Variance In Judgments Research Articles

Determinants of shared and idiosyncratic contributions to judgments of faces.

Recent work has shown that the idiosyncrasies of the observer can contribute more to the variance of social judgments of faces than the features of the faces. However, it is unclear what conditions determine the relative contributions of shared and idiosyncratic variance. Here, we examine two conditions: type of judgment and diversity of face stimuli. First, we show that for simpler, directly observable judgments that are consistent across observers (e.g., masculinity) shared exceeds idiosyncratic variance, whereas for more complex and less directly observable judgments (e.g., trustworthiness), idiosyncratic exceeds shared variance. Second, we show that judgments of more diverse face images increase the amount of shared variance. Finally, using machine-learning methods, we examine how stimulus (e.g., incidental emotion resemblance, skin luminosity) and observer variables (e.g., race, age) contribute to shared and idiosyncratic variance of judgments. Overall, our results indicate that an observer's age is the most consistent and best predictor of idiosyncratic variance contributions to face judgments measured in the current research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Three Traditions of African American Political Thought: Realism, Reformism, and Nationalism

This article argues that conflict rather than consensus defines the history of African American political thought. Its seminal figures have pursued justice along different and diverging lines—including advocating reformist, realist, and nationalist paths. While there is agreement that white supremacy is a form of social, economic, and political domination that should be eradicated, there is disagreement regarding its nature, effects, and resilience. This variance in judgments and inferences regarding the foundations and consequences of white supremacy leads to different accounts of social change, diverging strategic advice for realizing that change, and conflicting political theories. To press this claim, I consider the conflicting political visions of Booker T. Washington (1856–1915), W.E.B. Du Bois (1868–1963), and Marcus Garvey (1887–1940).

Blaming the smurf: Using a novel social deception behavior in online games to test attribution theories

Despite their popularity, online video games possess pervasive toxicity. However, players do not categorically judge toxic behaviors as wrong. Attribution theories are well suited to disambiguate such judgment variance, but debate exists on the usefulness of motivated versus socially regulated blame perspectives. By exploring a new, potentially toxic behavior called “smurfing,” we innovate on methodological barriers that make experimentally disentangling socially regulated and motivated attribution perspectives difficult. In Study 1, we empirically present, describe, and explore smurfing and its perceived effects as a novel cheating behavior in online gaming. In Study 2, we extracted player-generated reasons for smurfing and manipulated the stakes of games to manipulate transgression salience (a key factor of blame attribution) across a moral continuum. By having participants use a mock crowd-sourced judgment platform, we observed the (in)stability of stakes across a continuum of reasons. We subsequently replicated our findings with a novel sample in Study 3.

The Relative Importance of Target and Judge Characteristics in Shaping theMoral Circle.

People's treatment of others (humans, nonhuman animals, or other entities) often depends on whether they think the entity is worthy of moral concern. Recent work has begun to investigate which entities are included in a person's moral circle, examining how certain target characteristics (e.g., species category, perceived intelligence) and judge characteristics (e.g., empathy, political orientation) shape moral inclusion. However, the relative importance of target and judge characteristics in predicting moral inclusion remains unclear. When predicting whether a person will deem an entity worthy of moral consideration, how important is it to know who is making the judgment (i.e., characteristics of the judge), who is being judged (i.e., characteristics of the target), and potential interactions between the two factors? Here, we address this foundational question by conducting a variance component analysis of the moral circle. In two studies with participants from the Netherlands, the United States, the United Kingdom, and Australia (N = 836), we test how much variance in judgments of moral concern is explained by between-target differences, between-judge differences, and by the interaction between the two factors. We consistently find that all three components explain substantial amounts of variance in judgments of moral concern. Our findings provide two important insights. First, an increased focus on interactions between target and judge characteristics is needed, as these interactions explain as much variance as target and judge characteristics separately. Second, any theoretical account that aims to provide an accurate description of moral inclusion needs to consider target characteristics, judge characteristics, and their interaction.

A Feedforward Interactive Network to Explain Complex Information Processing Phenomena Including the Halo Effect and Its Generalization

Abstract Parallel interactive processing (PIP) is a parallel distributed processing approach in which a representation of an object involves interaction of its components in a way that influences information processing of the components. Prior research is summarized in the areas of categorization and probability judgment. It was found that an explanation of the halo effect and its generalization as well as phenomena in other information processing situations could be explained by PIP. The explanation of the halo effect is largely in terms of reduction of variance in judgments of components of an object produced by a holistic impression of the object. There was a focus on processes common to various subject areas.

A unified explanation of variability and bias in human probability judgments: How computational noise explains the mean–variance signature.

Human probability judgments are both variable and subject to systematic biases. Most probability judgment models treat variability and bias separately: a deterministic model explains the origin of bias, to which a noise process is added to generate variability. But these accounts do not explain the characteristic inverse U-shaped signature linking mean and variance in probability judgments. By contrast, models based on sampling generate the mean and variance of judgments in a unified way: the variability in the response is an inevitable consequence of basing probability judgments on a small sample of remembered or simulated instances of events. We consider two recent sampling models, in which biases are explained either by the sample accumulation being further corrupted by retrieval noise (the Probability Theory + Noise account) or as a Bayesian adjustment to the uncertainty implicit in small samples (the Bayesian sampler). While the mean predictions of these accounts closely mimic one another, they differ regarding the predicted relationship between mean and variance. We show that these models can be distinguished by a novel linear regression method that analyses this crucial mean-variance signature. First, the efficacy of the method is established using model recovery, demonstrating that it more accurately recovers parameters than complex approaches. Second, the method is applied to the mean and variance of both existing and new probability judgment data, confirming that judgments are based on a small number of samples that are adjusted by a prior, as predicted by the Bayesian sampler. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Perceiving a pandemic: Global–local incompatibility and COVID-19 superspreading events.

Superspreading events are the primary mode of infection driving the COVID-19 pandemic, but their effect on risk judgments is currently unknown. More than half a million people in the U.S. died from COVID-19 in 1 year, yet public risk perceptions of infection and mortality remain variable. Using a combination of epidemiological models and the psychological theory of global-local incompatibility, we theorize that superspreading diseases create a large variance in infections across geographic localities, leading to highly variable and inaccurate risk perceptions. This is problematic because these local infection rates fail to reveal the overall severity of the pandemic, which determines the personal risk of infection at any location in the near future. We test our predictions with a simulation study and a nationally representative study of U.S. citizens (N = 3,956) conducted in April 2020. Supporting our theory, we find that localized county-level infection rates of COVID-19 are unreliable predictors of national infection rates. However, they explain a significant proportion of variance in judgments of national infection rates, contributing to judgment errors. These results support our theoretical approach for modeling this unique judgment context as an incompatibility between global and local information, providing a framework to predict how citizens will react to novel large-scale (global) risks. Our results also help explain the extreme polarization witnessed in the U.S. regarding perceptions of the risks of the COVID-19 pandemic. Accounting for the variability of local experiences with a pandemic can help future generations prepare for how to respond to similar threats more effectively. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Discounting the Effect of Memory on Repeated Measures of Beauty Judgment

The intrinsic variance of beauty judgment is key to modeling beauty ratings. However, in repeated measures of beauty, observers surely make use of what they remember. To test how memory contributes to repeated beauty ratings, we asked participants to rate 75 arbitrarily named images (e.g., Fred). Initially, participants rated (1 to 7) how much beauty they felt from looking at a named image. Then participants completed two conditions. In the memory condition, participants saw only the name of an image and were asked to remember the image corresponding to that name and rate how much beauty they felt. In the repeat condition, they once again rated how much beauty they felt from looking at a named image. Lastly, in a memory check, participants tried to select which image was associated with a name. Only considering the correctly remembered trials (60%), we calculated the distribution of the differences between the initial beauty rating and that from either the memory condition or the repeat condition. The variance for the memory condition was more than double that of the repeat condition. Likewise, the initial beauty ratings predicted 84% of the variance in the repeat ratings but only 30% of the variance in the memory ratings. Cue combination studies report that observers typically combine cues by the optimal Bayesian rule: The combined reliability is the sum of the separate reliabilities for each cue, where reliability is one over variance. Assuming optimal combination of memory and immediate-perception judgment, we can discount the contribution of memory to estimate the variance of the immediate-perception judgment. Thus, in our paradigm the 0.83 variance of the repeated beauty rating corresponds to a 0.97 immediate-perception judgment variance (without memory). Overall, since there also was no significant difference in means, our results indicate that memory contributes little to repeated beauty ratings.

CHANDRACHUD V. CHANDRACHUD: UNDERSTANDING THE SCOPE OF INTERPRETATION OF STATUTES THROUGH THE FATHER

In the broader picture, Interpretation of Statutes donnes a rather infinitesimal scope to its applications in the practical judicial setup of the nation. Be it the Constitution or the plethora of laws that are passed by the parliament to run the nation and govern its various stratum, interpretation plays a dominant role in getting the same to percolate down to the grass-root level. Benjamin N Cardozo has very famously theorized a lot of what the scope of interpretation of statutes entails and has even streamlined major theories to deduce the process of derivation used by judges to draw out conclusions in various cases. These postulations, although not expressly, find themselves being effectuated via various judges and the same can be deduced upon closer inspection of the wordings of the judgment a judge chooses to articulate while delivering the same. These processes of reasoning by judges vary in their applications and lead to consequences that have been intended by the legislature or rather furthered by the principles of justice, equity and good conscience, the three pillars of a just society. Through the course of this paper, we analyse two major judgments, Sowmithri Vishnu v. Union of India and Joseph Shine v Union of India. Both cases were instituted challenging the constitutionality of section 497 of the Indian Penal Code, that criminalise the act of adultery. The former case, adjudged by Justice YV Chandrachud upheld its constitutional validity whereas the later one adjudged by Justice DY Chandrachud decriminalised the section. Adjudging the interpretative paths taken by the two judges in light of Cardozo’s understanding of Interpretation provides unique insight into the workings of the judicial minds and how time influence the scope of the same. The variance in judgments delivered by father and son presents as an important ground to understand the role of interpretation of statutes and its applications in the world while also helps map out a certain evolutionary process that may be attributed to the scope of interpretation in light of various societal factors that also affect it.

Correlations between person-descriptive items are predictable from the product of their mid-point-centered social desirability values

This paper presents a series of pre-registered analyses testing the same theoretically derived hypothesis: If (a) the attitudes that perceivers have toward targets contribute to the variance of judgments on most items, and (b) items’ rated social desirability values align very closely with the extent to which that is the case, then the product of two items’ mid-point-centered social desirability values should predict the amount of shared variance, and thus the correlation, between these items. This hypothesis applies equally to other ratings and self-ratings. Across samples, effect sizes ranged from r = .36 to r = .80 (average r = .61) and were statistically significant in every single case. We also found that the average effect is much larger for other-ratings ( r = .71) than for self-ratings ( r = .49). This difference was also replicable and is likely rooted in the greater relative importance of the attitude factor in other-ratings, as compared to self-ratings. An exploratory item resampling analysis suggested that scales may achieve good internal consistency, and correlate substantially with other scales, based solely on shared attitude variance. We discuss the relevance of these findings across different domains of psychological assessment, and possible ways of dealing with the issue.

Establishing the situated features associated with perceived stress

We propose that the domain general process of categorization contributes to the perception of stress. When a situation contains features associated with stressful experiences, it is categorized as stressful. From the perspective of situated cognition, the features used to categorize experiences as stressful are the features typically true of stressful situations. To test this hypothesis, we asked participants to evaluate the perceived stress of 572 imagined situations, and to also evaluate each situation for how much it possessed 19 features potentially associated with stressful situations and their processing (e.g., self-threat, familiarity, visual imagery, outcome certainty). Following variable reduction through factor analysis, a core set of 8 features associated with stressful situations—expectation violation, self-threat, coping efficacy, bodily experience, arousal, negative valence, positive valence, and perseveration—all loaded on a single Core Stress Features factor. In a multilevel model, this factor and an Imagery factor explained 88% of the variance in judgments of perceived stress, with significant random effects reflecting differences in how individual participants categorized stress. These results support the hypothesis that people categorize situations as stressful to the extent that typical features of stressful situations are present. To our knowledge, this is the first attempt to establish a comprehensive set of features that predicts perceived stress.

Visual discomfort and the spatial distribution of Fourier energy

Quite independently of what they represent, some images provoke discomfort, and even headaches and seizures in susceptible individuals. The visual system has adapted to efficiently process the images it typically experiences, and in nature these images are usually scale-invariant. In this work, we sought to characterize the images responsible for discomfort in terms of their adherence to low-level statistical properties typically seen in natural scenes. It has been conventional to measure scale invariance in terms of the one-dimensional Fourier amplitude spectrum, by averaging amplitude over orientations in the Fourier domain. However, this loses information on the evenness with which information at various orientations is represented. We therefore fitted a two-dimensional surface (regular circular cone 1/f in logarithmic coordinates) to the two-dimensional amplitude spectrum. The extent to which the cone fitted the spectrum explained an average of 18% of the variance in judgments of discomfort from images including rural and urban scenes, works of non-representational art, images of buildings and animals, and images generated from randomly disposed discs of varying contrast and size. Weighting the spectrum prior to fitting the surface to allow for the spatial frequency tuning of contrast sensitivity explained an average of 27% of the variance. Adjusting the shape of the cone to take account of the generally greater energy in horizontal and vertical orientations improved the fit, but only slightly. Taken together, our findings show that a simple measure based on first principles of efficient coding and human visual sensitivity explained more variance than previously published algorithms. The algorithm has a low computational cost and we show that it can identify the images involved in cases that have reached the media because of complaints. We offer the algorithm as a tool for designers rather than as a simulation of the biological processes involved.

The curious anomaly of skewed judgment distributions and systematic error in the wisdom of crowds.

Judgment distributions are often skewed and we know little about why. This paper explains the phenomenon of skewed judgment distributions by introducing the augmented quincunx (AQ) model of sequential and probabilistic cue categorization by neurons of judges. In the process of developing inferences about true values, when neurons categorize cues better than chance, and when the particular true value is extreme compared to what is typical and anchored upon, then populations of judges form skewed judgment distributions with high probability. Moreover, the collective error made by these people can be inferred from how skewed their judgment distributions are, and in what direction they tilt. This implies not just that judgment distributions are shaped by cues, but that judgment distributions are cues themselves for the wisdom of crowds. The AQ model also predicts that judgment variance correlates positively with collective error, thereby challenging what is commonly believed about how diversity and collective intelligence relate. Data from 3053 judgment surveys about US macroeconomic variables obtained from the Federal Reserve Bank of Philadelphia and the Wall Street Journal provide strong support, and implications are discussed with reference to three central ideas on collective intelligence, these being Galton's conjecture on the distribution of judgments, Muth's rational expectations hypothesis, and Page's diversity prediction theorem.

Consensus in landscape preference judgments: The effects of landscape visual aesthetic quality and respondents' characteristics

Landscape's visual aesthetic quality (VAQ) has been widely regarded as a valuable resource worthy of protection. Although great effort has been devoted to determining the factors driving aesthetic preferences, public consensus in judgments has been neglected in the vast majority of such studies. Therefore, the aim of our study was to analyze three main possible sources of judgment variance: landscape VAQ, landscape type, and variability among respondents. Based upon an extensive perception-based investigation including more than 400 hikers as respondents, we found that variance in respondents' judgments differed significantly among assessed landscape scenes. We discovered a significant difference in judgment variances within each investigated respondent characteristic (gender, age, education level, occupational classification, and respondent's type of residence). Judgment variance was at the same time affected by landscape VAQ itself – the higher the VAQ, the better the consensus. While differences caused by characteristics indicate subjectivity of aesthetic values, the knowledge that people better find consensus for positively perceived landscapes provides a cogent argument for legal protection of valuable landscape scenes.

Disentangling Consumer and Provider Predictors of Advance Care Planning

Factorial surveys were used to examine community-based long-term care providers' judgments about consumers' need for advance care planning (ACP) and comfort levels in discussing ACP. Providers (448 registered nurses and social workers) judged vignettes based on hypothetical consumers. Hierarchical linear models indicated providers judged consumers who were older, had end-stage diagnoses, multiple emergency department visits, and uninvolved caregivers as most in need of ACP. These variables explained 10% of the variance in judgments. Providers' beliefs about ACP predicted judgments of need for ACP and comfort level in discussing ACP. Provider characteristics explained more variance in comfort levels (44%) than in judgments of need (20%). This study demonstrates the need for tailored educational programs to increase comfort levels and address ACP misconceptions.

A Longitudinal Investigation of Task and Contextual Performance Influences on Promotability Judgments

Promotions in organizations traditionally have represented the principal measure of career success, and they tend to be based on evaluations or judgments of employees' promotability made by supervisors. Yet theory and research on the antecedents of promotability judgments have presented an inconsistent and ambiguous picture of just what factors are best predictive of such evaluations. In the present investigation, longitudinal data obtained from supervisors of professional employees were used to rigorously test the relative influence of task and contextual performance on judgments of promotability. Results indicate that task and contextual performance not only explain unique variance in judgments of promotability but also interact, such that subordinates who excel in task performance and in the job dedication aspect of contextual performance are judged more suitable for promotion than subordinates who excel in one but not in the other. Implications of results are discussed and future research directions are offered.

Predicting beauty: Fractal dimension and visual complexity in art

Visual complexity has been known to be a significant predictor of preference for artistic works for some time. The first study reported here examines the extent to which perceived visual complexity in art can be successfully predicted using automated measures of complexity. Contrary to previous findings the most successful predictor of visual complexity was Gif compression. The second study examined the extent to which fractal dimension could account for judgments of perceived beauty. The fractal dimension measure accounts for more of the variance in judgments of perceived beauty in visual art than measures of visual complexity alone, particularly for abstract and natural images. Results also suggest that when colour is removed from an artistic image observers are unable to make meaningful judgments as to its beauty.

Are discrimination thresholds a valid measure of variance for judgments of slant from texture?

There have been many experiments reported in the literature that have employed discrimination procedures to estimate the variance of observers' slant judgments from texture and binocular disparity, both individually and in combination. The research described in the present article identifies two serious methodological flaws in these studies. Although discrimination thresholds can be influenced by the variance of observers' slant estimates, they can also be affected by systematic biases in observers' judgments, and the presence of 2D cues that are irrelevant to the perception of slant. A series of five experiments is reported to show that: (1) the slants of surfaces specified by texture gradients can be systematically underestimated; (2) surfaces specified by texture gradients appear significantly less slanted than equivalent surfaces specified by binocular disparity; (3) the difference in bias between observers' slant judgments from stereo and texture may be more important than their relative variance in determining how these cues are weighted when presented in combination; (4) observers may be less sensitive to variations in apparent slant from texture than they are to variations in 2D cues that are unrelated to the perception of slant; and (5) these 2D cues may be the primary source of information for discriminating images of textured surfaces. These findings provide strong evidence that the results of prior discrimination studies have been misinterpreted because of the confounding effects of bias and/or 2D cues, and that this has resulted in several questionable conclusions that have been broadly accepted within the field.

Corrections to: Are discrimination thresholds a valid measure of variance for judgments of slant from texture?

Corrections to: Are discrimination thresholds a valid measure of variance for judgments of slant from texture?

Stability and Change of Well Being: An Experimentally Enhanced Latent State-Trait-Error Analysis

This study uses longitudinal panel data and short-term retest data from the same respondents in the German Socio-economic Panel to estimate the contribution of state and trait variance to the reliable variance in judgments of life satisfaction and domain satisfaction. The key finding is that state and trait variance contribute approximately equally to the reliable variance in well being measures. Most of the occasion specific variance is random measurement error, although occasion-specific variation in state variance makes a reliable contribution for some measures. Moreover, the study shows high similarity in life satisfaction and average domain satisfaction for the stable trait component (r = .97), indicating that these two measures are influenced by the same stable dispositions. In contrast, state variance of the two measures is distinct, although still highly correlated (r = .77). Error variances of the two measures are only weakly correlated, indicating that most of the error component is indeed due to random measurement error.