scholarly journals Facial Stereotyping Drives Judgments of Perceptually Ambiguous Social Groups

2021 ◽  
Author(s):  
Maryam Bin Meshar ◽  
Ryan Mayer Stolier ◽  
Jonathan B. Freeman
Keyword(s):  
Individual Differences ◽  
Statistical Learning ◽  
Social Groups ◽  
Causal Role ◽  
Facial Features ◽  
Facial Appearance ◽  
Social Categories ◽  
Social Encounters

When seeing a face, people form judgments of perceptually ambiguous social categories (PASCs), e.g., gays, gun-owners, or alcoholics. Previous research has assumed that PASC judgments arise from the statistical learning of facial features in social encounters. We propose, instead, that perceivers associate facial features with traits (e.g., extroverted) and then infer PASC membership via learned stereotype associations with those traits. Across 3 studies, we show that when any PASC is more stereotypically associated with a trait (e.g., alcoholics=extroverted), perceivers are more likely to infer PASC membership from faces conveying that trait (Study 1). Further, we demonstrate that individual differences in trait-PASC stereotypes predict face-based judgments of PASC membership (Study 2) and have a causal role in these judgments (Study 3). Together, our findings imply that people can form any number of PASC judgments from facial appearance alone by drawing on their learned social-conceptual associations.

scholarly journals Facial Stereotyping Drives Judgments of Perceptually Ambiguous Social Groups

2021 ◽  
pp. 194855062110622
Author(s):  
Maryam Bin Meshar ◽  
Ryan M. Stolier ◽  
Jonathan B. Freeman
Keyword(s):  
Individual Differences ◽  
Statistical Learning ◽  
Social Groups ◽  
Causal Role ◽  
Facial Features ◽  
Facial Appearance ◽  
Social Categories ◽  
Social Encounters

When seeing a face, people form judgments of perceptually ambiguous social categories (PASCs), for example, gun-owners, gay people, or alcoholics. Previous research has assumed that PASC judgments arise from the statistical learning of facial features in social encounters. We propose, instead, that perceivers associate facial features with traits (e.g., extroverted) and then infer PASC membership via learned stereotype associations with those traits. Across three studies, we show that when any PASC is more stereotypically associated with a trait (e.g., alcoholics = extroverted), perceivers are more likely to infer PASC membership from faces conveying that trait (Study 1). Furthermore, we demonstrate that individual differences in trait–PASC stereotypes predict face-based judgments of PASC membership (Study 2) and have a causal role in these judgments (Study 3). Together, our findings imply that people can form any number of PASC judgments from facial appearance alone by drawing on their learned social–conceptual associations.

Social Categorization From Faces: Evidence From Obvious and Ambiguous Groups

2017 ◽  
Vol 26 (3) ◽  
pp. 231-236 ◽  
Author(s):  
Nicholas O. Rule ◽  
Shelbie L. Sutherland
Keyword(s):  
Skin Color ◽  
Social Groups ◽  
Social Categorization ◽  
Social Consequences ◽  
Political Affiliation ◽  
Facial Features ◽  
Social Categories ◽  
Face Shape ◽  
The Social ◽  
Better Than

People use facial features (e.g., face shape, skin color, eye structure) both in isolation and in combination to identify others as members of a variety of social categories. For some categories (e.g., age, race, and sex), the markers are obvious and people categorize their members almost perfectly. For others, however (e.g., political affiliation, religious following, and sexual orientation), the markers are ambiguous, yet people can still categorize members of these groups with better than chance accuracy and little effort or awareness. Here, we describe how people categorize others into both perceptually obvious and perceptually ambiguous social groups from their faces, discussing potential mechanisms that may underlie categorization accuracy and noting some of the social consequences that result from categorizing other people into groups.

An Exploration of Individual Differences in Statistical Learning

2014 ◽  
Author(s):  
Lucy C. Erickson ◽  
Michael Kaschak ◽  
Erik D. Thiessen ◽  
Cassie Berry
Keyword(s):  
Individual Differences ◽  
Statistical Learning

FACE RECOGNITION USING FUZZY INFERENCE SYSTEM

2009 ◽  
Vol 8 (3) ◽  
pp. 887-897
Author(s):  
Vishal Paika ◽  
Er. Pankaj Bhambri
Keyword(s):  
Neural Networks ◽  
Fuzzy Inference ◽  
Facial Features ◽  
Facial Appearance ◽  
Feature Points ◽  
Inference System ◽  
Detection Techniques ◽  
The Face ◽  
Hair Style ◽  
Facial Images

The face is the feature which distinguishes a person. Facial appearance is vital for human recognition. It has certain features like forehead, skin, eyes, ears, nose, cheeks, mouth, lip, teeth etc which helps us, humans, to recognize a particular face from millions of faces even after a large span of time and despite large changes in their appearance due to ageing, expression, viewing conditions and distractions such as disfigurement of face, scars, beard or hair style. A face is not merely a set of facial features but is rather but is rather something meaningful in its form.In this paper, depending on the various facial features, a system is designed to recognize them. To reveal the outline of the face, eyes, ears, nose, teeth etc different edge detection techniques have been used. These features are extracted in the term of distance between important feature points. The feature set obtained is then normalized and are feed to artificial neural networks so as to train them for reorganization of facial images.

scholarly journals Lay beliefs in physiognomy explain overreliance on facial impressions

2019 ◽  
Author(s):  
Bastian Jaeger ◽  
Anthony M Evans ◽  
Marielle Stel ◽  
Ilja van Beest
Keyword(s):  
Representative Sample ◽  
Diagnostic Information ◽  
Facial Features ◽  
Facial Appearance ◽  
Dutch Population ◽  
Judgment Accuracy ◽  
Lay Beliefs ◽  
Decision Outcomes ◽  
Accuracy Study

People often rely on a person’s facial appearance when judging their character, even when more diagnostic information is available. This can lead to worse decision outcomes and appearance-based discrimination. What explains this overreliance on facial impressions? In three studies, we examine the role of lay beliefs in physiognomy—the idea that facial features are indicative of a person’s character. We find widespread endorsement of physiognomic beliefs in a representative sample of the Dutch population (Study 1, n = 2,624). Crucially, people with stronger physiognomic belief rely more on facial impressions when making trust decisions (Study 2, n = 224). They are also more confident in their ability to detect corrupt politicians based on facial photographs, but this increased confidence is not associated with superior judgment accuracy (Study 3, n = 406). In sum, our studies show that physiognomic beliefs are widespread and related to overreliance on facial impressions.

scholarly journals Investigating emotion recognition in the first year of life using eye-tracking Methodology

2021 ◽  
Author(s):  
Shira C. Segal
Keyword(s):  
Individual Differences ◽  
Eye Tracking ◽  
Emotion Recognition ◽  
Emotional Expressions ◽  
First Year ◽  
Facial Features ◽  
Fearful Faces ◽  
Facial Expressions Of Emotion ◽  
First Year Of Life ◽  
Key Words Emotion

The ability to recognize facial expressions of emotion is a critical part of human social interaction. Infants improve in this ability across the first year of life, but the mechanisms driving these changes and the origins of individual differences in this ability are largely unknown. This thesis used eye tracking to characterize infant scanning patterns of expressions. In study 1 (n = 40), I replicated the preference for fearful faces, and found that infants either allocated more attention to the eyes or the mouth across both happy and fearful expressions. In study 2 (n = 40), I found that infants differentially scanned the critical facial features of dynamic expressions. In study 3 (n = 38), I found that maternal depressive symptoms and positive and negative affect were related to individual differences in infants’ scanning of emotional expressions. Implications for our understanding of the development of emotion recognition are discussed. Key Words: emotion recognition, infancy eye tracking, socioemotional development

EVALUATION OF THE PHENOMENON OF SPATIAL SEGREGATION IN LVIV. HISTORICAL ASPECT

2021 ◽  
Vol 3 (2) ◽  
pp. 79-83
Author(s):  
Senkiv Z ◽  
Keyword(s):  
Social Groups ◽  
Current Situation ◽  
Spatial Segregation ◽  
Social Categories ◽  
Historical Aspect ◽  
Historical Aspects ◽  
Original Meaning ◽  
The Social ◽  
The City

The article attempts to outline the phenomenon of spatial segregation in Lviv. It highlights the historical aspects of this phenomenon, and their impact on the current situation. Also is outlined the own classification of the social groups which have developed at present city is considering the degree of their mutual isolation. It was found that in the historical aspect of spatial segregation in Lviv can be divided into three periods: - medieval (when it was discriminatory), Soviet (when it was a privilege marking of politically "trustworthy"), and modern (associated with property stratification). Each of these segregation stages has left its mark on the spatial character of the city, albeit to varying degrees. Thus, the medieval discriminatory segregation of space is now practically inactive; the Soviet partially changed its direction and lost its original meaning, the modern one is at the stage of active development and deepening. Eight social categories have been identified in modern Lviv, in relation to which the process of spatial segregation is taking place. Accordingly, an assessment of the phenomenon of spatial segregation is given, which should take into account the following factors: a) the frequency of intersection of social groups of different categories; b) the place where this intersection takes place (for example citywide holidays); c) territorial distribution of spatially segregated groups. Preliminarily assessed the isolation level of different social groups, which also has a urban dimension.

scholarly journals Information-theoretic Modeling of Perceived Musical Complexity

2019 ◽  
Vol 37 (2) ◽  
pp. 165-178
Author(s):  
Sarah A. Sauvé ◽  
Marcus T. Pearce
Keyword(s):  
Individual Differences ◽  
Computational Model ◽  
Information Content ◽  
Statistical Learning ◽  
Probabilistic Prediction ◽  
Information Theoretic ◽  
Musical Background ◽  
Musical Excerpts ◽  
Definition Of ◽  
Perceived Complexity

What makes a piece of music appear complex to a listener? This research extends previous work by Eerola (2016), examining information content generated by a computational model of auditory expectation (IDyOM) based on statistical learning and probabilistic prediction as an empirical definition of perceived musical complexity. We systematically manipulated the melody, rhythm, and harmony of short polyphonic musical excerpts using the model to ensure that these manipulations systematically varied information content in the intended direction. Complexity ratings collected from 28 participants were found to positively correlate most strongly with melodic and harmonic information content, which corresponded to descriptive musical features such as the proportion of out-of-key notes and tonal ambiguity. When individual differences were considered, these explained more variance than the manipulated predictors. Musical background was not a significant predictor of complexity ratings. The results support information content, as implemented by IDyOM, as an information-theoretic measure of complexity as well as extending IDyOM's range of applications to perceived complexity.

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