Do people use consensus information in making causal attributions?

Wells, Gary L.; Harvey, John H.

doi:10.1037/0022-3514.35.5.279

Cited by 166 publications

(139 citation statements)

References 13 publications

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“…We show that (a) our , Experiment 2) findings contradict the predictions made by the linear-combination rules and Suppes's (1984) model, (b) the differing results reported by Nisbett and Borgida (1975) and Wells and Harvey (1977) in their controversial debate regarding the use of consensus information are both consistent with our model, and (c) the differing attributions of actors and observers are also consistent with our model.…”

Section: Discussionsupporting

confidence: 60%

Covariation in natural causal induction.

Cheng

Novick²

1992

Psychological Review

370

321

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The covariation component of everyday causal inference has been depicted, in both cognitive and social psychology as well as in philosophy, as heterogeneous and prone to biases. The models and biases discussed in these domains are analyzed with respect to focal sets: contextually determined sets of events over which covariation is computed. Moreover, these models are compared to our probabilistic contrast model, which specifies causes as first and higher order contrasts computed over events in a focal set. Contrary to the previous depiction of covariation computation, the present assessment indicates that a single normative mechanism-the computation of probabilistic contrasts-underlies this essential component of natural causal induction both in everyday and in scientific situations.We do not perceive the visual world as a two-dimensional mosaic of bits of light patches. Instead, these data from the retina are processed by our central visual system to yield a coherent perception of the world, reflecting its visual and spatial structures. Similarly, we do not perceive our lives or the world beyond as a stream of unconnected elemental events. Here, too, central processes act on the data to yield an organized view, structured in terms of commonsensical and scientific theories. Causal induction is an example of such organizing processes. When a government resorts to violent suppression of its people or yields to peaceful reform, when a couple decides to date or a marriage breaks up, or when an epidemic strikes or a new vaccine controls it, we seek out causes.How do ordinary people induce the causes of events? Moreover, given that the primary goals of causal induction are the recovery of the causal structure of the world and the prediction of future events, is the mechanism underlying natural causal induction adequate for satisfying these goals? Covariation-the change in the probability of an effect given the presence versus the absence of a potential cause-has generally been regarded as a necessary (although insufficient) criterion of normative causal induction. 1 The computation of covariation has generated a considerable body of research in the cognitive and social literatures, both of which have presented rather messy pictures of the psychological mechanism. These literatures suggest that the covariation component in natural causal induction is non-

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Section: Discussionsupporting

confidence: 60%

Covariation in natural causal induction.

Cheng

Novick²

1992

Psychological Review

370

321

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“…The observed differential use of consensus information is of particular interest in the case of self-predictions. Several studies have found previously that consensus information affects judgments of others but not of one's own behavior (e.g., Hansen & Donoghue, 1977;Wells & Harvey, 1977). The present study indicates that judgements of one's own behavior can be infiuenced by consensus information, and this may be particularly true for certain people (viz., high self-monitors).…”

Section: Discussionmentioning

confidence: 58%

Self-monitoring and the use of consensus information

Kulik

Taylor

1981

J Personality

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This study investigated how individual differences in level of self-monitoring relate to the use of consensus information. We predicted that higher self-monitors would utilize consensus information more than would low self-monitors when making predictions about their own and another person's behavior, since high self-monitors are theoretically more responsive to the social norms surrounding situations. Low self-monitors, in contrast, were expected to rely more on self-hased consensus. Subjects read a description of Darley and Latane's (1968) bystander intervention study in which the participants purportedly rarely helped the victim (socially undesirahle consensus) or frequently helped the victim (socially desirable consensus). As predicted, higher relative to lower self-monitors predicted slower helping when consensus was for nonhelping. The prediction that higher relative to lower self-monitors would predict faster helping when consensus was for helping, although in the right direction, was not supported strongly. Evidence was found for the prediction that low self-monitors rely to a greater extent on self-hased consensus.Considerable research in recent years has been devoted to determining whether or not consensus information affects various types of attributional decisions. According to Kelley (1967), perceivers tend to compare an actor's behavior to the behavior of the population (i.e., to consensus information) when making attributional judgments. For example, an individual who knows most people respond to a stimulus in a eertain manner would likely perceive dissimilar behavior by an actor as caused more by dispositional qualities of the actor than by situational factors. Extrapolating from Kelley, one can predict that consensus information would generally affect predictions for the behavior of others and perhaps of oneself in the direction of the population performance. Thus, knowledge that most people respond to a stimulus in a certain manner should 1. The authors would like to thank Gharles Judd and Jennifer Grocker for their helpful comments.

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“…Research is available to support the contention that narrative messages are significantly more memorable and persuasive than are statistical/logical arguments (Borgida & Nisbett, 1977;Kazoleas, 1993;Koballa, 1986;Nisbett & Ross, 1980;Taylor & Thompson, 1982). However, other research indicates that fact-based and statistical evidence is more persuasive than personal narratives (see Allen & Preiss, 1997, for results of their metaanalysis; Baesler & Burgoon, 1994;Dickson, 1982;Wells & Harvey, 1977). Furthermore, still other evidence exists indicating that there is no difference in the persuasiveness of these different message types (Iyengar & Kinder, 1987;Nadler, 1983;Reyna, Woodruff, & Brainerd, 1987).…”

Section: Fear Appeals and The Testicular Self-exam Mormanmentioning

confidence: 86%