Having an Interdependent Self-Construal Leads to Greater Weighting of Data In Causal Judgment
Year: 2011
Type: article
Abstract: Having an Interdependent Self-Construal Leads to Greater Weighting of Data In Causal Judgment Kelly M. Goedert Seton Hall University Lisa R. Grimm The College of New Jersey Arthur B. Markman University of Texas, Austin Barbara A. Spellman University of Virginia Abstract: People’s causal judgments show systematic biases, including over-weighting of confirming information, and favoring prior beliefs over data. We investigated the effects of self-construal on data-weighting in causal judg- ments. We primed participants with interdependent or independent self-construals (interdependent people define themselves through relationships; independent through individual traits). On 56 trials, each containing complete fre- quency information (i.e., frequency of presence/absence of the cause and presence/absence of the effect), participants judged the ability of a cause to produce an effect. We observed a main effect of prime: Interdependent participants’ judgments covaried more with frequency information, suggesting they make greater use of data. Furthermore, on non-contingent trials, interdependents weighted all frequency data equally (independents did not). However, be- ing interdependent did not perfectly ameliorate biases in the weighting of data: on contingent trials, both groups weighted the data unequally, favoring confirming, cause-present information. Thus, independents only sometimes demonstrated extra sensitivity to background information.
Language: English
Subfield: General Decision Sciences
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2573763546