scholarly journals Biasing Effects in Ferroic Materials

10.5772/60764 ◽  
2015 ◽  
Author(s):  
Vladimir Koval ◽  
Giuseppe Viola ◽  
Yongqiang Tan
Keyword(s):  
Biasing Effects ◽  
Ferroic Materials

Ferroic materials and anomalous strains

2005 ◽  
Vol 96 (4) ◽  
pp. 316-324 ◽  
Author(s):  
E. Hornbogen
Keyword(s):  
Ferroic Materials

Debiasing the Outcome Effect: The Role of Instructions in an Audit Litigation Setting

2002 ◽  
Vol 21 (2) ◽  
pp. 7-20 ◽  
Author(s):  
Peter M. Clarkson ◽  
Craig Emby ◽  
Vanessa W.-S. Watt
Keyword(s):  
Theoretical Perspective ◽  
Cognitive Components ◽  
Audit Judgment ◽  
Outcome Information ◽  
Audit Litigation ◽  
Outcome Bias ◽  
Biasing Effects ◽  
Judgment Setting

The outcome effect occurs where an evaluator, who has knowledge of the outcome of a judge's decision, assesses the quality of the judgment of that decision maker. If the evaluator has knowledge of a negative outcome, then that knowledge negatively influences his or her assessment of the ex ante judgment. For instance, jurors in a lawsuit brought against an auditor for alleged negligence are informed of an undetected fraud, even though an unqualified opinion was issued. This paper reports the results of an experiment in an applied audit judgment setting that examined methods of mitigating the outcome effect by means of instructions. The results showed that simply instructing or warning the evaluator about the potential biasing effects of outcome information was only weakly effective. However, instructions that stressed either (1) the cognitive nonnormativeness of the outcome effect or (2) the seriousness and gravity of the evaluation ameliorated the effect significantly. From a theoretical perspective, the results suggest that there may both motivational and cognitive components to the outcome effect. In all, the findings suggest awareness of the outcome effect and use of relatively nonintrusive instructions to evaluators may effectively counteract the potential for the outcome bias.

The biasing effects of appearances go beyond physical attractiveness and mating motives

2017 ◽  
Vol 40 ◽  
Author(s):  
Christopher Y. Olivola ◽  
Alexander Todorov
Keyword(s):  
Labor Markets ◽  
Physical Attractiveness ◽  
Facial Features ◽  
Economic Games ◽  
Experimental Economic ◽  
Growing Body ◽  
Social Attributions ◽  
Biasing Effects

AbstractThe influence of appearances goes well beyond physical attractiveness and includes the surprisingly powerful impact of “face-ism” – the tendency to stereotype individuals based on their facial features. A growing body of research has revealed that these face-based social attributions bias the outcomes of labor markets and experimental economic games in ways that are hard to explain via evolutionary mating motives.

Snacking Around the World

2017 ◽  
pp. 91-130
Keyword(s):  
Social Media ◽  
Image Analysis ◽  
Image Coding ◽  
Empirical Data ◽  
Theoretical Approaches ◽  
The World ◽  
Social Media Platforms ◽  
Image Set ◽  
Research Questions ◽  
Biasing Effects

Social media platforms enable access to large image sets for research, but there are few if any non-theoretical approaches to image analysis, categorization, and coding. Based on two image sets labeled by the #snack hashtag (on Instagram), a systematic and open inductive approach to identifying conceptual image categories was developed, and unique research questions designed. By systematically categorizing imagery in a bottom-up way, researchers may (1) describe and assess the image set contents and categorize them in multiple ways independent of a theoretical framework (and its potential biasing effects); (2) conceptualize what may be knowable from the image set by the defining of research questions that may be addressed in the empirical data; (3) categorize the available imagery broadly and in multiple ways as a precursor step to further exploration (e.g., research design, image coding, and development of a research codebook). This work informs the exploration and analysis of mobile-created contents for open learning.

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