How to achieve synergy in group decision making: Lessons to be learned from the hidden profile paradigm

Based on over 25 years of research on hidden profiles and information sharing in groups, and particularly our own work in this area, we outline a general model of how groups can achieve better decisions in a hidden profile situation than their individual members would have been capable of (i.e., synergy). At its core the model defines intensity and bias as the two key parameters that have to be optimised with regard to both the discussion of information and the processing of information in order to ensure synergy in group decision making. We review the empirical literature on information sharing and group decision making in the hidden profile paradigm (with a particular focus on our own studies) to illustrate how group decision quality can be enhanced by increasing intensity and decreasing bias in the discussion and processing of information. Finally we also outline why we think that the lessons learned from research using the hidden profile paradigm can be generalised to group decision-making research in general, and how these lessons can stimulate studies in other fields of group decision-making and group performance research.     

Photic Stimulation of Young Rats

Zajonc, Harrison, and their colleagues have recently conducted a series of studies demonstrating a positive, monotonic relation between frequency of “mere” exposure and liking for stimuli. Other studies have found either the inverted-U relation or a decrease in liking. It was proposed that an emphasis upon mere exposure may be somewhat misleading, and that a concern with degree of stimulus familiarity might be more fruitful. Conflicting forms of the exposure-liking relation seem to be potentially reconcilable if consideration is given to factors that influence the rate at which stimuli become familiar, or capable of being anticipated and represented in memory.

Two experiments using stimuli and procedures taken from Zajonc (23) yielded a positive, monotonic relation between frequency and liking. A third experiment, designed to produce greater attention to the stimuli and thus hasten familiarization, yielded an inverted-U relation. A fourth experiment used simpler verbal stimuli than the first three. This was designed to result in even faster familiarization. As expected, there was a negative relation between liking and exposure frequency.

The “frequency group” of investigators has explained the monotonic exposure effect in terms of the response competition hypothesis. However, the latter is incapable of handling a nonmonotonic relation. A reasonable alternative seems to be the expectancy arousal hypothesis (5): viz., that liking is maximum for stimuli that arouse moderately strong expectancies of either a “molar” or a “molecular” nature. Previous research (5, 6, 7, 8) has supported this hypothesis, although some of the studies are also amenable to the response competition hypothesis. A further experiment was designed to distinguish between predictions from the response competition and the expectancy arousal hypotheses. The results supported the latter.     

Functions of Clinical Psychological Service in California Juvenile and Adult Courts

Subjects provided free responses to six concepts representing varying degrees of involvement. Responses were obtained from each subject under normal and negative affect conditions. Group data were used. Under negative affect conditions, significant correlations were found between concept involvement and type/token ratio (TTR), tokens per type, response variation index (RVI), and total types. Correlations were in the direction of increased redundancy as involvement decreased and, conversely, increased response variation as involvement increased. These relationships held only under negative affect conditions. Implications were discussed for the problems of communication under negative affect conditions and the assessment of individuals’ internal states from verbal behavior. Finally, a sociolinguistic view of the “language community” concept was offered.     

Error Theory and the Concept of Morality

Error theories about morality often take as their starting point the supposed queerness of morality, and those resisting these arguments often try to argue by analogy that morality is no more queer than other unproblematic subject matters. Here, error theory (as exemplified primarily by the work of Richard Joyce) is resisted first by arguing that it assumes a common, modern, and peculiarly social conception of morality. Then error theorists point out that the social nature of morality requires one to act against one's self‐interest while insisting on the categorical, inescapable, or overriding status of moral considerations: they argue that morality requires magic, then (rightly) claim that there is no such thing as magic. An alternate eudaimonist conception of morality is introduced which itself has an older provenance than the social point of view, dating to the ancient Greeks. Eudaimonism answers to the normative requirements of morality, yet does not require magic. Thus, the initial motivation for error theory is removed.     

Methods for second order meta-analysis and illustrative applications

This paper presents methods for second order meta-analysis along with several illustrative applications. A second order meta-analysis is a meta-analysis of a number of statistically independent and methodologically comparable first order meta-analyses examining ostensibly the same relationship in different contexts. First order meta-analysis greatly reduces sampling error variance but does not eliminate it. The residual sampling error is called second order sampling error. The purpose of a second order meta-analysis is to estimate the proportion of the variance in mean meta-analytic effect sizes across multiple first order meta-analyses attributable to second order sampling error and to use this information to improve accuracy of estimation for each first order meta-analytic estimate. We present equations and methods based on the random effects model for second order meta-analysis for three situations and three empirical applications of second order meta-analysis to illustrate the potential value of these methods to the pursuit of cumulative knowledge.     

Data Collection in a Flat World: The Strengths and Weaknesses of Mechanical Turk Samples

Mechanical Turk (MTurk), an online labor system run by Amazon.com, provides quick, easy, and inexpensive access to online research participants. As use of MTurk has grown, so have questions from behavioral researchers about its participants, reliability, and low compensation. In this article, we review recent research about MTurk and compare MTurk participants with community and student samples on a set of personality dimensions and classic decision‐making biases. Across two studies, we find many similarities between MTurk participants and traditional samples, but we also find important differences. For instance, MTurk participants are less likely to pay attention to experimental materials, reducing statistical power. They are more likely to use the Internet to find answers, even with no incentive for correct responses. MTurk participants have attitudes about money that are different from a community sample's attitudes but similar to students' attitudes. Finally, MTurk participants are less extraverted and have lower self‐esteem than other participants, presenting challenges for some research domains. Despite these differences, MTurk participants produce reliable results consistent with standard decision‐making biases: they are present biased, risk‐averse for gains, risk‐seeking for losses, show delay/expedite asymmetries, and show the certainty effect—with almost no significant differences in effect sizes from other samples. We conclude that MTurk offers a highly valuable opportunity for data collection and recommend that researchers using MTurk (1) include screening questions that gauge attention and language comprehension; (2) avoid questions with factual answers; and (3) consider how individual differences in financial and social domains may influence results. Copyright © 2012 John Wiley & Sons, Ltd.     

Decoding facial blends of emotion: Visual field,attentional and hemispheric biases

Most clinical research assumes that modulation of facial expressions is lateralized predominantly across the right-left hemiface. However, social psychological research suggests that facial expressions are organized predominantly across the upper-lower face. Because humans learn to cognitively control facial expression for social purposes, the lower face may display a false emotion, typically a smile, to enable approach behavior. In contrast, the upper face may leak a person’s true feeling state by producing a brief facial blend of emotion, i.e. a different emotion on the upper versus lower face. Previous studies from our laboratory have shown that upper facial emotions are processed preferentially by the right hemisphere under conditions of directed attention if facial blends of emotion are presented tachistoscopically to the mid left and right visual fields. This paper explores how facial blends are processed within the four visual quadrants. The results, combined with our previous research, demonstrate that lower more so than upper facial emotions are perceived best when presented to the viewer’s left and right visual fields just above the horizontal axis. Upper facial emotions are perceived best when presented to the viewer’s left visual field just above the horizontal axis under conditions of directed attention. Thus, by gazing at a person’s left ear, which also avoids the social stigma of eye-to-eye contact, one’s ability to decode facial expressions should be enhanced.     

Perceiving vocal age and gender: An adaptation approach

Aftereffects of adaptation have revealed both independent and interactive coding of facial signals including identity and expression or gender and age. By contrast, interactive processing of non-linguistic features in voices has rarely been investigated. Here we studied bidirectional cross-categorical aftereffects of adaptation to vocal age and gender. Prolonged exposure to young (~ 20 yrs) or old (~ 70 yrs) male or female voices biased perception of subsequent test voices away from the adapting age (Exp. 1) and the adapting gender (Exp. 2). Relative to gender-congruent adaptor-test pairings, vocal age aftereffects (VAAEs) were reduced but remained significant when voice gender changed between adaptation and test. This suggests that the VAAE relies on both gender-specific and gender-independent age representations for male and female voices. By contrast, voice gender aftereffects (VGAEs) were not modulated by age-congruency of adaptor and test voices (Exp. 2). Instead, young voice adaptors generally induced larger VGAEs than old voice adaptors. This suggests that young voices are particularly efficient gender adaptors, likely reflecting more pronounced sexual dimorphism in these voices. In sum, our findings demonstrate how high-level processing of vocal age and gender is partially intertwined.