Nov 12, 2011

Snowball sampling is the research method that works best in conflict zones

From the article "Field research in conflict environments: Methodological challenges and snowball sampling" by Cohen and Arieli, published in the Journal of Peace Research (July 2011). Alas, I could not find the paper online. 
This article addresses the central methodological problems of research conducted in conflict environments. We suggest the use of the snowball sampling method (hereafter, SSM) as an answer to these challenges. The effectiveness of this method has been recognized as significant in a variety of cases, mainly regarding marginalized populations. We claim that in conflict environments, the entire population is marginalized to some degree, making it ‘hidden’ from and ‘hard to reach’ for the outsider researcher. The marginalization explains why it is difficult to locate, access and enlist the cooperation of the research populations, which in a non-conflict context would not have been difficult to do. SSM directly addresses the fears and mistrust common to the conflict environment and increases the likelihood of trusting the researcher by introduction through a trusted social network. We demonstrate how careful use of SSM as a ‘second best’ but still valuable methodology can help generate cooperation. Therefore, the evaluation of SSM, its advantages and limitations in implementation in conflict environments can be an important contribution to the methodological training of researchers. In addition to its effectiveness under conditions of conflict, SSM may, in some cases, actually make the difference between research conducted under constrained conditions and research not conducted at all. Together with our experiences in the field, we supply several insights and recommendations for optimizing the use of SSM in a conflict environment.
What is SSM (from Wikipedia):
[I]s a non-probability sampling technique where existing study subjects recruit future subjects from among their acquaintances. Thus the sample group appears to grow like a rolling snowball. As the sample builds up, enough data is gathered to be useful for research. This sampling technique is often used in hidden populations which are difficult for researchers to access; example populations would be drug users or sex workers. As sample members are not selected from a sampling frame, snowball samples are subject to numerous biases. For example, people who have many friends are more likely to be recruited into the sample.

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