Objective: In this presentation, I argue that bias is essential for conducting excellent qualitative inquiry. Rather than avoiding bias, qualitative researchers must use bias by deliberately maximizing the phenomena, the event or the instance they are exploring.
Rationale: Quantitative techniques of randomization and selecting the average or typical example (rather than the extreme), makes it difficult in qualitative research to identify characteristics and to decontextualize concepts. Consistent with the principles of science, a pure substance renders insight into the composition of substances more quickly than contaminated samples. Such is the case for the discovery of the characteristics of concepts using the best, rather than an average example as data. Further, randomization increases the amount of data collected about common events, and provides inadequate data for saturation on the less common events, hence works to invalidate inquiry.
Methods: Principles for maximizing bias that will be discussed include: purposively directed sampling, representative of the phenomena, rather that the population, so that the results contribute effectively and efficiently towards understanding. Further, techniques of abduction, verification and saturation to prevent error, misinterpretation and distortion of the results. I also will discuss the consequences and costs of attempting to avoid bias, and the pitfalls of biasphobia.
Conclusions: The use of bias is essential for “good” qualitative inquiry, for obtaining results are to move beyond the obvious. A lack of understanding of qualitative principles, fear of discovery, or adherence to the principles of quantitative inquiry, are inhibitors to qualitative inquiry.
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