworld upon death, is the inventor of language and speech, interpreter, a liar, thief and trickster.[4] These multiple roles makes Hermes an ideal representative of Hermeneutics, For, as Socrates notes, words have the power to reveal or conceal, thus promoting the message in an ambiguous way.[5] The Greek view of language as consisting of signs that could lead to truth or falsehood is the very essence of Hermes, who is said to relish the uneasiness of the messaged.

Early use of the word Hermeneutics places it within the boundaries of the sacred. The divine message is one only understood on its own terms with uncertainty regarding its truth or falsehood. This ambiguity of message is an irrationality, a sort of madness inflicted upon the receiver. Only one who possesses a rational method of interpretation—an early hermeneutic—could divine the truth or falsehood (thus the sanity) of a statement.

The traditional etymology of Hermeneutics is derived from the Greek word ἑρμηνεύω (hermeneuō, 'translate' or 'interpret'), and is of uncertain origin. It was introduced into philosophy

mainly through the title of Aristotle's work Περὶ Ἑρμηνείας (Peri Hermeneias, 'On Interpretation', more commonly referred by its Latin title De Interpretatione). It is one of the earliest (c.360 BC) extant philosophical works in the Western tradition to deal with the relationship between language and logic in a comprehensive, explicit, and formal way.

History

Aristotle strikes a chord in his treatise De Interpretatione that reverberates through the intervening ages and supplies the key note for many contemporary theories of interpretation. His overture is here:

Words spoken are symbols or signs (symbola) of affections or impressions (pathemata) of the soul (psyche); written words are the signs of words spoken.

As writing, so also is speech not the same for all races of men.

But the mental affections themselves, of which these words are primarily signs (semeia), are the same for the whole of mankind, as are also the objects (pragmata) of which those affections are representations or likenesses, images, copies (homoiomata).

—Aristotle , On Interpretation, 1.16a4

Equally important to later developments are texts on poetry, rhetoric, and sophistry, including many of Plato's dialogues, such as Cratylus, Ion, Gorgias, Lesser Hippias, and Republic, along with Aristotle's Poetics, Rhetoric, and On Sophistical Refutations. However, these texts deal more with the presentation and refutation of arguments, speeches and poems rather than the understanding of texts as texts. As Ramberg and Gjesdal note, "Only with the Stoics, and their reflections on the interpretation of myth, do we encounter something like a methodological awareness of the problems of textual understanding." [9]

Some ancient Greek philosophers, particularly Plato, tended to vilify poets and poetry as harmful nonsense—Plato denies entry to poets in his ideal state in The Republic until they can prove their value. In the Ion, Plato famously portrays poets as possessed:

You know, none of the epic poets, if they're good, are masters of their subject; they are inspired, possessed, and that is how they utter all those beautiful poems. The same goes for lyric poets if they're good: just as the Corybantes are not in their right minds when they dance, lyric poets, too, are not in their right minds when they make those beautiful lyrics, but as soon as they sail into harmony and rhythm they are possessed by Bacchic frenzy.

—Plato , Ion, 533e-534a

The meaning of the poem thus becomes open to ridicule — whatever hints of the truth it may have, the truth is covered by madness. However, another line of thinking arose with Theagenes of Rhegium, who suggested that instead of taking poetry literally, what was expressed in poems were allegories of nature. Stoic philosophers further developed this idea, reading into the poets not only allegories of natural phenomena, but allegories of ethical behavior.

Aristotle differed with his predecessor, Plato, in the worth of poetry. Both saw art as an act of mimesis, but where Plato saw a pale, essentially false imitation in art of reality, Aristotle saw the possibility of truth in imitation. As critic David Richter points out, "for Aristotle, artists must disregard incidental facts to search for deeper universal truths"—instead of being essentially false, poetry may be universally true. (Richter, The Critical Tradition, 57.) In the Poetics, Aristotle called both the tragedy and the epic noble, with tragedy serving the essential function of purging strong emotions from the audience through katharsis.

A common use of the word hermeneutics refers to a process of scriptural interpretation. Its earliest example is however found not in the written texts, but in the Jewish Oral Tradition dated to the Second Temple era (515 BCE - 70 CE) that later became the Talmud.

Summaries of the principles by which Torah can be interpreted date back at least to Hillel the Elder, although the thirteen principles set forth in the Baraita of Rabbi Ishmael are perhaps the best known. These principles ranged from standard rules of logic (e.g., a fortiori argument (known in Hebrew as to more expansive ones, like the rule that a ,(((kal v'chomer) קל וחומר passage could be interpreted by reference to another passage in which the same word appears (Gezerah Shavah). The rabbis did not ascribe equal persuasive power to the various principles.[10]

Traditional Jewish hermeneutics differ from the Greek method in that the rabbis considered the Tanakh (the Jewish bibilical canon) to be without error. Any apparent inconsistencies needed to be understood by careful examination of a given text in the context of other texts. There were different levels of interpretation, some used to arrive at the plain meaning of the text, some that expounded the law given in the text, and others that found secret or mystical levels of understanding.

Critical theory

Jürgen Habermas criticized the conservatism of previous hermeneutics, especially Gadamer, because the focus on tradition seemed to undermine possibilities for social criticism and transformation. Habermas also criticized Marxism and previous members of the Frankfurt School for missing the hermeneutical dimension of critical theory. Habermas incorporated the notion of the lifeworld and emphasized the importance of both interaction and communication as well as labor and production for social theory. For Habermas, hermeneutics is one dimension of critical social theory.

Application

Archaeology

In archaeology, hermeneutics means the interpretation and understanding of material by analysing possible meanings or social use. Proponents argue that interpretation of artifacts is unavoidably hermeneutic as we cannot know for certain the meaning behind them, instead we can only apply modern value in the interpretation. This is most common in stone tools, for

example, where using descriptions such as "scraper" can be highly subjective and unproven. Opponents claim that a hermeneutic approach is too relativist and that their own interpretations are based on common-sense evaluation.

Architecture

Though the interpretation of buildings is clearly of abiding interest, there are several traditions of architectural scholarship that draw explicitly on the hermeneutics of Heidegger and Gadamer. Of note is the work of Lindsay Jones[18] on the way architecture is received and how that reception changes over time and according to context, ie how a building is interpreted by critics, users, historians, etc. Dalibor Vesely situates hermeneutics within a critique of the application of overly-scientific thinking to architecture.[19] This tradition fits within a critique of the Enlightenment,[20] but it has also informed design studio teaching. Snodgrass values historical study and the study of Asian cultures by architects as hermeneutical encounters with otherness [21]. He also deploys arguments from hermeneutics to explain design as a process of interpretation[22]. With Richard Coyne he extends the argument to a consideration of the nature of architectural education and design as a way of thinking.[23] The latter also expands to a consideration of the use of computers in design.[24]. Alberto Perez-Gomez is also well known for his application of phenomenology and hermeneutics to architectural history.

International relations

Insofar as hermeneutics is a cornerstone of both critical theory and constitutive theory, both of which have made important inroads into the postpositivist branch of international relations theory and political science, hermeneutics has been applied to international relations (IR). Steve Smith (Academic) refers to hermeneutics as the principal way of grounding a foundationalist yet postpositivist IR theory such as critical theory. An example of a postpositivist yet anti-foundationalist IR paradigm would be radical postmodernism.

LawMain article: Jurisprudence

Some scholars argue that law and theology constitute particular forms of hermeneutics because of their need to interpret legal tradition / scriptural texts. Moreover, the problem of interpretation is central to legal theory at least since the 11th century. In the Middle Ages and Renaissance, the schools of glossatores, commentatores and usus modernus distinguished themselves by their approach to the interpretation of "laws" (mainly, Justinian's Corpus Iuris Civilis). The University of Bologna gave birth to a "legal Renaissance" in the 11th century, when the Corpus Iuris Civilis was rediscovered and started to be systematically studied by people like Irnerius and Gratianus. It was an interpretative Renaissance. After that, interpretation has always been at the center of legal thought. Savigny and Betti, among others, made significant contributions also to general hermeneutics. Legal interpretivism, most famously Ronald Dworkin's, might be seen as a branch of philosophical hermeneutics.

PsychologySee also: Postcognitivism

Similar to the situation in computer science, psychologists have recently become interested in hermeneutics, especially those interested in alternatives to Cognitivism. Hubert Dreyfus's critique of conventional artificial intelligence has been influential not only in AI but in psychology, and psychologists are increasingly interested in hermeneutic approaches to meaning and interpretation as discussed by philosophers such as Heidegger (cf Embodied cognition) and the later Wittgenstein (cf discursive psychology). Hermeneutics is also influential in Humanistic Psychology [25]

Religion and theologySee also: Biblical hermeneutics, Qur'anic hermeneutics, Talmudical hermeneutics, and Exegesis

The process by which theological texts are understood relies on a particular hermeneutical viewpoint. Theorists like Paul Ricoeur have applied modern philosophical hermeneutics to theological texts (in Ricoeur's case, the Bible).

Safety science

In the field of Safety Science, especially the study of Human Error, scientists have become increasingly interested in hermeneutic approaches. It has been proposed by the ergonomist Donald Taylor that mechanist models of human behaviour will only take us so far in terms of accident reduction, and that safety science must now begin to look at the meaning of accidents for conscious human beings.[26] Other scholars in the field have attempted to create safety taxonomies that make use of hermeneutic concepts, in terms of their categorisation of qualitative data.[27]

Sociology

In sociology, hermeneutics means the interpretation and understanding of social events by analysing their meanings to the human participants and their culture. It enjoyed prominence during the sixties and seventies, and differs from other interpretative schools of sociology in that it emphasizes the importance of the context[28] as well as the form of any given social behaviour. The central principle of hermeneutics is that it is only possible to grasp the meaning of an action or statement by relating it to the whole discourse or world-view from which it originates: for instance, putting a piece of paper in a box might be considered a meaningless action unless put in the context of democratic elections, and the action of putting a ballot paper in a box. One can frequently find reference to the 'hermeneutic circle': that is, relating the whole to the part and the part to the whole. Hermeneutics in sociology was most heavily influenced by German philosopher Hans-Georg Gadamer [29].

The field of marketing has adopted this term from sociology, using the term to refer to qualitative studies in which interviews with (or other forms of text from) one or a small number of people are closely read, analyzed, and interpreted.

Phenomenography is a qualitative research methodology, within the interpretivist paradigm, that investigates the qualitatively different ways in which people experience something or think about something (Ference Marton, 1986). Phenomenography, an approach to educational

research that appeared in publications in the early 1980s (Marton, 1981; 1986), initially emerged from an empirical rather than theoretical or philosophical basis (Åkerlind, 2005).

Phenomenography's ontological assumptions are subjectivist: The world exists and different people construe it in different ways; and with a non-dualist viewpoint: There is only one world, one that is ours, and one that people experience in many different ways (Bowden, 2005; Marton & Booth, 1997). Phenomenography's research object has the character of knowledge; therefore the ontological assumptions also become the epistemological assumptions (Svensson, 1997), or, to put that another way, the epistemological position is represented by the ontological position (Uljens, 1996). The emphasis is on description, implying an assumption about the importance of and the need for description. The importance is related to an understanding of knowledge as a matter of meaning and similarities and differences in meaning (Svensson, 1997). Starting with a description follows from the assumption that, in the case of conceptions, these form both the results of and conditions for human activity, and clarification is dependent upon focusing on the meaning of the conceptions themselves (Svensson, 1997). The object of study is not the phenomenon per se, but the relationships between the actors and the phenomenon (Bowden, 2005).

A phenomenographic analysis seeks a "description, analysis, and understanding of ... experiences" (Marton, 1981, p. 180). The focus is on variation: variation in both the perceptions of the phenomenon as experienced by the actor, and in the "ways of seeing something" as experienced and described by the researcher (Pang, 1999:1). This is described as phenomenography's "theory of variation" (Pang, 1999:1). Phenomenography allows the researcher to use their own experiences as data for phenomenographic analysis (Roger Säljö, 1996; Uljens, 1996). Phenomenography aims for a collective analysis of individual experiences (Åkerlind, 2005).

Phenomenography is not phenomenology. Both phenomenography and phenomenology have human experience as its object; however, phenomenology is a philosophical method, with the philosopher engaged in investigating their own experience (Marton & Booth, 1997). Phenomenographers, on the other hand, adopt an empirical orientation, and then investigate the experience of others (Marton & Booth, 1997). The focus of interpretive phenomenology is the essence of the phenomenon, whereas the focus of phenomenography is the essence of the experiences and subsequent perceptions of the phenomenon (Hitchcock, 2006). Data collection methods typically include close interviews with a small, purposive sample with the researcher "working toward an articulation of the interviewee’s reflections on experience that is as complete as possible" (Marton & Booth, 1997:130).

A phenomenographic data analysis sorts these perceptions, which emerge from the data collected, into specific 'categories of description' (Åkerlind, 2005; Marton, 1981; 1986; Uljens, 1996). The set of categories of description is sometimes referred to as an 'outcome space'. These categories (and the underlying structure) become the phenomenographic essence of the phenomenon (Uljens, 1996). They are the primary outcomes, and the most important result of phenomenographic research (Marton, 1986). Phenomenographic categories are logically related to one another, typically by way of hierarchically inclusive relationships (Marton, 1986; Marton & Booth, 1997) although linear and branched relationships can also occur (Åkerlind, 2005). That

which varies between different categories of description is known as the 'dimensions of variation'. The process of phenomenographic analysis is strongly iterative and comparative and involves the continual sorting and resorting of data and ongoing comparisons between data and the developing categories of description, as well as between the categories themselves (Åkerlind 2005).

A case study is one of several ways of doing research whether it is social science related or even socially related. It is an in-depth investigation/study of a single individual, group, incident, or community.[1] Other ways include experiments, surveys, or analysis of archival information [2].

Rather than using samples and following a rigid protocol to examine limited number of variables, case study methods involve an in-depth, longitudinal examination of a single instance or event: a case. They provide a systematic way of looking at events, collecting data, analyzing information, and reporting the results. As a result the researcher may gain a sharpened understanding of why the instance happened as it did, and what might become important to look at more extensively in future research. Case studies lend themselves to both generating and testing hypotheses [3].

Another suggestion is that case study should be defined as a research strategy, an empirical inquiry that investigates a phenomenon within its real-life context. Case study research means single and multiple case studies, can include quantitative evidence, relies on multiple sources of evidence and benefits from the prior development of theoretical propositions. Case studies should not be confused with qualitative research and they can be based on any mix of quantitative and qualitative evidence. Single-subject research provides the statistical framework for making inferences from quantitative case-study data.[2][4] This is also supported and well-formulated in (Lamnek, 2005): "The case study is a research approach, situated between concrete data taking techniques and methodologic paradigms."

Case selection

Yin (2005) suggested that researchers should decide whether to do single-case or multiple-case studies and chose to keep the case holistic or have embedded sub-cases. This two-by-two combination can produce four basic designs for case studies.

When selecting a case for a case study, researchers often use information-oriented sampling , as opposed to random sampling [3]. This is because an average case is often not the richest in information. Extreme or atypical cases reveal more information because they activate more basic mechanisms and more actors in the situation studied. In addition, from both an understanding-oriented and an action-oriented perspective, it is often more important to clarify the deeper causes behind a given problem and its consequences than to describe the symptoms of the problem and how frequently they occur. Random samples emphasizing representativeness will seldom be able to produce this kind of insight; it is more appropriate to select some few cases chosen for their validity. But this isnt always the case.

Three types of information-oriented cases may be distinguished:

1. Extreme or deviant cases2. Critical cases

3. Paradigmatic cases.

Critical case

A critical case can be defined as having strategic importance in relation to the general problem. For example, an occupational medicine clinic wanted to investigate whether people working with organic solvents suffered brain damage. Instead of choosing a representative sample among all those enterprises in the clinic’s area that used organic solvents, the clinic strategically located , ‘If it is valid for this case, it is valid for all (or many) cases.’ In its negative form, the generalization would be, ‘If it is not valid for this case, then it is not valid for any (or only few) cases.’

For more on case selection, see [1]

Generalizing from case studies

The case study is effective for generalizing using the type of test that Karl Popper called falsification, which forms part of critical reflexivity [3]. Falsification is one of the most rigorous tests to which a scientific proposition can be subjected: if just one observation does not fit with the proposition it is considered not valid generally and must therefore be either revised or rejected. Popper himself used the now famous example of, "All swans are white," and proposed that just one observation of a single black swan would falsify this proposition and in this way have general significance and stimulate further investigations and theory-building. The case study is well suited for identifying "black swans" because of its in-depth approach: what appears to be "white" often turns out on closer examination to be "black."

For instance, Galileo Galilei’s rejection of Aristotle’s law of gravity was based on a case study selected by information-oriented sampling and not random sampling. The rejection consisted primarily of a conceptual experiment and later on of a practical one. These experiments, with the benefit of hindsight, are self-evident. Nevertheless, Aristotle’s incorrect view of gravity dominated scientific inquiry for nearly two thousand years before it was falsified. In his experimental thinking, Galileo reasoned as follows: if two objects with the same weight are released from the same height at the same time, they will hit the ground simultaneously, having fallen at the same speed. If the two objects are then stuck together into one, this object will have double the weight and will according to the Aristotelian view therefore fall faster than the two individual objects. This conclusion seemed contradictory to Galileo. The only way to avoid the contradiction was to eliminate weight as a determinant factor for acceleration in free fall. Galileo’s experimentalism did not involve a large random sample of trials of objects falling from a wide range of randomly selected heights under varying wind conditions, and so on. Rather, it was a matter of a single experiment, that is, a case study.(Flyvbjerg, 2006, p. 225-6) [2]

Galileo’s view continued to be subjected to doubt, however, and the Aristotelian view was not finally rejected until half a century later, with the invention of the air pump. The air pump made it possible to conduct the ultimate experiment, known by every pupil, whereby a coin or a piece of lead inside a vacuum tube falls with the same speed as a feather. After this experiment, Aristotle’s view could be maintained no longer. What is especially worth noting, however, is that the matter was settled by an individual case due to the clever choice of the extremes of metal and feather. One might call it a critical case, for if Galileo’s thesis held for these materials, it could be expected to be valid for all or a large range of materials. Random and large samples were at no time part of the picture. However it was Galileo's view that was the subject of doubt as it was not reasonable enough to be the Aristotelian view. By selecting cases strategically in this manner one may arrive at case studies that allow generalization.(Flyvbjerg, 2006, p. 225-6) For more on generalizing from case studies, see [3]

Assumptions

1. Cases selected based on dimensions of a theory (pattern-matching) or on diversity on a dependent phenomenon (explanation-building).

2. No generalization to a population beyond cases similar to those studied.

3. Conclusions should be phrased in terms of model elimination, not model validation. Numerous alternative theories may be consistent with data gathered from a case study.

4. Case study approaches have difficulty in terms of evaluation of low-probability causal paths in a model as any given case selected for study may fail to display such a path, even when it exists in the larger population of potential cases.

History of the case study

As a distinct approach to research, use of the case study originated only in the early 20th century. The Oxford English Dictionary traces the phrase case study or case-study back as far as 1934, influenced by the much older concept of a case history in medicine.[citation needed]

The use of case studies for the creation of new theory in social sciences has been further developed by the sociologists Barney Glaser and Anselm Strauss who presented their research method, Grounded theory, in 1967.

The popularity of case studies in testing hypotheses has developed only in recent decades. One of the areas in which case studies have been gaining popularity is education and in particular educational evaluation. [5]

Case studies have also been used as a teaching method and as part of professional development, especially in business and legal education. The problem-based learning (PBL) movement is such an example. When used in (non-business) education and professional development, case studies are often referred to as critical incidents.

History of business cases

When the Harvard Business School was started, the faculty quickly realized that there were no textbooks suitable to a graduate program in business. Their first solution to this problem was to interview leading practitioners of business and to write detailed accounts of what these managers were doing. Of course the of the factors that influence it. Cases are generally written by business school faculty with particular learning objectives in mind and are refined in the classroom before publication. Additional relevant documentation (such as financial statements, time-lines, and short biographies, often referred to in the case as "exhibits"), multimedia supplements (such as video-recordings of interviews with the case protagonist), and a carefully crafted teaching note often accompany cases.

Content analysis is a methodology in the social sciences for studying the content of communication. Earl Babbie defines it as "the study of recorded human communications, such as books, websites, paintings and laws." It is most commonly used by researchers in the social sciences to analyze recorded transcripts of interviews with participants.

Content analysis is also considered a scholarly methodology in the humanities by which texts are studied as to authorship, authenticity, or meaning. This latter subject include philology, hermeneutics, and semiotics.

Harold Lasswell formulated the core questions of content analysis: "Who says what, to whom, why, to what extent and with what effect?." Ole Holsti (1969) offers a broad definition of content analysis as "any technique for making inferences by objectively and systematically identifying specified characteristics of messages." Kimberly A. Neuendorf (2002) offers a six-part definition of content analysis:

"Content analysis is an indepth analysis using quantitative or qualitative techniques of messages using a scientific method (including attention to objectivity-intersubjectivity, a priori design, reliability, validity, generalizability, replicability, and hypothesis testing) and is not limited as to the types of variables that may be measured or the context in which the messages are created or presented."

Description

In the 1931s, Alfred R Lindesmith developed a methodology to refute existing hypotheses, which became known as a content analysis technique, and it gained popularity in the 1960s by Glaser and is referred to as the “The Constant Comparative Method of Qualitative Analysis” in an article published in 1964-65. Glaser and Strauss (1967) referred to their adaptation of it as “Grounded Theory." The method of content analysis enables the researcher to include large amounts of textual information and systematically identify its properties, e.g. the frequencies of most used keywords (KWIC meaning "Key Word in Context") by detecting the more important structures of its communication content. Yet such amounts of textual information must be categorised analysis, providing at the end a meaningful reading of content under scrutiny. David Robertson (1976:73-75) for example created a coding frame for a comparison of modes of party

competition between British and American parties. It was developed further in 1979 by the Manifesto Research Group aiming at a comparative content-analytic approach on the policy positions of political parties.

Since the 1980s, content analysis has become an increasingly important tool in the measurement of success in public relations (notably media relations) programs and the assessment of media profiles. In these circumstances, content analysis is an element of media evaluation or media analysis. In analyses of this type, data from content analysis is usually combined with media data (circulation, readership, number of viewers and listeners, frequency of publication). It has also been used by futurists to identify trends. In 1982, John Naisbitt published his popular Megatrends, based on content analysis in the US media.

The creation of coding frames is intrinsically related to a creative approach to variables that exert an influence over textual content. In political analysis, these variables could be political scandals, the impact of public opinion polls, sudden events in external politics, inflation etc. Mimetic Convergence, created by F. Lampreia Carvalho for the comparative analysis of electoral proclamations on free-to-air television is an example of creative articulation of variables in content analysis. The methodology describes the construction of party identities during long-term party competitions on TV, from a dynamic perspective, governed by the logic of the contingent. This method aims to capture the contingent logic observed in electoral campaigns by focusing on the repetition and innovation of themes sustained in party broadcasts. According to such post-structuralist perspective from which electoral competition is analysed, the party identities, 'the real' cannot speak without mediations because there is not a natural centre fixing the meaning of a party structure, it rather depends on ad-hoc articulations. There is no empirical reality outside articulations of meaning. Reality is an outcome of power struggles that unify ideas of social structure as a result of contingent interventions. In Brazil, these contingent interventions have proven to be mimetic and convergent rather than divergent and polarised, being integral to the repetition of dichotomised worldviews.

Mimetic Convergence thus aims to show the process of fixation of meaning through discursive articulations that repeat, alter and subvert political issues that come into play. For this reason, parties are not taken as the pure expression of conflicts for the representation of interests (of different classes, religions, ethnic groups (see: Lipset & Rokkan 1967, Lijphart 1984) but attempts to recompose and re-articulate ideas of an absent totality around signifiers gaining positivity.

Every content analysis should depart from a hypothesis. The hypothesis of Mimetic Convergence supports the Downsian interpretation that in general, rational voters converge in the direction of uniform positions in most thematic dimensions. The hypothesis guiding the analysis of Mimetic Convergence between political parties' broadcasts is: 'public opinion polls on vote intention, published throughout campaigns on TV will contribute to successive revisions of candidates' discourses. Candidates re-orient their arguments and thematic selections in part by the signals sent by voters. One must also consider the interference of other kinds of input on electoral propaganda such as internal and external political crises and the arbitrary interference of private interests on the dispute. Moments of internal crisis in disputes between candidates might result

from the exhaustion of a certain strategy. The moments of exhaustion might consequently precipitate an inversion in the thematic flux.

As an evaluation approach, content analysis is considered by some to be quasi-evaluation because content analysis judgments need not be based on value statements if the research objective is aimed at presenting subjective experiences. Thus, they can be based on knowledge of everyday lived experiences. Such content analyses are not evaluations. On the other hand, when content analysis judgments are based on values, such studies are evaluations (Frisbie, 1986).

As demonstrated above, only a good scientific hypothesis can lead to the development of a methodology that will allow the empirical description, be it dynamic or static.

Uses of content analysis

Content analysis. This is a closely related if not overlapping kind, often included under the general rubric of “qualitative analysis,” and used primarily in the social sciences. It is “a systematic, replicable technique for compressing many words of text into fewer content categories based on explicit rules of coding” (Stemler 2001). It often involves building and applying a “concept dictionary” or fixed vocabulary of terms on the basis of which words are extracted from the textual data for concording or statistical computation.

Ole Holsti (1969) groups 15 uses of content analysis into three basic categories:

make inferences about the antecedents of a communication describe and make inferences about characteristics of a communication

make inferences about the effects of a communication.

He also places these uses into the context of the basic communication paradigm.

The following table shows fifteen uses of content analysis in terms of their general purpose, element of the communication paradigm to which they apply, and the general question they are intended to answer.

Uses of Content Analysis by Purpose, Communication Element, and Question

Purpose Element Question Use

Make inferences about the antecedents of communications

Source Who? Answer questions of

disputed authorship (authorship analysis)

Encoding process

Why? Secure political & military intelligence

Analyze traits of individuals

Infer cultural aspects & change

Provide legal & evaluative evidence

Describe & make inferences about the characteristics of communications

Channel How?

Analyze techniques of persuasion

Analyze style

Message What?

Describe trends in communication content

Relate known characteristics of sources to messages they produce

Compare communication content to standards

Recipient To whom?

Relate known characteristics of audiences to messages produced for them

Describe patterns of communication

Make inferences about the consequences of communications

Decoding process

With what effect?

Measure readability

Analyze the flow of information

Assess responses to communications

Note. Purpose, communication element, & question from Holsti (1969). Uses primarily from Berelson (1952) as adapted by Holsti (1969).

The process of a content analysis

According to Dr. Klaus Krippendorff (1980 and 2004), six questions must be addressed in every content analysis:

1. Which data are analyzed?2. How are they defined?

3. What is the population from which they are drawn?

4. What is the context relative to which the data are analyzed?

5. What are the boundaries of the analysis?

6. What is the target of the inferences?

The assumption is that words and phrases mentioned most often are those reflecting important concerns in every communication. Therefore, quantitative content analysis starts with word frequencies, space measurements (column centimeters/inches in the case of newspapers), time counts (for radio and television time) and keyword frequencies. However, content analysis extends far beyond plain word counts, e.g. with Keyword In Context routines words can be analysed in their specific context to be disambiguated. Synonyms and homonyms can be isolated in accordance to linguistic properties of a language.

Qualitatively, content analysis can involve any kind of analysis where communication content (speech, written text, interviews, images ...) is categorized and classified. In its beginnings, using the first newspapers at the end of 19th century, analysis was done manually by measuring the number of lines and amount of space given a subject. With the rise of common computing facilities like PCs, computer-based methods of analysis are growing in popularity. Answers to open ended questions, newspaper articles, political party manifestoes, medical records or systematic observations in experiments can all be subject to systematic analysis of textual data. By having contents of communication available in form of machine readable texts, the input is analysed for frequencies and coded into categories for building up inferences. Robert Philip Weber (1990) notes: "To make valid inferences from the text, it is important that the classification procedure be reliable in the sense of being consistent: Different people should code the same text in the same way" (p. 12). The validity, inter-coder reliability and intra-coder reliability are subject to intense methodological research efforts over long years (see Krippendorf, 2004).

One more distinction is between the manifest contents (of communication) and its latent meaning. "Manifest" describes what (an author or speaker) definitely has written, while latent meaning describes what an author intended to say/write. Normally, content analysis can only be applied on manifest content; that is, the words, sentences, or texts themselves, rather than their meanings.

Dermot McKeone (1995) has highlighted the difference between prescriptive analysis and open analysis. In prescriptive analysis, the context is a closely-defined set of communication parameters (e.g. specific messages, subject matter); open analysis identifies the dominant messages and subject matter within the text.

A further step in analysis is the distinction between dictionary-based (quantitative) approaches and qualitative approaches. Dictionary-based approaches set up a list of categories derived from the frequency list of words and control the distribution of words and their respective categories over the texts. While methods in quantitative content analysis in this way transform observations

of found categories into quantitative statistical data, the qualitative content analysis focuses more on the intentionality and its implications.

Reliability in content analysis

Dr. Kimberly A. Neuendorf (2002) suggests that when human coders are used in content analysis, reliability translates to intercoder reliability or "the amount of agreement or correspondence among two or more coders."

Critical theory is the examination and critique of society and culture, drawing from knowledge across the social sciences and humanities. The term has two quite different meanings with different origins and histories, one originating in sociology and the other in literary criticism. This has led to the very literal use of 'critical theory' as an umbrella term to describe theoretical critique.

Critical theory, in the sociological context, refers to a style of Marxist theory with a tendency to engage with non-Marxist influences (for instance, the work of Nietzsche and Freud).[1] This tendency has been referred to pejoratively by stricter Marxists as 'revisionism'. Modern critical theory arose from a trajectory extending from the nonpositivist sociology of Weber and Simmel, the neo-Marxist theory of Lukács and Gramsci, toward the milieu associated with Frankfurt Institute of Social Research. It is with this so-called 'Frankfurt School' of theorists that the term is most commonly associated: Herbert Marcuse, Theodor Adorno, Max Horkheimer, Walter Benjamin, and Jürgen Habermas. With the latter, critical theory shed further its roots in German Idealism and moved closer to American Pragmatism. The theoretical concern for a cultural 'superstructure' derived from a material 'base' often remains as the only central Marxist tenet in contemporary critical theory.

Two primary definitions

There are two meanings of critical theory which derive from two different intellectual traditions associated with the meaning of criticism and critique. Both derive ultimately from the Greek word kritikos meaning judgment or discernment, and in their present forms go back to the 18th century. While they can be considered completely independent intellectual pursuits, increasingly scholars are interested in the areas of critique where the two overlap.

To use an epistemological distinction introduced by Jürgen Habermas in Erkenntnis und Interesse [1968] (Knowledge and Human Interests), critical theory in literary studies is ultimately a form of hermeneutics, i.e. knowledge via interpretation to understand the meaning of human texts and symbolic expressions. Critical social theory is, in contrast, a form of self-reflective knowledge involving both understanding and theoretical explanation to reduce entrapment in systems of domination or dependence, obeying the emancipatory interest in expanding the scope of autonomy and reducing the scope of domination.

From this perspective, much literary critical theory, since it is focused on interpretation and explanation rather than on social transformation, would be regarded as positivistic or traditional rather than critical theory in the Kantian or Marxian sense. Critical theory in literature and the humanities in general does not necessarily involve a normative dimension, whereas critical social theory does, either through criticizing society from some general theory of values, norms, or oughts, or through criticizing it in terms of its own espoused values.

In social theory, Critical theory was first defined by Max Horkheimer of the Frankfurt School of sociology in his 1937 essay Traditional and Critical Theory: Critical theory is a social theory oriented toward critiquing and changing society as a whole, in contrast to traditional theory oriented only to understanding or explaining it. Horkheimer wanted to distinguish critical theory as a radical, emancipatory form of Marxian theory, critiquing both the model of science put forward by logical positivism and what he and his colleagues saw as the covert positivism and authoritarianism of orthodox Marxism and Communism. Core concepts are: (1) That critical social theory should be directed at the totality of society in its historical specificity (i.e. how it came to be configured at a specific point in time), and (2) That critical theory should improve understanding of society by integrating all the major social sciences, including geography, economics, sociology, history, political science, anthropology, and psychology.

This version of "critical" theory derives from Kant's (18th-century) and Marx's (19th Century) use of the term "critique", as in Kant's Critique of Pure Reason and Marx's concept that his work Das Kapital (Capital) forms a "critique of political economy". For Kant's transcendental idealism, "critique" means examining and establishing the limits of the validity of a faculty, type, or body of knowledge, especially through accounting for the limitations imposed by the fundamental, irreducible concepts in use in that knowledge system. Early on, Kant's notion associated critique with the disestablishment of false, unprovable, or dogmatic philosophical, social, and political beliefs, because Kant's critique of reason involved the critique of dogmatic theological and metaphysical ideas and was intertwined with the enhancement of ethical autonomy and the Enlightenment critique of superstition and irrational authority. Marx explicitly developed this notion into the critique of ideology and linked it with the practice of social revolution, as in the famous 11th of his "Theses on Feuerbach," "Philosophers have only interpreted the world in certain ways; the point is to change it".[3]

One of the distinguishing characteristics critical theory, as Adorno and Horkheimer elaborated in their Dialectic of Enlightenment (1947), is a certain ambivalence concerning the ultimate source or foundation of social domination, an ambivalence which gave rise to the “pessimism” of the new critical theory over the possibility of human emancipation and freedom.[4] This ambivalence was rooted, of course, in the historical circumstances in which the work was originally produced, in particular, the rise of National Socialism, state capitalism, and mass culture as entirely new forms of social domination that could not be adequately explained within the terms of traditional Marxist sociology.[5] For Adorno and Horkheimer state intervention in the economy had effectively abolished the tension in capitalism between the "relations of production" and "material productive forces of society," a tension which, according to traditional critical theory, constituted the primary contradiction within capitalism. The market (as an "unconscious" mechanism for the distribution of goods) and private property had been replaced by centralized planning and socialized ownership of the means of production.[6] Yet, contrary to Marx’s famous

prediction in the Preface to a Contribution to the Critique of Political Economy, this shift did not lead to "an era of social revolution," but rather to fascism and totalitarianism. As such, critical theory was left, in Jürgen Habermas’ words, without "anything in reserve to which it might appeal; and when the forces of production enter into a baneful symbiosis with the relations of production that they were supposed to blow wide open, there is no longer any dynamism upon which critique could base its hope."[7] For Adorno and Horkheimer, this posed the problem of how to account for the apparent persistence of domination in the absence of the very contradiction that, according to traditional critical theory, was the source of domination itself.

In the 1960s, Jürgen Habermas raised the epistemological discussion to a new level in his Knowledge and Human Interests, by identifying critical knowledge as based on principles that differentiated it either from the natural sciences or the humanities, through its orientation to self-reflection and emancipation. Though unsatisfied with Adorno and Horkeimer's thought presented in Dialectic of Enlightenment, Habermas shares the view that, in the form of instrumental rationality, the era of modernity marks a move away from the liberation of enlightenment and toward a new form of enslavement.[8] His ideas regarding the relationship between modernity and rationalization are in this sense strongly influenced by Max Weber. Habermas dissolved further the elements of critical theory derived from Hegelian German Idealism, though his thought remains broadly Marxist in its epistemological approach. Perhaps his two most influential ideas are the concepts of the public sphere and communicative action; the latter arriving partly as a reaction to new post-structural or so-called 'post-modern' challenges to the discourse of modernity. Habermas engaged in regular correspondence with Richard Rorty and a strong sense of philosophical pragmatism may be felt in his theory; thought which frequently traverses the boundaries between sociology and philosophy.

Postmodern critical theory

While modernist critical theory (as described above) concerns itself with “forms of authority and injustice that accompanied the evolution of industrial and corporate capitalism as a political-economic system,” postmodern critical theory politicizes social problems “by situating them in historical and cultural contexts, to implicate themselves in the process of collecting and analyzing data, and to relativize their findings” (Lindlof & Taylor, 2002, p. 52). Meaning itself is seen as unstable due to the rapid transformation in social structures and as a result the focus of research is centered on local manifestations rather than broad generalizations.

Postmodern critical research is also characterized by what is called, the crisis of representation, which rejects the idea that a researcher’s work is considered an “objective depiction of a stable other” (Lindlof & Taylor, 2002, p. 53). Instead, in their research and writing, many postmodern scholars have adopted “alternatives that encourage reflection about the ‘politics and poetics’ of their work. In these accounts, the embodied, collaborative, dialogic, and improvisational aspects of qualitative research are clarified” (Lindlof & Taylor, 2002, p. 53). For an example of postmodern critical work, see Rolling’s piece, entitled Secular Blasphemy: Utter(ed) Transgressions Against Names and Fathers in the Postmodern Era (2008).

Often, the term 'critical theory' is appropriated when an author (perhaps most notably Michel Foucault) works within sociological terms yet attacks the social or human sciences (thus

attempting to remain 'outside' those frames of enquiry). Jean Baudrillard has also been described as a critical theorist to the extent that he was an unconventional and critical sociologist; this appropriation is similarly casual, holding little or no relation to the Frankfurt School.

Critical ethnographyMain article: Critical Ethnography

Critical ethnography is "a type of reflection that examines culture, knowledge, and action...Critical ethnographers describe, analyze, and open to scrutiny otherwise hidden agendas, power centers, and assumptions that inhibit, repress, and constrain" (Thomas, 1993, pp. 2–3). While "conventional ethnography" "describes what is", critical ethnography "asks what could be"….Conventional ethnographers study culture for the purposes of describing it; critical ethnographers do so to change it" (Thomas, 1993, p. 4).

In literary criticism

Main article: Literary theory

The second meaning of critical theory is that of theory used in literary criticism ("critical theory") and in the analysis and understanding of literature. This is discussed in greater detail under literary theory. This form of critical theory is not necessarily oriented toward radical social change or even toward the analysis of society, but instead specializes on the analysis of texts. It originated among literary scholars and in the discipline of literature in the 1960s and 1970s, and has really only come into broad use since the 1980s, especially as theory used in literary studies has increasingly been influenced by European philosophy and social theory.

This version of "critical" theory derives from the notion of literary criticism as establishing and enhancing the understanding and evaluation of literature in the search for truth. Some consider literary theory merely an aesthetic concern, as articulated, for example, in Joseph Addison's notion of a critic as one who helps understand and interpret literary works: "A true critic ought to dwell rather upon excellencies than imperfections, to discover the concealed beauties of a writer, and communicate to the world such things as are worth their observation." [9] This notion of criticism ultimately goes back to Aristotle's Poetics as a theory of literature.

From the literary side, starting in the 1960s literary scholars, reacting especially against the New Criticism of the previous decades, which tried to analyze literary texts purely internally, began to incorporate into their analyses and interpretations of literary works initially semiotic, linguistic, and interpretive theory, then structuralism, Lacanian psychoanalysis, post-structuralism, and deconstruction as well as Continental philosophy, especially phenomenology and hermeneutics, and critical social theory and various other forms of neo-Marxian theory.

Thus literary criticism became highly theoretical and some of those practicing it began referring to the theoretical dimension of their work as "critical theory", i.e. philosophically inspired theory of literary criticism. And thus incidentally critical theory in the sociological sense also became, especially among literary scholars of left-wing sympathies, one of a number of influences upon and streams within critical theory in the literary sense.

Furthermore, along with the expansion of the mass media and mass/popular culture in the 1960s and 1970s and the blending of social and cultural criticism and literary criticism, the methods of both kinds of critical theory sometimes intertwined in the analysis of phenomena of popular culture, as in the emerging field of cultural studies, in which concepts deriving from Marxian theory, post-structuralism, semiology, psychoanalysis and feminist theory would be found in the same interpretive work. Both strands were often present in the various modalities of postmodern theory.

Language and construction

The two points at which there is the greatest overlap or mutual impingement of the two versions of critical theory are in their interrelated foci on language, symbolism, and communication and in their focus on construction.

Language and communication

From the 1960s and 1970s onward, language, symbolism, text, and meaning became foundational to theory in the humanities and social sciences, through the short-term and long-term influences of Ludwig Wittgenstein, Ferdinand de Saussure, George Herbert Mead, Noam Chomsky, Hans-Georg Gadamer, Roland Barthes, Jacques Derrida and other thinkers in the traditions of linguistic and analytic philosophy, structural linguistics, symbolic interactionism, hermeneutics, semiology, linguistically oriented psychoanalysis (Jacques Lacan, Alfred Lorenzer), and deconstruction. When, in the 1970s and 1980s, Jürgen Habermas also redefined critical social theory as a theory of communication, i.e. communicative competence and communicative rationality on the one hand, distorted communication on the other, the two versions of critical theory began to overlap or intertwine to a much greater degree than before.

Construction

Both versions of critical theory have focused on the processes of synthesis, production, or construction by which the phenomena and objects of human communication, culture, and political consciousness come about. Whether it is through the transformational rules by which the deep structure of language becomes its surface structure (Chomsky), the universal pragmatic principles through which mutual understanding is generated (Habermas), the semiotic rules by which objects of daily usage or of fashion obtain their meanings (Barthes), the psychological processes by which the phenomena of everyday consciousness are generated (psychoanalytic thinkers), the episteme that underlies our cognitive formations (Foucault), and so on, there is a common interest in the processes (often of a linguistic or symbolic kind) that give rise to observable phenomena. Here there is significant mutual influence among aspects of the different versions of critical theory. Ultimately this emphasis on production and construction goes back to the revolution wrought by Kant in philosophy, namely his focus in the Critique of Pure Reason on synthesis according to rules as the fundamental activity of the mind that creates the order of our experience.

Discourse analysis (DA), or discourse studies, is a general term for a number of approaches to analyzing written, spoken or signed language use.

Discourse analysis is the branch of linguistics that deals with the study and application of approaches to analyse written, spoken or signed language.

The objects of discourse analysis—discourse, writing, talk, conversation, communicative event, etc.—are variously defined in terms of coherent sequences of sentences, propositions, speech acts or turns-at-talk. Contrary to much of traditional linguistics, discourse analysts not only study language use 'beyond the sentence boundary', but also prefer to analyze 'naturally occurring' language use, and not invented examples. This is known as corpus linguistics; text linguistics is related.

Discourse analysis has been taken up in a variety of social science disciplines, including linguistics, sociology, anthropology, social work, cognitive psychology, social psychology, international relations, human geography, communication studies and translation studies, each of which is subject to its own assumptions, dimensions of analysis, and methodologies. Sociologist Harold Garfinkel was another influence on the discipline: see below.

History

The examples and perspective in this article deal primarily with the United States and do not represent a worldwide view of the subject. Please improve this article and discuss the issue on the talk page.

The term discourse analysis (DA) first came into general use following the publication of a series of papers by Zellig Harris beginning in 1952 and reporting on work from which he developed transformational grammar in the late 1930s. Formal equivalence relations among the sentences of a coherent discourse are made explicit by using sentence transformations to put the text in a canonical form. Words and sentences with equivalent information then appear in the same column of an array. This work progressed over the next four decades (see references) into a science of sublanguage analysis (Kittredge & Lehrberger 1982), culminating in a demonstration of the informational structures in texts of a sublanguage of science, that of immunology, (Harris et al. 1989) and a fully articulated theory of linguistic informational content (Harris 1991). During this time, however, most linguists pursued a succession of elaborate theories of sentence-level syntax and semantics.

Although Harris had mentioned the analysis of whole discourses, he had not worked out a comprehensive model, as of January, 1952. A linguist working for the American Bible Society, James A. Lauriault/Loriot, needed to find answers to some fundamental errors in translating Quechua, in the Cuzco area of Peru. He took Harris's idea, recorded all of the legends and, after going over the meaning and placement of each word with a native speaker of Quechua, was able to form logical, mathematical rules that transcended the simple sentence structure. He then applied the process to another language of Eastern Peru, Shipibo. He taught the theory in Norman, Oklahoma, in the summers of 1956 and 1957 and entered the University of Pennsylvania in the interim year. He tried to publish a paper Shipibo Paragraph Structure, but it was delayed until 1970 (Loriot & Hollenbach 1970). In the meantime, Dr. Kenneth L. Pike, a

professor at University of Michigan, Ann Arbor, taught the theory, and one of his students, Robert E. Longacre, was able to disseminate it in a dissertation.

Harris's methodology was developed into a system for the computer-aided analysis of natural language by a team led by Naomi Sager at NYU, which has been applied to a number of sublanguage domains, most notably to medical informatics. The software for the Medical Language Processor is publicly available on SourceForge.

In the late 1960s and 1970s, and without reference to this prior work, a variety of other approaches to a new cross-discipline of DA began to develop in most of the humanities and social sciences concurrently with, and related to, other disciplines, such as semiotics, psycholinguistics, sociolinguistics, and pragmatics. Many of these approaches, especially those influenced by the social sciences, favor a more dynamic study of oral talk-in-interaction.

Mention must also be made of the term "Conversational analysis", which was influenced by the Sociologist Harold Garfinkel who is the founder of Ethnomethodology.

In Europe, Michel Foucault became one of the key theorists of the subject, especially of discourse, and wrote The Archaeology of Knowledge.

Topics of interest

Topics of discourse analysis include:

The various levels or dimensions of discourse, such as sounds (intonation, etc.), gestures, syntax, the lexicon, style, rhetoric, meanings, speech acts, moves, strategies, turns and other aspects of interaction

Genres of discourse (various types of discourse in politics, the media, education, science, business, etc.)

The relations between discourse and the emergence of syntactic structure

The relations between text (discourse) and context

The relations between discourse and power

The relations between discourse and interaction

The relations between discourse and cognition and memory

Perspectives

The following are some of the specific theoretical perspectives and analytical approaches used in linguistic discourse analysis:

Emergent grammar Text grammar (or 'discourse grammar')

Cohesion and relevance theory

Functional grammar

Rhetoric

Stylistics (linguistics)

Interactional sociolinguistics

Ethnography of communication

Pragmatics , particularly speech act theory

Conversation analysis

Variation analysis

Applied linguistics

Cognitive psychology , often under the label discourse processing, studying the production and comprehension of discourse.

Discursive psychology

Response based therapy (counselling)

Critical discourse analysis

Sublanguage analysis

Although these approaches emphasize different aspects of language use, they all view language as social interaction, and are concerned with the social contexts in which discourse is embedded.

Often a distinction is made between 'local' structures of discourse (such as relations among sentences, propositions, and turns) and 'global' structures, such as overall topics and the schematic organization of discourses and conversations. For instance, many types of discourse begin with some kind of global 'summary', in titles, headlines, leads, abstracts, and so on.

In psychology, qualitative research has come to be defined as research whose findings are not arrived at by statistical or other quantitative procedures. Qualitative research is often said to be naturalistic.[1] That is, its goal is to understand behaviour in a natural setting. Two other goals attributed to qualitative research are understanding a phenomenon from the perspective of the research participant and understanding the meanings people give to their experience. It attempts to do this by using so-called naturalistic methods - interviewing, observation, ethnography, participant observation and focus groups. Each of these methods seeks to understand the perspective of the research participant within the context of their everyday life. This means that the researcher is concerned with asking broad questions that allow the respondent to answer in

their own words. These methods allow the researcher to try to qualify their understanding during the research process through further probing questions. In addition, a method such as observation allows the researcher to observe people within natural settings - particularly those in public places. This has resulted in greater understanding of people's behaviours in for example - lifts, public transport, and queues.

Qualitative research is sometimes said to have as its goal the understanding of the sample studied, rather than generalizing from the sample to the population. However, the results of qualitative research can be applied to other settings - as long as the reader of the research understands the limitations. For example, the research findings of a qualitative case study of primary school children in a particular school and their mobile phone use will tell us more about the mobile phone of children in the general population, than of adults. However, the type of school (public or private), where it was located, and the socio-economic background of the students need to be taken into consideration when applying any findings to other settings (either schools or the general population of children).

In addition to the methods for collecting data mentioned above, qualitative research includes a wide range of ways to analyse the data. One of the most popular of these is known as grounded theory. Others include conversation analysis, discourse analysis, thematic analysis, and even historical analysis.

Qualitative psychological research emphasizes fieldwork, and this emphasis has been offered as a distinguishing mark. Qualitative psychological research is also described as holistic. That is, qualitative researchers believe in studying phenomena in its context rather than concentrating on narrow aspects of the phenomena. This means that they either observe or participate in the phenomena they are studying, e.g. attending a football game to understand the behaviours of fan, and/or they ask open-ended questions about the behaviour of fans at football games. These questions are holistic because they are designed to understand the context of behaviour - they will usually follow a pattern that replicates the experience, e.g. "What did you do when you arrived? Who did you come with? What did you do then?" However, similar methods are used by quantitative researchers.

Origins and methods

The philosophical bases of qualitative psychological research are found in phenomenology, ethnomethodology, and naturalistic behaviourism. Its research methods are derived from ethnography and anthropology.

In psychology, the research methods commonly classified as qualitative include:

participant observation direct observation

unstructured interviewing

case studies

content analysis

protocol analysis

focus groups

The data collected by researchers using these techniques consist of:

the results of open-ended interviews notes of direct observation

written documents (answers to questionnaires, diaries, program records, and so on)

After collecting data qualitative psychological researchers goal are to examine their data in depth and in detail.

Most psychological researchers probably use both types of method. In particular, qualitative methods are widely used as exploratory methods; the results of qualitative analysis are used to design quantitative research which tests null hypotheses derived from the qualitative observations.

Those psychological researchers who prefer qualitative research argue that statistically-based research has limitations because it is less able to take into consideration the context of behaviour. Qualitative researchers have developed their own criteria for assessing reliability and validity. The work of Yvonna Lincoln and Egon Guba is an example of this.

Confirmability is a qualitative concept analogous to the concept of objectivity in quantitative research. It is the degree to which research results can be confirmed by other researchers.

Transferability has been proposed as a qualitative substitute for psychometric validity. Research findings are transferable to the extent to which they can be generalized to settings other than the one in which they were made.

It could be argued, however, that any concept which attempts to assess degree or extent is inherently quantitative.

Quantitative psychological research is defined as psychological research which performs mathematical modeling and statistical estimation or statistical inference. This definition distinguishes it from so-called qualitative psychological research; however, many psychologists do not acknowledge any real difference between quantitative and qualitative research. The validity of the distinction is discussed in the article about qualitative psychological research.

Statistics is widely used in quantitative psychological research. Typically a project begins with the collection of data based on a theory or hypothesis, followed by the application of descriptive or inferential statistical methods. Often it is necessary to collect a very large volume of data,

which require validating, verifying and recoding. Software packages such as PSPP and R are typically used for this purpose, and for subsequent analysis. Causal relationships are studied by manipulating factors thought to influence the phenomena of interest while controlling other variables relevant to the experimental outcomes. Researchers might measure and study the relationship between education and measurable psychological effects, whilst controlling for other key variables. Quantitatively based surveys are widely used by psychologists, and statistics such as the proportion of respondents who display one or more psychological traits reported. In such surveys, respondents are asked a set of structured questions and their responses are tabulated. The software can then perform correlation analysis or other procedures on the data.

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Yin (2005) suggested that researchers should decide whether to do single-case or multiple-case studies and chose to keep the case holistic or have embedded sub-cases. This two-by-two combination can produce four basic designs for case studies.

When selecting a case for a case study, researchers often use information-oriented sampling , as opposed to random sampling [3]. This is because an average case is often not the richest in information. Extreme or atypical cases reveal more information because they activate more basic mechanisms and more actors in the situation studied. In addition, from both an understanding-oriented and an action-oriented perspective, it is often more important to clarify the deeper causes behind a given problem and its consequences than to describe the symptoms of the problem and how frequently they occur. Random samples emphasizing representativeness will seldom be able to produce this kind of insight; it is more appropriate to select some few cases chosen for their validity. But this isnt always the case.

Three types of information-oriented cases may be distinguished:

1. Extreme or deviant cases2. Critical cases

3. Paradigmatic cases.

Critical case

A critical case can be defined as having strategic importance in relation to the general problem. For example, an occupational medicine clinic wanted to investigate whether people working with organic solvents suffered brain damage. Instead of choosing a representative sample among all those enterprises in the clinic’s area that used organic solvents, the clinic strategically located , ‘If it is valid for this case, it is valid for all (or many) cases.’ In its negative form, the generalization would be, ‘If it is not valid for this case, then it is not valid for any (or only few) cases.’

Generalizing from case studies

The case study is effective for generalizing using the type of test that Karl Popper called falsification, which forms part of critical reflexivity [3]. Falsification is one of the most rigorous tests to which a scientific proposition can be subjected: if just one observation does not fit with the proposition it is considered not valid generally and must therefore be either revised or rejected. Popper himself used the now famous example of, "All swans are white," and proposed that just one observation of a single black swan would falsify this proposition and in this way have general significance and stimulate further investigations and theory-building. The case study is well suited for identifying "black swans" because of its in-depth approach: what appears to be "white" often turns out on closer examination to be "black."

For instance, Galileo Galilei’s rejection of Aristotle’s law of gravity was based on a case study selected by information-oriented sampling and not random sampling. The rejection consisted primarily of a conceptual experiment and later on of a practical one. These experiments, with the benefit of hindsight, are self-evident. Nevertheless, Aristotle’s incorrect view of gravity dominated scientific inquiry for nearly two thousand years before it was falsified. In his experimental thinking, Galileo reasoned as follows: if two objects with the same weight are released from the same height at the same time, they will hit the ground simultaneously, having fallen at the same speed. If the two objects are then stuck together into one, this object will have double the weight and will according to the Aristotelian view therefore fall faster than the two individual objects. This conclusion seemed contradictory to Galileo. The only way to avoid the contradiction was to eliminate weight as a determinant factor for acceleration in free fall. Galileo’s experimentalism did not involve a large random sample of trials of objects falling from a wide range of randomly selected heights under varying wind conditions, and so on. Rather, it was a matter of a single experiment, that is, a case study.(Flyvbjerg, 2006, p. 225-6) [2]

Galileo’s view continued to be subjected to doubt, however, and the Aristotelian view was not finally rejected until half a century later, with the invention of the air pump. The air pump made it possible to conduct the ultimate experiment, known by every pupil, whereby a coin or a piece of lead inside a vacuum tube falls with the same speed as a feather. After this experiment, Aristotle’s view could be maintained no longer. What is especially worth noting, however, is that the matter was settled by an individual case due to the clever choice of the extremes of metal and feather. One might call it a critical case, for if Galileo’s thesis held for these materials, it could be expected to be valid for all or a large range of materials. Random and large samples were at no time part of the picture. However it was Galileo's view that was the subject of doubt as it was not reasonable enough to be the Aristotelian view. By selecting cases strategically in this manner one may arrive at case studies that allow generalization.(Flyvbjerg, 2006, p. 225-6) For more on generalizing from case studies, see [3]

Assumptions

1. Cases selected based on dimensions of a theory (pattern-matching) or on diversity on a dependent phenomenon (explanation-building).

2. No generalization to a population beyond cases similar to those studied.

3. Conclusions should be phrased in terms of model elimination, not model validation. Numerous alternative theories may be consistent with data gathered from a case study.

4. Case study approaches have difficulty in terms of evaluation of low-probability causal paths in a model as any given case selected for study may fail to display such a path, even when it exists in the larger population of potential cases.

History of the case study

As a distinct approach to research, use of the case study originated only in the early 20th century. The Oxford English Dictionary traces the phrase case study or case-study back as far as 1934, influenced by the much older concept of a case history in medicine.

The use of case studies for the creation of new theory in social sciences has been further developed by the sociologists Barney Glaser and Anselm Strauss who presented their research method, Grounded theory, in 1967.

The popularity of case studies in testing hypotheses has developed only in recent decades. One of the areas in which case studies have been gaining popularity is education and in particular educational evaluation.

Case studies have also been used as a teaching method and as part of professional development, especially in business and legal education. The problem-based learning (PBL) movement is such an example. When used in (non-business) education and professional development, case studies are often referred to as critical incidents.

History of business cases

When the Harvard Business School was started, the faculty quickly realized that there were no textbooks suitable to a graduate program in business. Their first solution to this problem was to interview leading practitioners of business and to write detailed accounts of what these managers were doing. Of course the of the factors that influence it. Cases are generally written by business school faculty with particular learning objectives in mind and are refined in the classroom before publication. Additional relevant documentation (such as financial statements, time-lines, and short biographies, often referred to in the case as "exhibits"), multimedia supplements (such as video-recordings of interviews with the case protagonist), and a carefully crafted teaching note often accompany cases.

Sensemaking is the ability or attempt to make sense of an ambiguous situation. More exactly, sensemaking is the process of creating situational awareness and understanding in situations of high complexity or uncertainty in order to make decisions. It is "a motivated, continuous effort to understand connections (which can be among people, places, and events) in order to anticipate their trajectories and act effectively" (Klein et al., 2006a).

Sensemaking in individuals and organizations

In individuals, sensemaking is the largely cognitive activity of constructing a hypothetical mental model of the current situation and how it might evolve over time, what threats and opportunities for each action are likely to emerge from this evolution, what potential actions can be taken in response, what the projected outcomes of those responses are, and what values drive the choice of future action. In organizations, sensemaking is a collaborative process of creating shared awareness and understanding out of different individuals' perspectives and varied interests. The process of moving from situational awareness in individuals to shared awareness and

understanding to collaborative decision-making can be considered a socio-cognitive activity in that the individual’s cognitive activities are directly impacted by the social nature of the exchange and vice versa.

Klein et al. (2006b) have presented a theory of sensemaking as a set of processes that is initiated when an individual or organization recognizes the inadequacy of their current understanding of events. Sensemaking is an active two-way process of fitting data into a frame (mental model) and fitting a frame around the data. Neither data nor frame comes first; data evoke frames and frames select and connect data. When there is no adequate fit, the data may be reconsidered or an existing frame may be revised. This description resembles the Recognition-Metacognition model (Cohen et al. 1996), which describes the metacognitive processes that are used by individuals to build, verify, and modify working models (or "stories") in situational awareness to account for an unrecognised situation.(Such notions also echo the processes of assimilation and accommodation in Piaget’s (1972, 1977) theory of cognitive development.)

Sensemaking in command & control

Sensemaking is central to the conceptual framework for military network-centric operations (NCO) espoused by the U.S. Department of Defense (DoD) (Gartska and Alberts, 2004). Sensemaking in NCO theory is said to consist of three interrelated activities:

Forming an awareness of key elements relevant to the situation. This entails knowing "the who, what, when and where."

Forming an understanding of what it all means in some bounded context, based upon past experiences, training, education and cognitive capabilities. This entails:

o Forming hypotheses and making inferences, i.e. generalizations (predictions or anticipations) about future events.

o Forming a sense of the implications for different courses of action.

Making decisions by:

o Generating alternative response actions to control the situation.

o Identifying the objectives, constraints, and factors that influence the feasibility and desirability of each alternative.

o Conducting an assessment of these alternatives.

In a joint/coalition military environment, sensemaking is complicated by numerous of technical, social, organizational, cultural, and operational factors. A central hypothesis of NCO, however, is that the quality of shared sensemaking and collaboration will be better in a "robustly networked" force than in a platform-centric force, empowering people to make better decisions. According to NCO theory, there is a mutually reinforcing relationship among and between individual sensemaking, shared sensemaking, and collaboration.

A symposium on Sensemaking, sponsored by the Command and Control Research Program (CCRP) of the Assistant Secretary of Defense for Command, Control, Communications, and Intelligence, was held in Vienna, Virginia, on 23-25 October 2001. The goal of this meeting was to bring together knowledgeable researchers and practitioners from industry, academia, and government to cross-fertilize the best sensemaking ideas and practices (Leedom, 2001).

Sensemaking and situation assessment

The DoD concept of sensemaking is very similar to that of situation assessment, an umbrella term for the various forms of cognitive processing involved in maintaining situational awareness (SA) (see Endsley, 1995). But while situation assessment is generally thought of as a process of fitting the observed facts to a familiar model, sensemaking implies more of an inductive and constructive process - actively creating awareness and understanding to account for many vague and disparate pieces of information concerning multiple decision-critical events that occur simultaneously over different functional areas. While the original work on situation assessment concentrated on how individuals maintain SA at the tactical level, sensemaking theorists have primarily focused on how shared awareness and understanding are developed within command and control (C2) organizations at the operational level. At the tactical level, individuals monitor and assess their immediate physical environment in order to predict where different elements will be in the next moment. At the operational level, where the situation is far broader, more complex and uncertain, and evolves over hours and days, the organization must collectively make sense of enemy dispositions, intentions and capabilities, as well as anticipate the (often unintended) effects of own-force actions on a complex system of systems.

Sensemaking research

Dervin (1983, 1992, 1996) has investigated individual sensemaking, developing theories underlying the “cognitive gap” that individuals experience when attempting to make sense of observed data.

Weick (1988, 1993, 1995, 2005) has researched sensemaking at the organizational level, providing insight into factors that surface as organizations address either uncertain or ambiguous situations.

Because much of this applied psychological research is grounded within the context of systems engineering and human factors, there exists a strong desire for concepts and performance to be measurable and for theories to be testable. Accordingly, sensemaking and situational awareness are viewed as working concepts that enable us to investigate and improve the interaction between man and information technology. Within this perspective, it is recognized that humans play a significant role in adapting and responding to unexpected or unknown situations, as well as recognized situations.

Theoretical sampling is a term coined by Barney Glaser and Anselm Strauss in 1967 in the context of social research to describe the process of choosing new research sites or research cases to compare with one that has already been studied. It is one of the tools of qualitative research.

The goal of theoretical sampling is not the same as with the probabilistic sampling; the researcher's goal is not the representative capture of all possible variations, but to gain a deeper understanding of analysed cases and facilitate the development of analytic frame and concepts used in their research.

Theoretical sampling can be viewed as a technique of data triangulation: using independent pieces of information to get a better fix on something that is only partially known or understood.

Description

Use quantitative research methods in market research when:

You want to know “how many” and/or “how often” You want to profile a target audience by determining what proportion of the

audience has certain behaviors, behavioral intentions, attitudes, and knowledge related to the health concern, and whether specific determinants predict behaviors at a statistically significant level.

You conduct quantitative market research generally involves:

Surveying a large group of people (usually several hundred), and Using a structured questionnaire that contains predominantly closed-ended, or

forced-choice, questions.

To design and conduct a quantitative survey, you should consider getting input from a survey expert. Together you will need to consider issues related to designing an appropriate sample, using valid and reliable measures, and conducting a pretest before the survey study is launched. Most surveys are custom studies designed to answer a specific set of research questions. Some surveys are omnibus studies, in which you add questions about your topic to an existing survey.

Surveys can be conducted face-to-face, by mail or telephone, or by computer. They can be self-administered or administered by an interviewer. Tools such as computer-assisted telephone interviewing or touch-screen surveys via a Web site can be useful.

Pros

When the survey involves a convenience sample (e.g., a mall intercept study), data can be collected and analyzed fairly quickly

When the survey involves a statistically valid random sample, the results from the sample can be generalized to the entire population if the response rate is high enough

Surveys can provide reliable (i.e., repeatable) direction for planning programs and messages

Surveys can be anonymous, which is useful for sensitive topics

Like qualitative research methods, surveys can include visual material and can be used to pretest prototypes

You can generalize your findings beyond your participant group.

Cons

They have a limited ability to probe answers People who are willing to respond may share characteristics that don’t apply to

the audience as a whole, creating a potential bias in the study

They can be very costly.