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4.4 Analytical framework
Witdeep Primary. In 2011, essays were written by learners from Dawn Park High without my prompting that expressed their experience of the Boksburg Lake Day.
• Six statements handed to the municipality during the 2010 and 2011 Boksburg Lake Days, which expressed the learners’ feelings about the condition of Boksburg Lake and the role they would like to play in its restoration. Schools represented were Boksburg High, Goede Hoop Primary, Hoërskool Voortrekker, Reiger Park High and St Michaels Primary.
reasoning processes. This prepares the ground for discussing the RRREIC schema that relies on retrodiction.
4.4.1 Inductive and deductive philosophical approaches
Two levels of knowledge exist, namely the empirical and the theoretical (Erzberger &
Kelle 2003). Research can begin at either the empirical level (inductive approach) or theoretical level (deductive approach) and the chosen starting point affects the research process. The inductive approach is characteristically an open-ended and exploratory approach, particularly at the beginning of the research process. It begins with specific empirical observations and derives general rules and theories from patterns found in the data; it is therefore associated with hypothesis seeking (Erzberger & Kelle 2003;
Sullivan & Brockington 2004). It is adopted more for qualitative than quantitative research (Neuman 2003), but can be used to explore quantitative data (through, for example, multivariate statistics) that is designed to examine many variables simultaneously. If observed patterns are consistent this can lead to the development of a lawful relationship (Connole 1998).
The inductive approach is usually used in case study research because data is initially analysed from within its own context rather than through a predetermined theoretical lens (Eisenhardt 1989).
Rationalist philosophers such as Kant critiqued the inductive approach. They argued that observation is always theory laden, whether explicitly or not, and highlighted the importance of a pre-theoretical framework for making sense of data (Erzberger &
Kelle 2003). This debate led to the popularity of the deductive approach, which proceeds from theory to data (Connole 1998) and has been popular in quantitative methodologies (Erzberger & Kelle 2003). A theoretical framework is made explicit, from which hypotheses emerge, which are then tested against empirical data (Erzberger & Kelle 2003). A critique of this approach is that it reduces research to testing empirical data against already formulated theories, and denies the possibility of empirically based theory generation (Erzberger & Kelle 2003).
Neither of these classic philosophical approaches of the research process capture the interplay that occurs between empirical and theoretical levels of meaningful knowledge production (Erzberger & Kelle 2003; O’Leary 2004). The process can rather be seen as one that continually cycles between the empirical and theoretical
knowledge levels. Data is observed, theory is developed and then tested through further observations (Harvey 1973).
4.4.2 Grounded approach
Glaser and Strauss (1967) developed the grounded approach as a nuanced inductive research process that begins with an open and relatively unbiased process of data collection rather than testing a hypothesis (Danermark et al. 2002: 130). The aim is to ground the development of theory in data that has been systematically collected and analysed (Strauss & Corbin 1998). In the grounded approach data collection, analysis and theory development are not seen as separate, but rather different steps to be repeated in a cyclical process until additional data no longer changes the emerging theory (Glaser & Straus 1967).
Coding is the analytical process at the core of the grounded approach (Danermark et al.
2002). The initial coding is called open or substantive coding and is the first level of abstraction. In this process, every line of data is coded according to common properties emerging in the data (Danermark et al. 2002). These codes are then grouped into similar concepts to make the data more workable. As the coding process continues throughout the data, the developing concepts are compared with each other, modified and sharpened. From these concepts, categories are derived that form the basis of conceptually dense theory, made up of plausible relationships among concepts and between sets of concepts (Strauss & Corbin 1998).
The grounded approach is concerned with generating concepts with wider applicability than the context from which they were derived where conceptualisation integrates data at a higher abstract level to form theory (Danermark et al. 2002). Through this abstraction the developing theory extends its reach from the particular data from which it was derived to provide insights into different social contexts.
This case study research followed a simplified version of the grounded approach. This is supported by Gillham (2000: 12) who stated that “the case study researcher, working inductively from what’s there in the research setting develops grounded theory: theory that is grounded in the evidence that is turned up”. As he has pointed out, case study research does not start with a priori theoretical notions because, until one has experienced the context and collected data, one will not know which theories are most suitable. Rather, one collects data inductively and thereafter makes sense of it (Gillham 2000). My research journey began at the empirical rather than theoretical level as I did
not have a carefully constructed theoretical framework from which to test particular hypotheses. However, from the outset of the research process, the concept of a social- ecological system was an interpretive theoretical lens. My research design was, therefore, based on a theoretically open space that would allow the data to emerge in the context of a social-ecological system, which I wanted to understand in depth.
4.4.3 Modes of inference
The inductive and deductive philosophical approaches are associated with inductive and deductive modes of inference, respectively. Inductive inferences derive a lawful relationship from consistent empirical patterns. For example, imagine a bag of beans and up until this point, all beans taken out of the bag have been white. An inductive inference assumes that the next bean taken out of the bag will also be white. This approach is limited, as one creates a generalisation from the observations made (Mingers 2011); it cannot explain what has caused these patterns (Erzberger & Kelle 2003) and remains at the level of the empirical, providing no insight into underlying structures and mechanisms (Danermark et al. 2002).
Deductive observations derive lawful relationships based on logic rather than empirical observations. Using the same example of white beans, a deductive inference would be as follows: If all beans in this bag are white; and if this bean has been taken out of this bag; it must be white. If the premises in this example are true, then the conclusion will also be true. The limitation of the deductive mode of inference is that the development of new knowledge is limited to the premises put forward and, therefore, the particular context in which they were derived (Mingers 2011). Both inductive and deductive inferences are therefore unable to postulate generative mechanisms operating in a particular context. They remain at the level of the empirical rather than exploring the deeper structures and mechanisms of the real, which Bhaskar (1975) argued make up the largest part of reality (Danermark et al. 2002; Mingers 2011).
Abduction, retroduction and retrodiction are forms of inference that address these limitations by postulating explanations (hypothetical reasoning) for empirical findings (Erzberger & Kelle 2003). C.S. Peirce (1839-1914) is regarded as the first philosopher to conceptualise hypothetical reasoning (Erzberger & Kelle 2003). He developed the logic of abduction as an alternative mode of inference to deduction and induction:
With the process of abduction we begin with some particular occurrence or event, usually one that is unexpected or does not conform to current theories; and we then take an imaginative leap to think of some theory or explanation which might account for the
event. This is…an explanatory or exploratory hypothesis as to why the situation might have occurred… Abduction is the point where novelty, innovation and creativity enter the scientific method, as indeed they must… with abduction we get explanation and the possibility of new knowledge. (Mingers 2011: 4)
Explanations are hypothesised by firstly, drawing on a variety of theoretical perspectives, secondly, using creative reasoning processes and imagination to identify non-obvious relations and connections, and thirdly, examining how the particularly empirical manifestations would be expressed in a different context (Danermark et al.
2002).
Retroduction and retrodiction are two concepts used by Bhaskar (2010) that have a similar function to abduction. He uses these terms to distinguish between abductive inferences in natural sciences based on experimentation to identify universal laws/
generative mechanisms (retroduction) and abductive inferences in social sciences that cannot rely on experimentation to identify generative mechanisms (retrodiction). It is rather through conceptualisation and abstract theorising that retrodictive inferences move from empirical observations to elucidating underlying generative mechanisms (Carter & New 2004). The use of available social concepts and theories becomes invaluable in this process. Critical realists thus adopt retroduction and retrodiction as useful inferential tools to probe underlying generative mechanisms operating in natural and social systems respectively (Danermark et al. 2002).
4.4.4 RRREIC schema
Bhaskar developed the DREIC schema for natural science that relies on experimentation within closed systems. The DREIC schema stands for D: description of the phenomena of interest; R: application of retroductive inferences to hypothesise generative mechanisms that, if they existed would account for the phenomena observed; E: eliminate the least likely hypotheses; I: identify the most likely correct mechanisms, and C: correct identified mechanisms through further engagement with colleagues and theory (Mingers 2011).
The RRREIC schema has been developed for the applied and social sciences that work in open systems. In this case, retrodiction is the inferential tool used to postulate generative mechanisms (Danermark et al. 2002). The RRREIC schema makes more refined use of theory and stands for: 1R: resolution of the complex event or research focus into its components and associated relations; 2R: redescription of these
causes, supported by theoretical perspectives E: eliminate, I: identify and C: correct, as highlighted above (Bhaskar 2010).
The first three Rs in the RRREIC schema were used in this study to identify underlying generative mechanisms. The first two steps (resolution and redescription) are well suited to a grounded theory approach, while retrodiction provides a space for a strong theoretical emphasis. The grounded approach was used to resolve (1R) my data into its components (through coding) and associated relations (through conceptualisation and categorisation). These components were then redescribed (2R) into theoretically condensed categories, and written up as my data representations (chapter 6 and 7). The represented data for each applicable chapter was then read through a number of times to identify all emergent themes. Similar themes were clustered and from this, key analytical statements (meaningful statements) were derived (Bassey 1999). These analytical statements were therefore strongly grounded in the data. Theory was then used to postulate causality associated with each statement in a retrodictive process (R3). Theory included both normative theory (which argues for the way things should be and focuses on moral, political or ideological issues) and descriptive theory (which helps one understand the factors at play) (Danermark et al. 2002). The analytical statements with their theoretical explanations, structure the discussion components of chapters 6 and 7.
Now that a broad description of the analytical process has been provided, the chapter ends with an explanation of my ethical position.