Inner Mongolia
5. DATA ANALYSIS 1 Qualitative data 1 Qualitative data
The research involved four sources of qualitative data: 1) the answers to open-ended survey questions; 2) records and notes from interviews; 3) records and notes from focus group discussions; and 4) notes from participant observation. The data analysis was based on the grounded theory approach and its coding procedure. Grounded theory allowed me to follow an inductive approach to building a perspective on the research outcomes. As Strauss and Corbin (1990:23) suggest, grounded theory can be carried out when “one does not begin with a theory, then prove it. Rather, one begins with an area of theory and what is relevant to that area is allowed to emerge”. The study of TEK differs from the conventional Western research approach of hypothesis (before going into the field) and validation (in the field) (Lalonde, 1993). Wolfe et al. (1991) provide a
comparison between the TEK knowledge system and modern scientific knowledge system. There are several fundamental differences between them. TEK is commonly based on a holistic worldview. It then positions humans as subordinate to nature. On the contrary, the Western scientific approach is based on a reductionist worldview, and recognises humans as being able to play a dominant role over nature. Accordingly, TEK is presented and communicated through intuitive, oral and spiritual forms (e.g. oral history and rituals), while Western science follows an analytical and literary/academic approach (e.g. hypothesis and laws). Reflecting these fundamental differences, the research and analytical methods applied to TEK can be expected to differ from the conventional scientific ones.
Grounded theory was also a critical tool to help avoid potential bias and
misunderstanding related to local knowledge. For example, following a grounded theory approach, I tended to avoid any hypothesis or prediction before collecting data. During the data analysis, the results were produced based on the data collected from the survey only. This helped to remove the bias that stemmed from my own perspective and other literature (Charmaz, 2006).
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There were three sources of data that contributed to the formation of the typologies: the survey results, the literature review and the results from the case study in Inner
Mongolia. In contrast to methodology applied to the quantitative data analysis (e.g. on the geographic distribution of TEK studies and overall trends of TEK change) which was conducted separately from the literature review and the survey, I decided to combine the qualitative data from different sources to form unified TEK typologies. This is
because the typologies support a comprehensive understanding of all possible threats to TEK and all available conservation actions at the global scale. Thus, there is no point in separating the results from the survey, the literature review and the case study for the purpose of differentiation or comparison; rather, they supplement one another and contribute to the formation of the synthesised typologies. To create the typologies using these diverse sources of information, I applied the three-step coding procedure of grounded theory, i.e. open coding, axial coding and selective coding (Strauss and Corbin, 1997). For example, to analyse the data regarding direct threats to TEK:
Open coding – I broke down, examined and compared the original data in order to abstract and conceptualise it. Then I grouped the data into categories.
Axial coding – According to causal conditions and intervening conditions, I
reassembled the data in new ways and identified connections between categories.
Selective coding – This was the final part of the coding procedure. It was also a further step of axial coding with more abstract selection. I eventually selected six categories and produced my own grounded theory related to the research topic.
Adjustments were also made according to the feedback from 17 experts.
5.2 Quantitative data
For the quantitative data which were generated from the survey and the literature, I applied descriptive quantitative statistics to present the data in aggregate by using Qualitrics data analysis tools (an online survey tool) and Microsoft Excel. I used this approach to analyse variation in: 1) responses’ geographical distribution; 2) the overall trend of TEK change; and 3) the significance of different categories of TEK threats and conservation options.
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For all three targets, the first step was to tabulate the data for the different variables (e.g.
different geo-regions, different scales of TEK change, and different categories of TEK threats and conservation options). Then percentage distribution was applied to reveal the geographical distribution of survey responses, and frequency distribution was used to present the trends for TEK change (Robson, 2002)18. After using qualitative data analysis to develop the categories of the TEK typologies, the data for each category of TEK threats and conservation actions were disaggregated, and ratios among these categories were produced (Bernard, 2010; Bryman, 2008). These ratios represent the significance of each category identified by the survey respondents and in the literature.
6. LIMITATIONS
The most significant limitation of this research was the limited number of survey
responses. Ideally, the survey should be carried out evenly in each country or region and should seek ample representation from all key stakeholder groups: community
members, researchers and organisations. This was not possible due to financial,
logistical and time constraints of this research. As an individual PhD student researcher, my capacity to reach potential respondents was limited mostly to internet
communication and international conferences. As a result, I have to be very careful to qualify conclusions about the global patterns produced from my research. Even though the responses to the survey were from 48 countries and regions, the representation from each country and region was limited. For example, the survey had 34 responses from India, 12 from Canada and 14 from USA, while only one response was received from Benin, Russia and the Congo. In turn, the results from these countries were not very comparable. Thus, I only presented comparisons between larger geographical regions (Africa, Asia, North America, South America, Europe and Oceania), instead of between individual countries.
18 The questionnaire gave eight scales of TEK change – dramatic gain, gain, slight gain, no change, slight loss, loss, dramatic loss and other. See Appendix 5 for examples.
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The second limitation is the source of information. Although the information from community members is more direct and firsthand, due to the financial constraint, I could not distribute the questionnaire to communities in person and had to rely on the internet as my main tool for surveying. The most accessible respondents via internet communication were researchers19. Applying the concepts from cultural anthropology here, much of the data collected through the questionnaire and its follow-up interviews were etic (outsiders’ views)20, rather than emic (insiders’ views)21. As Headland et al.
(1990) note, social scientists have long debated whether their knowledge is objective or subjective. The objectivity of researchers’ observation and opinions is a concern of this research. The information provided by the researchers and practitioners may contain their personal or professional bias and judgment, which may lead to some bias in the results.
Despite the above limitations, the results of this research are still valuable in terms of an initial attempt to create globally applicable typologies for TEK threats and actions; in the future, more thorough surveys can further hone the classification. Ideally, this process could resemble the long, collective development of the IUCN classifications of threats to and actions for biodiversity, which involves multiple organisations and researchers, and has been tested over thousands of cases through its network (Salafsky et al., 2008). For future research, there are two urgent needs: 1) collecting more data from each country more evenly and thoroughly; and 2) comprehensively testing the typologies in various locations and cases.
There are also limitations to the case study. First, the cooperative activities (both on the research site and in wider China) have only been active for a short period of time. Their long term effects on recovering traditional institutions and wider aspects of TEK, as well as on community empowerment, need long-term monitoring and further research.
19 Accounting for 74% of the total respondents.
20 Etic is a description of a behaviour or belief by an observer, in terms that can be applied to other cultures (Morris et al., 1999).
21 Emic is a description of behaviour or a belief in terms meaningful (consciously or unconsciously) to the actor; that is, an emic account comes from a person within the culture (Morris et al., 1999).
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Second, the implementation of the Cooperative Law and assisting policies may vary in different locations. Local governments will play a critical role in determining the degree of legal enforcement. In turn, the law could lead to different cooperative development at the local level, and ultimately have different effects on TEK and its revitalisation. Lastly, TEK is not a homogeneous system of thought; TEK may vary enormously among
different cultural groups and ecosystems. Thus, the conclusions from this research in Inner Mongolia are not necessarily applicable to other locations and other TEK systems.
So far, this research has been the first to focus on the effects of the Cooperative Law on TEK and TEK conservation in Inner Mongolia and China. I hope it may inspire further research in this field and in wider areas of the world.
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