Conceptually, the way that we understand the world (reality) is based on a particular paradigm. Kuhn (1970) popularised the term ‘paradigm’, which he described as sets of linked assumptions, concepts and common language about the way the world works. The notion of a paradigm contains elements that provide the means to examine problems, to understand situations and, under certain circumstances, to propose solutions. However, the use of the term paradigm has been expanded to a wide variety of interpretations and is often used loosely, even by Kuhn (1970) as well as others (Guba, 1990).
Once a paradigm is chosen, the philosophy of that paradigm will dictate its assumptions and practice. These are components of the mental models of the intended problem-solver, all of which are simpler representations of the real world, constructions to help make sense of complicated and complex situations.
The way in which we comprehend the world around us is an ongoing and
contentious debate in the philosophy of science and is often framed in terms of dichotomies, for example, between constructivism and positivism, or holistic and reductionist. In this chapter we explore three frameworks for representing the tension between alternative ways in which reality is represented.
The analysis of alternative assumptions of how we understand reality and portray that reality was once more commonly the subject matter of the social sciences (Burrell and Morgan, 1979; Guba, 1990). It is not normally felt to be necessary for advocates of the traditional or normal scientific approach to analyse the theoretical presuppositions of paradigms because the ontology, epistemology and methodology (see Section 4.3.1) is assumed to be positivist, although this once strongly held position is changing. The literature warns of going beyond the normal scientific paradigm (Soulé, 1995). In an interdisciplinary synthesis of the ‘nature of nature’, radical forms of ‘post- modern deconstructivism’ were critically analysed and it was proposed that such a dialogue could be just as destructive as chainsaws and bulldozers in the process of nature conservation (Soulé, 1995). Soulé (1995) challenged theorists who engaged in constructivist dialogue to do so with the aim of protecting nature.
Increasingly, natural resource problems are seen as having a social component requiring better understanding of social science paradigms and theory. So it is with the ethos of helping to understand the complex relationships between people and nature and to protect nature that we undertake this analysis.
4.3.1 Ontology, epistemology, human nature and methodology Paradigms may be considered as models for understanding reality and are described using the following categories: ontology, epistemology, human nature and methodology (Burrell and Morgan, 1979) (Figure 4.1).
The subjective approach to organisational analysis Nominalism Anti-positivism Voluntarism Ideographic
The objective approach to organisational analysis
Realism Positivism Determinism Nomothetic ontology
epistemology human nature methodology
Fig. 4.1. The subjective–objective dichotomy for analysing assumptions about the nature of social science.Source:Burrell and Morgan (1979)
Table 4.1.Ontology, epistemology, human nature and methodology
Ontology Epistemology Human nature Methodology
Relates to the nature of existence
Relates to the nature and understanding of knowledge, the theory of how knowledge is constructed
Relates to the relationship between human beings and their environment
Relates to the process of understanding
What is the nature of the knowable, or what is the nature of reality?
What is the nature of the relationship between the knower (the inquirer) and the known (or knowledge)?
What is the nature of the relationship between the knower and their environment?
How should the enquirer go about developing new knowledge?
In this figure the extreme dichotomies are identified between the subjective–
objective approaches to organisational analysis. Methodologies are guided by ontological, epistemological positions and human nature, and will in turn guide the choices of method and recording techniques employed, and how results are interpreted and reported (Table 4.1). The recording technique or the way information is captured is a sub-component of the methodology. Any discussion of these concepts necessarily overlaps and one cannot discuss one without the other or necessarily separate them.
4.3.2 Normal science paradigm
Normal science is that body of research which has as its basis a body of accepted theory and methods, concepts, definitions and procedures and is often referred to as a paradigm. During the twentieth century, until the mid 1970s normal science was the dominant orthodoxy of inquiry for the physical and natural sciences. However, from the mid 1970s, the normal science paradigm became contested even while still widely practised (Ziman, 2000; Gauch, 2003). It was proposed that normal science was practised and justified under certain conditions according to this line of reasoning because of the lack of worthy theoretical and methodological alternatives (Norgaard, 1989).
The normal science paradigm has a number of assumptions (Table 4.2).
For example, it assumes that there is certainty in decisions and that
Table 4.2.Assumptions and characteristics of the normal science paradigm
problem solving one ‘truth’ or best answer
averages always dominate assumed predictability context not very
relevant
reversibility
certainty observer status
objective
externalities not important
control focusses on parts equilibrium
determinism analysis reduction asymptotic stability single linear causality structural constancy rationality
Sources: Bawden et al. (1985); Funtowicz and Ravetz (1990);
Tognetti (1999); Rosenberg (2000); Hollinget al. (2002b)
decision-makers can predict, manage and control outcomes in the environ- ment (Bawden et al., 1985; Funtowicz and Ravetz, 1990; Tognetti, 1999;
Rosenberg, 2000; Holling et al., 2002b). In addition the paradigm assumes a mechanistic world ruled by deductive logic and mathematics in which equilibrium-centred thinking dominates (De Greene, 1993). It is assumed that natural resources can be controlled through the process of acquiring enough information, which combined with computer power results in the ability to predict the spatial and temporal environmental outcomes with certainty (Tognetti, 1999). The normal science paradigm is a problem-solving paradigm, which in the Hawkesbury Hierarchy of approaches to problem- solving and situation improvement (Bawden et al., 1985) is most suited to problems classified as basic research (Table 4.3).
The foremost methodology within the normal science paradigm was empir- ical experimentalism (the hypothetico-deductive method (Romesburg, 1981) also known as the scientific or nomothetic method) (Figure 4.1). This method is usually identified by four steps (Stokes, 1998):
1. observation and description of a phenomenon or problem;
2. formulation of a hypothesis to explain the phenomenon: in physics, the hypothesis often takes the form of a causal mechanism or a mathematical relationship;
3. use of the hypothesis to predict the existence of other phenomena, or to predict quantitatively the results of new observations; and
4. performance of experimental tests of the predictions by several independent experimenters and properly performed experiments.
Table 4.3.The Hawkesbury Hierarchy of approaches to problem-solving and situation improvement
Problem focus Classification Outcomes
Given this complex problem situation, how can I improve the situation?
Soft systems research Client satisfaction
Given this system, how can I optimise its performance?
Hard systems research Performance optimisation Given this component,
how can I improve its effectiveness?
Applied research Problem resolution
Given the phenomenon, why is it so?
Basic research Puzzle resolution
Source:Bawdenet al. (1985)
This method relies on the use of standard scientific techniques and procedures for gathering, sorting, processing and applying information. It also involves a peer review process for ensuring the standard quality and validity of results.
This process also serves to maintain the survival of the paradigm. These techniques are appropriate for situations with high levels of certainty and low levels of risk, characteristics not often found in social and biological systems.