ABSTRACT
What is the legal U.S. immigration rate, as a percentage of the nation’s population? We have observed median estimates of 10% (from students at an elite college; Ranney, Cheng, Garcia de Osuna, & Nelson, 2001) or more (from adolescents). The true value is over 30 times less—only 0.3%! Might this datum change one’s opinion or preference on immigration—one’s policy? We often make decisions, and justify or reason about our views, based on available evidence. The Theory of Explanatory Coherence and its models (e.g., ECHO) describe principles that guide belief evaluation and revision. Two such principles are that we (a) weight evidence more than conjecture, and (b) prefer propositions explained parsimoniously (Ranney & Schank, 1998). Thus, true base rates represent parsimonious evidence, relative to instances or anecdotes, and so should be both heavily weighted in one’s thinking and usually evaluated as believable. The present study explored aspects of this general hypothesis—that a single, germane, critical, and surprising number may foster conceptual change. Using a novel paradigm, Numerically Driven Inferencing (NDI; Ranney et al., 2001), and one of its methods, EPIC—Estimate, Prefer, Incorporate, and Change—we studied both estimates and the effects of numerical feedback on (UC-Berkeley) undergraduates’ abortion policies. Quantitatively and qualitatively, 92 such students offered estimates and preferences for the legal U.S. abortion rate, explaining and justifying them. After receiving the (usually, quite surprising) true rate as feedback, a highly minimalist intervention, they provided another (typically changed) preference-and-rationale.
