Reducing suggestibility to additive versus contradictory misinformation in younger and older adults via divided attention and/or explicit error detection

Younger and older adults are more suggestible to additive (not originally included) versus contradictory (a change to the original) misleading details. Only suggestibility to contradictory misinformation can be reduced with explicit instructions to detect errors during exposure to misinformation. The present work examines how to reduce suggestibility to additive misinformation and whether attentional resources at exposure similarly influence additive and contradictory misinformation. During the misleading question phase, attention and error detection were manipulated. Participants answered the questions under full or divided attention, and some were instructed to mark detected errors. On the final test, additive misinformation was endorsed more than contradictory misinformation despite equivalent error detection. However, dividing attention reduced suggestibility for additive misinformation, whereas successful error detection showed evidence of reducing contradictory misinformation, providing further evidence for the dissociation between these types of misinformation. Additionally, dividing younger adults' attention did not consistently result in a pattern paralleling older adults.     

Same‐gender and same‐race bias in assessment center ratings: A rating error approach to understanding subgroup differences

This study investigated leniency and similar‐to‐me bias as mechanisms underlying demographic subgroup differences among assessees in assessors’ initial dimension ratings from three assessment center (AC) simulation exercises used as part of high‐stakes promotional testing. It examined whether even small individual‐level effects can accumulate (i.e., “trickle‐up”) to produce larger subgroup‐level differences. Individual‐level analyses were conducted using cross‐classified multilevel modeling and conducted separately for each exercise. Results demonstrated weak evidence of leniency toward White assessees and similar‐to‐me bias among non‐White assessee–assessor pairs. Similar leniency was found toward female assessees, but no statistically significant effects were found for assessee or assessor gender or assessee–assessor gender similarity. Using traditional d effect size estimates, weak individual level assessee effects translated into small but consistent subgroup differences favoring White and female assessees. Generally small but less consistent subgroup differences indicated that non‐White and male assessors gave higher ratings. Moreover, analyses of overall promotion decisions indicate the absence of adverse impact. Findings from this AC provide some support for the “trickle‐up” effect, but the effect on subgroup differences is trivial. The results counter recent reviews of AC studies suggesting larger than previously assumed subgroup differences. Consequently, the findings demonstrate the importance of following established best practices when developing and implementing the AC method for selection purposes to minimize subgroup differences.     

Error reframing: studying the promotion of an error management culture

In the organizational behaviour and organizational psychology literature, individual errors are considered either as sources of blame (error-prevention culture) or as sources of learning and something to be encouraged in order to promote innovation (error-management culture). While we can assume that a third perspective exists somewhere in between, error management is usually considered as the best solution. Yet scholars have tended to neglect the planned and directed transition from a pure error-prevention to an error-management culture. We thus examine to what extent and under what conditions an organization can culturally transform the representation of individual errors through its business leaders. To answer this question, we conducted a qualitative study on the case of a French insurance company. We portray a realistic image of the promotion of an error management culture, pointing out certain limitations and constraints, while nonetheless identifying some conditions for successful error reframing.     

四参数Logistic加权模型下被试能力稳健估计

设计项目参数、被试得分已知的测验情境,在两、三、四参数Logistic加权模型下进行能力估计,发现被试得分等级之间的能力步长存在着均匀的步长间距,被试得分能较好的反映多级记分的分数加权作用。两参数Logistic加权模型下会出现被试参数估计扰动现象,猜测现象会导致能力高估现象,失误现象会导致能力低估现象;三参数Logistic加权模型c型下能力高估现象未出现或不明显;三参数Logistic加权模型γ型下能力低估现象未出现或不明显;四参数Logistic加权模型下被试能力高估现象和低估现象都未出现或不明显,四参数Logistic加权模型是被试能力稳健性估计较好的方法。     

物体受力分析正误样例组合的学习效果

分别采用正误样例组合、有无错误标记的正误样例组合和有标记的正误样例配对组合设计方法,以物体受力分析正误样例为实验材料,以初中三年级学生为被试进行3项实验,考察了被试物体受力分析图正误样例组合的学习效果。结果表明,正误样例组合的学习成绩显著优于正确样例组合的学习成绩;有标记的正误样例组合的学习成绩显著优于无标记样例组合的学习成绩;有标记正误样例配对组合的学习成绩明显优于正确样例组合的学习成绩。     

Using the dual‐criteria methods to supplement visual inspection: An analysis of nonsimulated data

The purpose of our study was to examine the probability of observing false positives in nonsimulated data using the dual‐criteria methods. We extracted data from published studies to produce a series of 16,927 datasets and then assessed the proportion of false positives for various phase lengths. Our results indicate that collecting at least three data points in the first phase (Phase A) and at least five data points in the second phase (Phase B) is generally sufficient to produce acceptable levels of false positives.     

What are other-rated scales composed of? Sources of measurement error and true trait variance in other-ratings of the Big Five

Other-ratings of targets’ traits may consist – besides true trait variance (TTV) – of different measurement error sources, particularly due to raters, scales, items, measurement times, and random fluctuations. Using Gnambs’ (2015) and Ones, Wiernik, Wilmot, and Kostal’s (2016) procedures for partitioning variance in scales due to measurement error, available meta-analytical data on Big Five other-ratings were analyzed. They showed relatively little TTV (0–13%), which was especially decreased by both low inter-rater reliability and convergent validity of Big Five measures. Accounting for both, TTV levels rose, but were still small to medium (4–26%). These findings provide important insights on what Big Five other-ratings are composed of and how such scale scores may be interpreted and treated in further analyses (e.g., trait-outcome relations).     

Born to be biased? Unrealistic optimism and error management theory

When individuals display cognitive biases, they are prone to developing systematically false beliefs. Evolutionary psychologists have argued that rather than being a flaw in human cognition, biases may actually be design features. In my paper, I assess the claim that unrealistic optimism is such a design feature because it is a form of error management. Proponents of this theory say that when individuals make decisions under uncertainty, it can be advantageous to err on the side of overconfidence if the potential gains through success are high and the costs of failure are low. I argue that there are a number of conceptual problems in matching the theory with the existing data. I also show that there is empirical evidence against the error management hypothesis.     

Older, not younger, children learn more false facts from stories

Early school-aged children listened to stories that contained correct and incorrect facts. All ages answered more questions correctly after having heard the correct fact in the story. Only the older children, however, produced story errors on a later general knowledge test. Source errors did not drive the increased suggestibility in older children, as they were better at remembering source than were the younger children. Instead, different processes are involved in learning correct and incorrect facts from fictional sources. All ages benefited from hearing correct answers because they activated a pre-existing semantic network. Older children, however, were better able to form memories of the misinformation and thus showed greater suggestibility on the general knowledge test.     

Williamson on inexact knowledge

Timothy Williamson claims that margin for error principles govern all cases of inexact knowledge. I show that this claim is unfounded: there are cases of inexact knowledge where Williamson’s argument for margin for error principles does not go through. The problematic cases are those where the value of the relevant parameter is fixed across close cases. I explore and reject two responses to my objection, before concluding that Williamson’s account of inexact knowledge is not compelling.