The Role of Representative Design in an Ecological Approach to Cognition

Brunswikian Resources for Event-Perception Research

Recent psychological research aimed at determining whether dynamic event perception is direct or mediated by cue-based inference convincingly demonstrates evidence of both modes of perception or apprehension. This work also shows that noise is involved in attaining any perceptual variable, whether it perfectly (invariantly) specifies or imperfectly (fallibly) indicates the value of a target or criterion variable. As such, event-perception researchers encounter both internal (sensory or inferential) and external ecological sources of noise or uncertainty, owing to the organism's possible use of imperfect or ‘nonspecifying’ variables (or cues) and cue-based inference. Because both sources play central roles in Egon Brunswik's theory of probabilistic functionalism and methodology of representative design, event-perception research will benefit by explicitly leveraging original Brunswikian and, more recent, neo-Brunswikian scientific resources. Doing so will result in a more coherent and powerful approach to perceptual and cognitive psychology than is currently displayed in the scientific literature.

A Meta-Analysis of Judgment Achievement as Defined by the Lens Model Equation

This research determined the extent of judgment achievement (i.e., accuracy) across different decision-making domains (e.g., medicine, business, education, psychology). Judgment achievement was examined in terms of the lens model equation ( Tucker, 1964 ). A meta-analysis of 29 studies incorporating 1,032 people across 43 judgment tasks was performed. Overall judgment achievement across different tasks was found to be moderate (r = .42), ranging from .22 for studies in the area of psychology to .58 for those in other professional areas. Methodological moderator factors (type of correlation, database) used in task analysis or the number of cues used in tasks were also considered. The findings indicated that research on judgment achievement should examine judgment tasks relating to specific research areas.

Evolution of the interpersonal conflict paradigm

Using Brunswik’s (1952) lens model framework, Hammond (1965) proposed interpersonal conflict theory to explain the nature, source, and resolution of disagreement or “cognitive conflict” between parties performing judgment tasks. An early review by Brehmer (1976) highlighted the potential of this approach in, for example, understanding the structure of cognitive conflicts, and the effect of task and person variables on judgment policy change and conflict resolution. However, our bibliographic and content reviews from 1976 to the present day demonstrate that research on cognitive conflict using the lens model has declined sharply, while research on “task conflict” has grown dramatically. There has also been a shift to less theoretical precision and methodological rigor. We discuss possible reasons for these developments, and suggest ways in which lens model research on cognitive conflict can be revitalized by borrowing from recent theoretical and methodological advances in the field of judgment and decision making.

A note on determining the number of cues used in judgment analysis studies: The issue of type II error

Many judgment analysis studies employ multiple regression procedures to estimate the importance of cues. Some studies test the significance of regression coefficients in order to decide whether or not specific cues are attended to by the judge or decision maker. This practice is dubious because it ignores type II error. The purposes of this note are (1) to draw attention to this issue, specifically as it appears in studies of self-insight, (2) to illustrate the problem with examples from the judgment literature, and (3) to provide a simple method for calculating post-hoc power in regression analyses in order to facilitate the reporting of type II errors when regression models are used.

Designing Experiments That Generalize

Organizational research has relied too heavily on methods characterized by passive observation, likely because there is a widespread belief that experimental research has limited generalizability. However, this is often because researchers (and reviewers or editors) misunderstand the nature of generalizability and what it requires. This article reiterates the importance of experimental research for understanding organizational phenomena and separates the legitimate concerns about experimental generalizability from the irrelevant ones. Whereas most criticisms of experiments focus on sample characteristics and mundane realism (i.e., superficial resemblance to the real world), more attention needs to be paid to the degree to which the treatment manipulation is valid, representative, and strong.

A signal detection analysis of the recognition heuristic

The recognition heuristic uses a recognition decision to make an inference about an unknown variable in the world. Theories of recognition memory typically use a signal detection framework to predict this binary recognition decision. In this article, I integrate the recognition heuristic with signal detection theory to formally investigate how judges use their recognition memory to make inferences. The analysis reveals that false alarms and misses systematically influence the performance of the recognition heuristic. Furthermore, judges should adjust their recognition response criterion according to their experience with the environment to exploit the structure of information in it. Finally, the less-is-more effect is found to depend on the distribution of cue knowledge and judges' sensitivity to the difference between experienced and novel items. Theoretical implications of this bridge between the recognition heuristic and models of recognition memory are discussed.