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As described in Chapter Three, the methods of research move from coding, to categories, to themes, to discourses and is adapted from a combination of Charmaz’s (2006) constructivist grounded theory and Carabine’s (2001) genealogical discourse analysis. Using this type of discourse analysis means that if these methods were to be carried out in exactly the same way again, the results might well be different, because of the spatial and temporal dependence of the data collected and the interpretative nature of the analysis. Nevertheless, the methods should be replicable and generally applicable. This chapter combines a description of the methods along with initial results, to explain the procedures of the analysis. Examples are given throughout to demonstrate the methods and also, in line with poststructural theory, to be as explicit as possible so that readers can scrutinise the analysis and potentially develop new insights for themselves.
Coding
To begin with, codes were described in a process termed open coding. Over time, the names of the codes were clarified and refined so that the key concepts and nuances of meaning were effectively captured. From this point the code names remain unchanged and were termed ‘initial codes’ (Charmaz 2006, p. 48). This demonstrates how the first step of analysis is a complicated, lengthy, multi-step procedure that is essentially about getting to know the data as richly as possible. Figure 2 is an example of how coding works using NVivo.
Figure 2: Screenshot showing coding.
Source: NVivo 2009, personal file.
In Figure 2, there are a series of coloured bars depicting the segments of parallel text that have been coded following Charmaz (2006). There are two codes visible: ‘Describes a current or potential threat’ (green bar) and ‘Complains about the fairness of responding to climate change’ (yellow bar).
Open coding
In the process of naming the codes, memos are written to describe individual codes, to compare them to other codes, to detail their characteristics, how they might be recognised in the transcripts, and what their limits are. These memos are written in response to questions and they form part of the coding analysis process. Examples of these questions include: Why is this code different from another? Why is it significant enough to stand alone as a new code? Why has it been given
that particular name? Does the name describe what is occurring in the transcript? What concepts are included in the code? What concepts are excluded?
NVivo software was used throughout the analysis to structure and store the transcripts, memos and the developing codes, and to help allow easy access, refinement, notations and connections at all points of analysis. Below is an example, taken from NVivo, of part of a memo written during the open coding process.
Box 4: Memo excerpt.
The memo demonstrates how the differences and connections between codes are an important part of the process of the coding analysis. It also shows how the naming of codes is a significant step because it constructs, defines and limits the phenomena that are found in the transcripts. The codes described in the memo belong to the initial codes ‘expresses uncertainty about climate change as reality or as actionable’ and ‘pinpoints specific needs for more information’ (see Table 3). This demonstrates how settling on the names of codes – the movement from open coding to initial coding – is part of the process of analysis which creates a unique and personal interpretation.
Information and Uncertainty codes
The difference between uncertainty and more information is quite fine but important, uncertainty is the unknown, with no way of knowing how to make it known. More information is specific to needs or complaints about information that is lacking. More information also includes attempts to get more information, positive assumptions that more information is out there or will be forthcoming and support for research and education. Uncertainty is more disabling as a restriction or as evidence that action is pointless or unnecessary or too early (therefore it is a barrier, while more information is a way forward). Uncertainty is also fuel for doubt, scepticism and distrust whereas more information is based on general acceptance and gives impetus for moving forward.
Initial coding
The final names of the codes use present tense verbs in an attempt to capture the active purpose in the phenomena being described (Charmaz 2006). The codes were informed by the researcher’s theoretical sensitivity (Strauss & Corbin 1998), and directed toward answering the research question: what are the reasons for farmers’ resistance to climate change? Therefore, the codes are about understandings of climate change and evidence of action and barriers to action, rather than, for example, about farmers’ use of water, which might be a relevant code for a different study of climate change and was strongly present in the transcripts collected. Through this process, the large number of open codes found is reduced to the initial codes relevant to this research and those listed here are quite particular and unique to this analysis and form the first level of sorting or limiting the data.
The initial codes created from the data are listed in Table 3. Numbers are for reference and recording purposes and not for ranking. Similarly, the frequency of codes is useful for describing and showing relationships between codes and for providing a record of the analysis but it is not intended that they be used for establishing an order of importance. Recording the frequency of the codes is the first step in identifying discursive patterns in the transcripts.
Table 3: Initial codes.
Code name and number Frequency
1. makes observations about landscape change 69
2. advocates adaptation 34
3. advocates personal actions 126
4. advocates industry actions 66
5. advocates social actions 40
6. advocates government actions 41
7. connects emotionally with an image of people 9
8. connects emotionally with an image of problems 6
9. connects emotionally with an image of nature 19
10. demonstrates a negative emotional reaction to the topic 22
11. demonstrates conflation of different issues 37
12. describes a current or potential threat 108
13. expresses a worry for the future 69
14. expresses the urgency of action 10
15. describes the complexity of climate change 19
16. expresses distrust in science and/or government 77
17. expresses uncertainty about climate change as reality or as actionable
77
18. emphasises economic viability 46
19. values environmental stewardship 33
20. expresses concern about natural resource limits, scarcity and control
43
21. advocates working together 13
22. emphasises the power of social networks 18
23. sees opportunity for Tasmania in a changed climate 133
24. distrusts the media hype 45
25. highlights/agrees with the scepticism about climate change 57
26. believes climate changes are caused by natural cycles 86
27. believes Mother Nature is beyond human influence 17
28. complains about the fairness of responding to climate change 77
29. believes there is time to act later 35
30. emphasises other issues as more important 87
31. states climate change is a non-issue 16
32. points out the limitations of social norms 13
33. states that personal actions are pointless 28
34. points out the limitations of infrastructure 8
35. accepts the scientific evidence of climate change 55
36. pinpoints specific needs for more information 33
37. assumes a technology fix can and will be found 27
38. places trust in science 39
39. discusses government responsibility 60
40. describes industry progress 67
41. feels out of control of the future 46
Identifying themes/memo writing and category formation
During the open coding process, the codes were named with key words and stored in the ‘Free nodes’ section of NVivo. Detailed descriptions about each code were recorded in NVivo memos in order to keep a record of the types of meanings included at particular codes. This process represents the beginning of identifying themes. Open coding name changes were recorded and explained and examples or key words noted in the properties function of NVivo to help keep codes authentic, relevant, comprehensive and distinct. This technique was also used to clarify any confusion between codes that had some overlap. The final coding names are the initial codes. These were described in more detail in memos to help start the process of identifying connections between them that would allow them to be grouped into categories. Memos were also used to reflect on why some codes were more prevalent in the transcripts than others.
After all the interview transcripts had been coded, a list of all codes created was generated. This was then analysed and grouped into categories in a process termed ‘axial coding’ (Strauss & Corbin 1998, p. 96). Concepts were ‘grouped together under a higher order, more abstract concept called a category’ (Strauss & Corbin 1998, p. 61). Each code contributes to only one category. The categories were created in a way that helped to add further depth to the scope of the codes, and the process used memos to identify similarities and points of connection. For example, codes that achieved the same purpose but in different ways, or focused on different aspects of the same concept, were grouped together. Descriptions of each category were written up to draw out the connections between the codes and to indicate how they overlap to reinforce particular ideas, or approach a particular concept in different ways. Again, this was not a one-step process; much reflection and re-reading of the transcripts, experimenting and rearranging the codes into different hierarchies in NVivo and writing memos of ideas and evaluating these, led to the development of the categories. An initial hurdle was encountered by grouping the codes into those with similar names, rather than grouping the codes with the same function, e.g. code 39, discusses government responsibility is more
aligned with code 33, states that personal actions are pointless, rather than code 6, advocates government action.
The memos at the category stage also suggested potential themes and these ideas were highlighted and expanded in memos, exploring their connections to initial codes, to observations and to the literature. This allowed a kind of theoretical test of the potential discourses. Exploring connections in this way, both theoretically and practically within the data, foreshadowed looking for interrelationships among discourses. In this way, the analysis process is not linear, but rather multiple points happen at once, and different points of analysis can be revisited and revised.
Figure 3: Screenshot showing the hierarchy of codes, categories and themes/potential discourses.
Source: Nvivo 2009, personal file.
Figure 3 shows the hierarchy of codes, categories and potential discourses in NVivo. The theme or potential discourse shown is ‘Human Responsibility’ with four categories visible: ‘Action’, ‘Barriers to Action’, ‘People power’ and
‘Responsibility’. The remaining icons belong to codes placed under their respective category.
Axial coding – constructing categories
From the list of initial codes, axial coding is the first step in grouping the codes to a higher level of abstraction, in which more layers and complexities of meaning can be created. Axial coding is: ‘a set of procedures whereby data are put back together in new ways after open coding’ (Strauss & Corbin 1998, p. 96). This process is achieved by connecting and comparing codes and checking them against the interview transcripts.
The process of axial coding, that is, the construction of categories, follows a similar path to that from open coding to initial coding. Axial coding is a more flexible and exploratory part of the development of categories. Again, memo writing is an important tool for moving the analysis forward (Charmaz 2006). Memos are written to describe connections between codes and to explore tentative category names, to detail their characteristics, how they occur, what their limits are, and what they might contribute to understandings of the research question. As in the coding process, these memos are written in response to posed questions. Sample questions include: What connects the codes? What differentiates them? What new concepts are gained by connecting the codes? Is this new concept still consistent with each code individually? Is it relevant to the research question? Are all the codes active in creating this new concept? Are all the codes relevant to this concept included? These questions have the purpose of drawing out the relationship between codes and form the first stage of the development of categories. Below is an example of part of a memo taken from NVivo, during the axial coding process.
Box 5: Memo excerpt.
The above memo is titled hip pocket as an ‘in vivo’ category name – originally a term used by the interviewees that was utilised in the analysis. This title was later rejected because it was too limited in representing the defining concept of the category and instead the category was later named Business viability (see below). This demonstrates that, as with the naming of codes, the naming of categories is a significant part of the analysis process.
Categories
The final contents and name of each category was decided after a process of detailed analysis, questioning and exploration, verified at the end of each cycle against interview transcripts, to make sure that the category concepts were still relevant and consistent. Table 4 presents a list of categories and the codes that are connected to form that category. As with the codes, each category is numbered as a means of labelling and recording, not as a means of ranking. A combined total of the codes are given as an indicator of the prevalence of the category in the data. As this research is qualitative, not quantitative, these numbers offer interesting insights and comparisons, but are not meaningful beyond a record of the prevalence of the codes in the original data. Following the sorting of the codes into categories, each category was described individually in order to make explicit the ways that the particular combination of codes created adds a conceptual understanding that is relevant to understanding farmers’ responses to climate change.
Hip pocket
This category is about finances, growth and competition. It is about how climate change can be fixed by market solutions, and therefore is cannot be fixed yet, because cost effective solutions (technological) and consumer demand are not high enough. It is about how climate change represents a cost to the public in general and farmers specifically, and how it is increasingly hard to maintain profit with competition from the world market, consumer ambivalence, supermarket monopolies and marketing and government requirements, of which the carbon pollution reduction scheme is the latest addition and possibly will push many farmers over the brink of viability. The consequences of this category are that climate change is seen as a cost, as a threat to the current way of business and to the economic stability of Australia.
Table 4: Categories.
Category Name and Number
Codes included Combined
Frequency
1.Business viability
12. describes a current or potential threat
18. emphasises the importance of economic viability 23. sees opportunity for Tasmania in a changed climate 30. emphasises other issues as more important
374
2. Action 3. advocates personal actions 4. advocates industry actions 5. advocates social actions 6. advocates government actions
273
3. Global equity 10. demonstrates a negative emotional reaction to the topic
28. complains about the fairness of responding to climate change
33. states that personal actions are pointless 39. discusses government responsibility
187
4. Responsibility 1. makes observations about landscape change 8. connects emotionally with an image of problems 14. expresses the urgency of action
19. values environmental stewardship
35. accepts the scientific evidence of climate change
173
5. Community 7. connects emotionally with an image of people 21. advocates working together
22. emphasises the power of social networks
40
6. Waiting 36. pinpoints specific needs for more information 42. believes climate is a problem for future generations
59 7. Barriers to
action
32. points out the limitations of social norms 34. points out the limitations of infrastructure 41. feels out of control of the future
67
8. Faith 2. advocates adaptation
29. believes there is time to act later 31. states climate change is a non-issue
85
9. Mother Nature 26. believes climate changes are caused by natural cycles 27. believes Mother Nature is beyond human influence 9. connects emotionally with an image of nature
122
10. Market solutions
37. assumes a technology fix can and will be found 38. places trust in science
40. describes industry progress
133
11. Confusion 11. demonstrates conflation of different issues 15. describes the complexity of climate change
17. expresses uncertainty about climate change as reality or as actionable
133
12. Distrust and scepticism
16. distrusts science and/or government 24. distrusts the media hype
25. highlights/agrees with the scepticism about climate change
179
13. Resource limits
13. expresses a worry for the future
20. expresses concern about natural resource limits
Category One: Business viability
Business viability connects the codes that express the importance of keeping the farming business viable and profitable. These codes are: code 12, describes a current or potential threat; code 18, emphasises economic viability; code 23, sees opportunity for Tasmania in a changed climate; and code 30, emphasises other issues as more important.
In this category, climate change is not perceived as bringing significant changes to Tasmania, and opportunity will come through production capacity remaining the same, or increasing slightly. Tasmania is seen to be sheltered from severe impacts, while other competitors, interstate and overseas, struggle with more serious changes. An example demonstrating this is: ‘Tasmania probably has an advantage to gain from the weather fluctuating as wildly as it is in the rest of the world and we’ve got a relatively temperate climate here still, it’s really interesting. I think we’ve got big opportunities with climate change if we go along carefully.’ Apple grower.
As climate change is not perceived as bringing too many physical changes to production capacity, other issues of business viability are more important and immediate, including the global financial crisis that was developing at the time, labour shortages, constraints of free trade, supermarket monopolies, decreasing markets and returns, political decisions and increasing costs of production. Compared to these other issues, climate change seems to be a passing fad: ‘Time is very, very valuable and we’re all under pressure, so growers are really in survival mode mostly and growers can’t be running all the time with every latest issue of public interest.’ Apple grower.
The dominant concerns of farmers in this category relate to the economic viability of their business, and while the connection between the drought and rising prices of grain and fertiliser is accepted, climate change is not perceived as a major factor in influencing financial concerns. The end result is that as long as there is water – and it is assumed that there will be – climate change will mean
that things will be no different, or comparatively better, for Tasmania. An example of how climate change is likely to advantage Tasmania, with the assumption of sufficient water, is:
Some cold, frosty mornings you think, roll on climate change! (laughs) In the middle of winter, when it’s freezing cold, I can’t