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Accepted Paper:

Identifying and mitigating research bias with GIS  

Author:

Keiko Kanno (University of Oxford)

Paper short abstract:

Drawing on my fieldwork with GIS in rural, urban, and peri-urban Mongolia, I will explore to what extent GIS could identify and mitigate research bias and its potential limitations in ethnographic research.

Paper long abstract:

Recognising and understanding potential research bias in a study is crucial, as such bias may significantly distort the results of a study (Galdas, 2017; Polit & Beck, 2014). For instance, sampling bias occurs from having underrepresented groups, and nonresponse bias occurs when some sampled subjects cannot be reached (Agresti & Finlay, 2009). Some groups of people who have nomadic lifestyles in rural Mongolia are often excluded from health-related studies, an especially intractable problem among the many nomadic peoples of Mongolia. Fieldwork with GIS enables ethnographers to recognise and mitigate such biases and make adjustments during the fieldwork to make a more valuable end product. GIS can also be used to cross-check data when different methods are used to repeat the initial work with a new twist to increase accuracy. Drawing on my fieldwork with GIS in rural, urban, and peri-urban Mongolia, I will explore to what extent GIS could identify and mitigate research bias and its potential limitations in ethnographic research.

Panel ME07
Ethnography and GIS