Yesterday, BBC News published a short article based on a radio program featuring Malcolm Gladwell. Gladwell’s radio presentation was entitled Listening in Vietnam. The article drawn from the program was entitled Could One Man Have Shortened the Vietnam War? Both pieces are instructive for interviewers on the art of listening without bias.
Gladwell tells the story of the Vietnam War “morale project” conducted by the U.S. government. Essentially, as Gladwell tells it, the government wanted to collect evidence on what it would take to break the will of the North Vietnamese, an enemy about which little was known and little was understood. Leon Goure gathered interview data to help the Americans understand “what the North Vietnamese were thinking.” Sixty-one thousand pages of interview transcripts were created, translated, and analyzed for this project. Goure concluded that the North Vietnamese were demoralized and about to give up. Just a little more bombing was needed. Goure’s findings “formed the justification for U.S. policy in Vietnam.”
However, another researcher, named Konrad Kellen, reached a different conclusion based on the very same interviews. He concluded that the U.S. could not win the war. Why? He read the transcripts carefully and objectively. He “listened” to every word. He noticed contradictions and created a theory that would make sense of them. Goure, on the other hand, read the interviews through the lens of his own assumptions and biases. He disregarded information that did not support his foregone conclusions. Time proved Kellen correct; but the people who shared Goure’s biases were the ones setting policy.
The lessons for qualitative researchers? Gathering information through interviews is only part of the job. Interpreting — making sense of — that information is equally important. A good interviewer listens. A good interviewer is objective, unbiased, and avoids foregone conclusions. A good interviewer pays attention to the data that seem contrary, contradictory, and unexpected. Then, he or she builds an explanation that encompasses all of the data. Inconvenient data cannot just be cast aside; it is part of the puzzle.