RESEARCH METHODOLOGY 5.0 Introduction
5.5 Grounded theory methodology
5.5.3 Data collection and data analysis in GT
According to Corbin and Strauss (1990), the first canon or procedure is that information- gathering and analysis are interconnected processes. In carrying out this study, when the first lot of data was collected, it was followed by data analysis. Data were collected in the morning
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and part of the afternoon. Evenings were reserved for analytic work on the data in which the task was coding. Coding is the process of defining what data are about. It is a way of categorising sections of information with a short label that at the same time sums up and accounts for every piece of the information. Codes specify how one chooses, divides, and sorts out data and commences with analytic accounting of the information (Charmaz, 2014, p. 111).
Charmaz (2014, p. 113) in addition argues that coding is the pivotal link between collecting data and developing an emergent theory to explain these data. Through coding, you define what is happening in the data and begin to grapple with what it means.” The process of coding allowed me to break up, describe and label the data that I had collected. By coding I labelled data and explained what I saw in the data and what was emerging from the data. Other scholars have described coding as codifying:
“To codify is to arrange things in a systematic order, to make something part of a system or classification, to categorise. When codes are applied and reapplied to quantitative data, you are codifying a process that permits data to be segregated, groups, regrouped and re-linked in order to consolidate meaning and explanation…analysis is the search for patterns in data and for ideas that help explain why those patterns are there in the first place. Coding is thus a method that enables you to organise and group similarly coded data into categories or families because they share some characteristics (Saldaña, 2009, p. 8).”
So coding is heuristic data analytic tool which is done both during and after data collection. It is a process of discovering, an analytic, issue-resolving method which has no specific method to pursue (Saldaña, pp. 7-8). GT data analysis method consists of three stages of coding in which codes are identified, labelled, and analysed. The primary objective of GT is to create the basic concepts from the information and develop the theoretical framework that specifies their interrelations. According to Ngulube (2015), the data coding stages in GT comprise the following: Initial coding, intermediate coding, and advanced coding.
Various grounded theorists such as Strauss and Glaser, 1967 (Traditional theorists), Corbin and Strauss, 2008 (Evolved theorists), and Charmaz, 2006 & 2014, (Constructivist) deal with the coding of data differently. Although they have similarities in the way they handle data as they embark on coding data to generate concepts and categories to construct theory, they also have differences. Table 5.1 below shows similarities and differences in coding phases in data collection and analysis of the three theorists.
131 Table 5.1: Table showing stages of grounded theory
A genre of grounded theory
Initial Intermediate Advanced
Traditional (Glaser and Strauss, 1967)
Open coding Selective coding Theoretical coding Evolved (Corbin and
Strauss, 2008)
Open coding Axial coding Selective coding Constructivist
(Charmaz, 2006)
Initial coding Focused cording Theoretical coding Source: Ngulube, 2015, p. 11.
This study has tried to follow the coding phases in accordance with Corbin and Strauss (1990, p. 12-14). Corbin and Strauss (1990, p. 12) write that, coding is a basic analytic process used in research and in GT there are three types of coding namely: open, axial, and selective coding.
These types of coding are discussed below.
5.3.3.1 Open coding
The first phase upon which one begins to examine data is open coding. At this level, one must be open about the ideas he or she wants to find in data and one ought to remain open to exploring all theoretical possibilities one can discern in the information. This stage in coding is a step towards later decisions regarding defining our core conceptual categories (Charmaz, 2014, p. 116). At this stage, data is analysed for salient concepts and categories. Codes are applied to the text by labelling phenomena. Open coding is explained by Corbin and Strauss (1990, p. 12) as, “the interpretive process by which data are broken down analytically. Its purpose is to give the analyst new insights by breaking through standard ways of thinking about interpreting phenomena reflected in data.” Open coding transforms data into codes, it is the first step of a theoretical investigation that relates to the first discovery of categories and their properties. Interviews and observations are broken down into phrases and keywords. The aim of open coding is to describe the overall features of dissecting analysis, contrasting, and labelling of the data. Ngulube (2015, p. 11) argues that open coding is articulated in the form of concepts. Concepts are the building blocks of theory development. Open coding fractures data into smaller segments that are profoundly examined. The purpose of this analysis is to grasp the core idea of each part and to develop a code to describe it. These smaller analytical
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components can then be contrasted between resemblances and variations (Vollstedt and Rezat, 2019). It is further added that:
“In open coding events, action and interactions are compared with each other for similarities and differences. They are also given conceptual labels. In this way, conceptually similar events, actions, and interactions are grouped together for form categories and subcategories. Categories can then be broken down into specific properties and their dimensions. Once identified, categories and their properties become the basis for sampling on theoretical grounds (Corbin and Strauss, 1990, p. 12).”
The main aim of open coding is to build a pool of codes with which to label the data. To achieve this aim, one may ask sensitising questions in relation to the data being analysed. This may eventually lead to discoveries (Vollstedt and Rezat, 2019). Open coding excites generative and comparative questions to guide the researcher. Posing questions permits the researcher to be open to new concerns and more probable to take note of their empirical implications (Corbin and Strauss, 1990, p. 12).
According to Vollstedt and Rezat (2019), the following questions may be posed during open coding to be able to find deep answers for analysis of data: what? Which phenomenon is described, by who? Which people are involved? Which roles do they play? Or which ones are assigned to them? How? Which aspects of the phenomenon are dealt with? Which ones are left out? When? How long? Where? In what way is the spatiotemporal dimension biographically relevant to important for single actions? Why? Which justification is given or deducible?
Where? Which strategies are used? What for? Which consequences are anticipated? In asking these sensitising questions the researcher used his or her personal and professional experiences as well as the knowledge that was gained from the relevant literature. Open coding as a process of data analysis uses a constant comparison approach to reach saturation. In open coding we continue searching for new information until new information does not provide further insight into the category. You reach saturation because there are no new illuminations of the concepts, the categories are saturated. I used open coding as presented above by Vollstedt and Rezet (2019). I was interested in how the participants, experienced and described the phenomenon of poverty and inequality. Through open coding I also observed the details of who or what was responsible for the women’s experiences of poverty and inequality. Similarly, at this stage in data collection, I looked for reasons why the women experienced the poverty and inequality in the manner they did. I also explored the consequences of poverty and inequality from what the women were sharing in the interviews. I was amenable to new ideas that were developing from
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the data. Furthermore, throughout open coding, I asked as many types of questions as possible in order to seek clarity and meaning of the phenomenon of poverty and inequality for the women of Mungwi district. In the following section axial coding is discussed.
5.3.3.2 Axial coding
Corbin and Strauss (1990, p. 13) assert that “Axial coding is the process by which categories are related to their subcategories and the relationships are tested against data. Vollstedt and Rezet (2019, p. 87) stress that “Axial coding is needed to investigate the relationship between concepts and categories that have been developed in the open coding process.” Vollstedt and Rezet (2019) reveal that according to Corbin and Strauss (1990) analysis of the data and the codes should be based on a coding paradigm. This coding paradigm should be dependent on and related to causal conditions, context, intervening conditions, action-interaction strategies and consequences. The main features of the coding paradigm have now been reduced to only three main features namely, conditions, actions-interactions and consequences (Vollstedt and Rezet, 2019). Vollstedt and Rezet (2019) further write, “As people act and interact with other people, they possess different strategies to handle their interpretations of the situation in which they are involved. Their acting, as well as the pursuit of their strategies, have consequences.
Explanations contain conditions that have an impact on one’s actions and interaction as well as the consequences that result from these.” The coding paradigm, therefore, enabled me to see relationships between concepts and categories in order to relate them to a higher level (Vollstedt and Rezat, 2019).
The coding paradigm is therefore important in axial coding and significant for theory development (Vollstedt and Rezat, 2019). Using the coding paradigm data may be broken down through the process of open coding and joined in new ways in the process of axial coding as connections are worked out between categories and its subcategories. Through axial coding the researcher explored the relationship of categories and made connections between them and that enabled the researcher to further develop categories. Categories as explained above by Murphy (2021) are a group of things that can be considered together. I formed categories out of the responses I elicited from the participants on poverty and inequality. For instance, I elicited the words culture, patriarchy and socialisation which I put into one category. Further analysis of this category of three concepts led to a subcategory of other concepts such as domination,
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discrimination, and oppression. This process was repeated with other categories of concepts used in this study.
5.3.3.3 Selective coding
Selective coding is the third step in the process of analysis in GT. The aim of selective coding is to integrate the various categories that have been developed, expounded, and jointly correlated for the duration of axial coding into one consistent theory. This is achieved by making sure that outcomes from axial coding are developed further, combined, and qualified (Vollstedt and Rezat, 2019). Selective cording is described by Corbin and Strauss (1990, p. 14) as, “the process by which all categories are unified around a core category and categories that need further explanation are filled in with descriptive detail.” According to Corbin and Strauss (1990) the core category presents the phenomenon of the study. It can be detected by posing questions such as: “what is the main analytic idea presented in this research? If my findings are to be conceptualised in a few sentences, what do I say? What does all the action/interaction seem to be about? How can I explain the variation that I see between and among the categories?” Vollstedt and Rezat, (2019) write that: “Having detected the core category the researcher knows the central phenomenon of his/her research and can finally answer the research question.” Searching for core categories in relation to poverty and inequality of the rural women of Mungwi District and eventually answering the research questions is what I endeavoured to carry out in this study.