Q-Methodology Essay ⋆ Political Science Essay Examples ⋆ EssayEmpire

Invented by British psychologist William Stephenson in 1935, Q-methodology represents a kind of observer rating that can be used to assess subjective opinions or beliefs about any topic or situation. It is often used in political science in observations of policy issues and decision makers.

In a Q-sort, subjects are asked to rank their impressions of a particular topic, person, or event by indicating how well they think predetermined words or traits describe those things. For example, they might be asked to rank order one hundred descriptive adjectives by how accurately they think the particular word applies to a subject, or they may be asked how much they may agree or disagree with a given set of statements. Oftentimes, a stimulus, such as a video or speech on the subject, might be delivered to observers before they are asked to rank the target. These rankings are then factor analyzed to reveal areas of overlapping subjective points of similarity and difference between subjects. In contrast to conventional factor analysis, which operates on the intervariable correlation matrix, Q-methodology operates on the intersubject correlation matrix.

The goal of this kind of research is to provide a systematic way to combine the idiosyncratic individual responses of observers into an aggregate assessment of individual subjective judgments; this helps researchers understand the nature of preferences, motives, and other phenomenon that can be otherwise difficult to determine. Once this is done, investigators often examine whether these imputed characteristics can predict particular behaviors. Q-methodology can be used in concert with other methods to provide a multimethod investigation of political traits or character.

Several criticisms of this kind of work exist, including claims that many individuals converging in their judgments do not necessarily make these perceptions accurate. This criticism is particularly relevant under modern conditions of impression management and media attention.

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