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"Social Bias"
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Social Desirability Bias in Self-reports of Physical Activity: Is an Exercise Identity the Culprit?
Like that of other normative behaviors, much of the research on physical exercise is based on self-reports that are prone to overreporting. While research has focused on identifying the presence and degree of overreporting, this paper fills an important gap by investigating its causes. The explanation based in impression management will be challenged, using an explanation based in identity theory as an arguably better fitting alternative. Respondents were randomly assigned to one of two conditions: (1) a web instrument using direct survey questions, or (2) a chronological reporting procedure using text messaging. Comparisons to validation data from a reverse record check indicate significantly greater rates of overreporting in the web condition than in the text condition. Results suggest that measurement bias is associated with the importance of the respondents' exercise identity, prompted by the directness of the conventional survey question. Findings call into question the benefit of self-administration for bias reduction in measurement of normative behaviors.
Journal Article
The Experiential Advantage in Consumption: Evidence from Hungary
Previous research indicates that individuals derive greater happiness from spending on experiences than on material possessions. However, these studies have relied primarily on U.S. samples and research designs in which participants directly rated their happiness with recalled purchases. This study examines whether the “experiential advantage” holds in a non-U.S. context, specifically among two samples from Hungary in East-Central Europe, which differs from the U.S. in terms of socioeconomic conditions, cultural values, and consumer behavior. In addition, we examine whether reported happiness from purchases may be influenced by socially desirable responding due to negative reputations of materialistic values. Using self-administered online surveys that ensure respondent anonymity and a between-subject design in which respondents do not directly compare the happiness returns of experiential and material purchases, we find that people report greater happiness from experiential purchases than from material ones. Our results indicate a substantial happiness gap in the relative absence of social desirability bias. However, we also find that socially desirable responding can affect the size of the estimated happiness gap. Nevertheless, this moderating effect appears to be relatively modest or imprecisely estimated compared to the overall size of the happiness gap, suggesting that it is unlikely to undermine the validity of the happiness gap between experiential and material purchases.
Journal Article
Algorithmic bias
Often machine learning programs inherit social patterns reflected in their training data without any directed effort by programmers to include such biases. Computer scientists call this algorithmic bias. This paper explores the relationship between machine bias and human cognitive bias. In it, I argue similarities between algorithmic and cognitive biases indicate a disconcerting sense in which sources of bias emerge out of seemingly innocuous patterns of information processing. The emergent nature of this bias obscures the existence of the bias itself, making it difficult to identify, mitigate, or evaluate using standard resources in epistemology and ethics. I demonstrate these points in the case of mitigation techniques by presenting what I call ‘the Proxy Problem’. One reason biases resist revision is that they rely on proxy attributes, seemingly innocuous attributes that correlate with socially-sensitive attributes, serving as proxies for the socially-sensitive attributes themselves. I argue that in both human and algorithmic domains, this problem presents a common dilemma for mitigation: attempts to discourage reliance on proxy attributes risk a tradeoff with judgement accuracy. This problem, I contend, admits of no purely algorithmic solution.
Journal Article
Racial Capitalism: A Fundamental Cause of Novel Coronavirus (COVID-19) Pandemic Inequities in the United States
Racial capitalism is a fundamental cause of the racial and socioeconomic inequities within the novel coronavirus pandemic (COVID-19) in the United States. The overrepresentation of Black death reported in Detroit, Michigan is a case study for this argument. Racism and capitalism mutually construct harmful social conditions that fundamentally shape COVID-19 disease inequities because they (a) shape multiple diseases that interact with COVID-19 to influence poor health outcomes; (b) affect disease outcomes through increasing multiple risk factors for poor, people of color, including racial residential segregation, homelessness, and medical bias; (c) shape access to flexible resources, such as medical knowledge and freedom, which can be used to minimize both risks and the consequences of disease; and (d) replicate historical patterns of inequities within pandemics, despite newer intervening mechanisms thought to ameliorate health consequences. Interventions should address social inequality to achieve health equity across pandemics.
Journal Article
Nudging Toward Diversity: Applying Behavioral Design to Faculty Hiring
This narrative and integrative literature review synthesizes the literature on when, where, and how the faculty hiring process used in most American higher education settings operates with implicit and cognitive bias. The literature review analyzes the “four phases” of the faculty hiring process, drawing on theories from behavioral economics and social psychology. The results show that although much research establishes the presence of bias in hiring, relatively few studies examine interventions or “nudges” that might be used to mitigate bias and encourage the recruitment and hiring of faculty identified as women and/or faculty identified as being from an underrepresented minority group. This article subsequently makes recommendations for historical, quasi-experimental, and randomized studies to test hiring interventions with larger databases and more controlled conditions than have previously been used, with the goal of establishing evidence-based practices that contribute to a more inclusive hiring process and a more diverse faculty.
Journal Article
Social Desirability Bias in Child-Report Social Well-Being: Evaluation of the Children’s Social Desirability Short Scale Using Item Response Theory and Examination of Its Impact on Self-Report Family and Peer Relationships
Research on child well-being largely relies on children’s self-report data, potentially biased by social desirability (SD). In this study, we aim to (1) evaluate the psychometric properties of the Children’s Social Desirability Short (CSD-S) scale, and (2) examine if and, if so, how SD systematically biases child-report family and peer relationships as indicators of social well-being. In spring 2015, 843 elementary school children (aged 10) and their parents were surveyed on well-being indicators and SD measured with the 14-items Children’s Social Desirability Short (CSD-S) scale. The CSD-S was evaluated using nonparametric Item Response Theory (NIRT). Linear mixed-effects regression models based on multiple imputations of multilevel missing data were run to examine the role of SD in self-report social well-being in addition to socio-demographic characteristics, accounting for the nested structure of the data (students were sampled at class level). Applying NIRT, we identified a 13-items subset of the CSD-S with double monotonicity. Cronbach’s alpha was .82. When controlling for children’s socio-demographic characteristics, SD significantly positively predicted subjective evaluations of family relationships (
B
= 0.04,
t
(49272) = 7.45,
p
< .001), whereas it significantly negatively predicted self-report deviant behavior performed towards peers (
B
= −0.03,
t
(39927) = −14.40,
p
< .001) and experienced from peers (
B
= −.0.01,
t
(39028) = −2.86,
p
= .002). SD bias explained additional 22 percent of variance in self-report deviant behavior performed towards peers. Since SD impacts the validity of self-report well-being, child indicators research should include age-specific SD scales, e.g., the CSD-S, and control for the bias in statistical analyses.
Journal Article
When to Worry about Sensitivity Bias: A Social Reference Theory and Evidence from 30 Years of List Experiments
Eliciting honest answers to sensitive questions is frustrated if subjects withhold the truth for fear that others will judge or punish them. The resulting bias is commonly referred to as social desirability bias, a subset of what we label sensitivity bias. We make three contributions. First, we propose a social reference theory of sensitivity bias to structure expectations about survey responses on sensitive topics. Second, we explore the bias-variance trade-off inherent in the choice between direct and indirect measurement technologies. Third, to estimate the extent of sensitivity bias, we meta-analyze the set of published and unpublished list experiments (a.k.a., the item count technique) conducted to date and compare the results with direct questions. We find that sensitivity biases are typically smaller than 10 percentage points and in some domains are approximately zero.
Journal Article
Social Vulnerability and Racial Inequality in COVID-19 Deaths in Chicago
Although the current COVID-19 crisis is felt globally, at the local level, COVID-19 has disproportionately affected poor, highly segregated African American communities in Chicago. To understand the emerging pattern of racial inequality in the effects of COVID-19, we examined the relative burden of social vulnerability and health risk factors. We found significant spatial clusters of social vulnerability and risk factors, both of which are significantly associated with the increased COVID-19-related death rate. We also found that a higher percentage of African Americans was associated with increased levels of social vulnerability and risk factors. In addition, the proportion of African American residents has an independent effect on the COVID-19 death rate. We argue that existing inequity is often highlighted in emergency conditions. The disproportionate effects of COVID-19 in African American communities are a reflection of racial inequality and social exclusion that existed before the COVID-19 crisis.
Journal Article
Gender Differences in Ethics Research: The Importance of Controlling for the Social Desirability Response Bias
Gender is one of the most frequently studied variables within the ethics literature. In prior studies that find gender differences, females consistently report more ethical responses than males. However, prior research also indicates that females are more prone to responding in a socially desirable fashion. Consequently, it is uncertain whether gender differences in ethical decision-making exist because females are more ethical or perhaps because females are more prone to the social desirability response bias. Using a sample of 30 scenarios from prior studies that find gender differences, we examine whether these gender differences remain robust once social desirability is controlled for in the analysis. Our data suggest that the effect of gender on ethical decision-making is largely attenuated once social desirability is included in the analysis. In essence, the social desirability response bias appears to be driving a significant portion of the relationship between gender and ethical decision-making. We discuss several important research implications of this study.
Journal Article