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The single factor fallacy occurs when social scientists model their applied work largely around a single factor. The problem generally arises when either a highly relevant theory is ignored or when missing key variables distort the results. Examples of this fallacy are drawn from the expanding research literature on intergroup contact, where we discuss the implications of missing critical variables from the analysis (including segregation, effects of negative as well as positive contact, extended contact, and contact when the outgroup is in the majority). The policy issues involved include racially desegregated schools, minority protest, the impact of neighborhood diversity, and anti‐immigration voting. Three suggestions for avoiding the fallacy are emphasized—the use of mediation–moderation analysis, longitudinal research, and multilevel analysis. We end by outlining five simple principles, based on our own experience in the United States and the United Kingdom, that may increase the impact of social scientists’ research on public policy.
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