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In-Depth Information
3.1
Participant Observation and Participatory Methods
Participant observation allows for detailed contextualization and analysis of both
material and subjective processes which form the experience of actors within a system
[10, 16]. At the early fieldwork stages, several months were spent in each of Mbirika-
ni and Eselenkei Group Ranches, accompanying participants in their daily activities to
gain an understanding of how users perceive the rangeland, the parameters of the
system and the decision-making processes in utilizing the resources within it [17].
The information gained on these walks was triangulated through informal discussions
with a range of different user groups including women, herders and elders in order to
gain multiple perspectives.
3.2
Semi-structured Interviews and Focus Groups
Purposive sampling was used to identify interview respondents from households lo-
cated throughout the study area. Sample size was greater than 30 in each of the Group
Ranches [18] and included a wide range of interests and 'multiple realities' to develop
a conceptual theory of decision-making processes in the system [19]. Topics included
in interview schedules were livelihood activities, natural resource use over space and
time, other actors and institutions, perceived socio-economic and environmental
changes and the drivers of change, particularly with reference to the 2009 drought, as
well as plans for the future.
A technique that was used during this work was discussions of scenarios and “what
if?” situations. This approach helped to increase participation, depersonalize discus-
sions, protect the privacy of other participants, and frame issues more effectively.
Comprehensive notes were taken during interviews and field notes taken during par-
ticipant observation and informal discussions. A field diary was kept on a daily basis
also to ensure other information was captured.
4
Developing Behavioural Rules for Agents
4.1
Qualitative Data Analysis
Thematic analysis of transcripts and field notes was undertaken after the first and
second field visits [20]. Particular care was taken to avoid biases, high-inference de-
scriptors and jumping to conclusions too early [21] by sequentially coding the materi-
al by hand, starting first with descriptive codes and then more analytical coding to
establish meaning as well as content [22].
NVivo software was used as a means of identifying broad-scale categories of in-
formation from secondary data such as policy documents and the wealth of informa-
tion captured in previous studies undertaken in the area. In undertaking this analysis,
particular emphasis was placed on reconstructing the perspectives of the research
participants, incorporating emic interpretations of the system. Data were analyzed
iteratively so that researcher and participant perspectives were appropriately
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