Compare methods

	False Consensus Paradigm	Unmatched Count Technique
Field	Social Psychology	Social Psychology
Family	Process / pipeline	Process / pipeline
Year of origin	1977	2010
Originator	Lee Ross, David Greene & Pamela House	Survey-methodology tradition; Holbrook & Krosnick (validation)
Type	Experimental paradigm for social-perception bias	Indirect survey technique for sensitive questions
Seminal source	Ross, L., Greene, D., & House, P. (1977). The 'false consensus effect': An egocentric bias in social perception and attribution processes. Journal of Experimental Social Psychology, 13(3), 279-301.	Holbrook, A. L., & Krosnick, J. A. (2010). Social desirability bias in voter turnout reports: Tests using the item count technique. Public Opinion Quarterly, 74(1), 37-67.
Aliases	False Consensus Effect, Egocentric Projection Paradigm, Consensus Estimation Task	Item Count Technique, List Experiment, Unmatched Block Design
Related	3	3
Summary	The false consensus paradigm, established by Ross, Greene, and House in 1977, demonstrates a pervasive bias in social perception: people overestimate the extent to which others share their own choices, beliefs, and behaviors. In the canonical procedure, participants indicate their own position on some issue or choice -- famously, whether they would walk around campus wearing a sandwich-board sign -- and then estimate what proportion of their peers would do the same. The signature finding is that those who choose a given option estimate that option to be more common than do those who reject it, so each group projects its own response onto others. Ross and colleagues also showed that people view their own responses as relatively common and unrevealing of personality while seeing differing responses as uncommon and diagnostic of others' traits. The paradigm became a foundational demonstration of egocentric bias in social judgment and attribution.	The unmatched count technique (also called the item count technique or list experiment) is an indirect survey method for estimating the prevalence of sensitive attitudes or behaviors while protecting respondents' privacy. Respondents are randomly assigned to one of two versions of a question. The control group sees a list of several non-sensitive items and reports only how many of them apply to them; the treatment group sees the same list plus one additional sensitive item and likewise reports only the count. Because respondents report a number rather than which items apply, no one's answer reveals their stance on the sensitive item. The estimated prevalence of the sensitive attribute is simply the difference in mean counts between the treatment and control groups. By breaking the link between an individual and the sensitive item, the technique reduces social-desirability bias for topics like prejudice, illegal behavior, or stigmatized attitudes, as documented in validation work by Holbrook and Krosnick.