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Ground Theory-Social Research Methods

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Grounded theory

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This article includes a list of references or external links, but its sources remain unclear because it has insufficient inline citations. Please help to improve this article by introducing more precise citations where appropriate. (March 2009)

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].

x[edit] 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

[edit] 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).

[edit] 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.

[edit] Glaser

The first book, "The Discovery of Grounded Theory", from 1967, was "developed in close and equal collaboration" (Strauss, 1993, p. 12) by Glaser and Strauss. Glaser wrote a methodology "Theoretical Sensitivity" in 1978 and has since then 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[2] 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.

[edit] 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

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