All human social groups are human, but some are more human than others: A comprehensive investigation of the implicit association of "Human" to US racial/ethnic groups

Attribution of undesirable character traits, rather than trait-based dehumanization, predicts punishment decisions

Previous work has reported that the extent to which participants dehumanized criminals by denying them uniquely human character traits such as refinement, rationality and morality predicted the severity of the punishment endorsed for them. We revisit this influential finding across six highly powered and pre-registered studies. First, we conceptually replicate the effect reported in previous work, demonstrating that our method is sensitive to detecting relationships between trait-based dehumanization and punishment should they occur. We then investigate whether the apparent relationship between trait-based dehumanization and punishment is driven by the desirability of the traits incorporated into the stimulus set, their perceived humanness, or both. To do this, we asked participants to rate the extent to which criminals possessed uniquely human traits that were either socially desirable (e.g. cultured and civilized) or socially undesirable (e.g. arrogant and bitter). Correlational and experimental evidence converge on the conclusion that apparent evidence for the relationship between trait-based dehumanization and punishment is better explained by the extent to which participants attribute socially desirable attributes to criminals rather than the extent to which they attribute uniquely human attributes. These studies cast doubt on the hypothesized causal relationship between trait-based dehumanization and harm, at least in this context.

Intersectional Male-Centric and White-Centric Biases in Collective Concepts

In principle, the fundamental concepts person, woman, and man should apply equally to people of different genders and races/ethnicities. In reality, these concepts might prioritize certain groups over others. Based on interdisciplinary theories of androcentrism, we hypothesized that (a) person is more associated with men than women (person = man) and (b) woman is more associated with women than man is with men (i.e., women are more gendered: gender = woman). We applied natural language processing tools (specifically, word embeddings) to the linguistic output of millions of individuals (specifically, the Common Crawl corpus). We found the hypothesized person = man / gender = woman bias. This bias was stronger about Hispanic and White (vs. Asian) women and men. We also uncovered parallel biases favoring White individuals in the concepts person, woman, and man. Western society prioritizes men and White individuals as people and "others" women as people with gender, with implications for equity across policy- and decision-making contexts.

White Americans' preference for Black people in advertising has increased in the past 66 y: A meta-analysis

This study investigates Black and White consumers' preferences for Black versus White people in United States advertising contexts over 66 y, from 1956 until 2022, a time in which the United States has experienced significant ethno-racial diversification. Examining Black and White consumers' reactions to visual advertising over more than half a century offers a unique and dynamic view of interracial preferences. Mass advertising reaches an audience of billions and can shape people's attitudes and behavior, emphasizing the relevance of clarifying the influence of race in advertising, how it has evolved over time, and how it may contribute to mitigating discrimination based on racial perceptions. A meta-analysis of extant experiments into the relationship between the depicted endorser's race (i.e., the model in a visual ad) and the reaction of Black and White viewers pertains to 332 effect sizes from 62 studies reported in 52 scientific papers, comprising 10,186 Black and White participants. Our results are anchored in a conceptual framework, including a comprehensive set of perceiver (viewer), target (endorser), social/societal context, and publication characteristics. Without accounting for temporal dynamics, the results indicate ingroup favoritism, such that White viewers prefer White models and Black viewers prefer Black models. But by controlling for the publication year, it is possible to observe a time-dependent trend: Historically, White consumers preferred endorsers of the same race, but this preference has significantly shifted toward Black endorsers in recent years. In contrast, the level of Black consumers' reactions to endorsers of the same race remains largely unchanged over time.

Ideological asymmetries in online hostility, intimidation, obscenity, and prejudice

To investigate ideological symmetries and asymmetries in the expression of online prejudice, we used machine-learning methods to estimate the prevalence of extreme hostility in a large dataset of Twitter messages harvested in 2016. We analyzed language contained in 730,000 tweets on the following dimensions of bias: (1) threat and intimidation, (2) obscenity and vulgarity, (3) name-calling and humiliation, (4) hatred and/or racial, ethnic, or religious slurs, (5) stereotypical generalizations, and (6) negative prejudice. Results revealed that conservative social media users were significantly more likely than liberals to use language that involved threat, intimidation, name-calling, humiliation, stereotyping, and negative prejudice. Conservatives were also slightly more likely than liberals to use hateful language, but liberals were slightly more likely than conservatives to use obscenities. These findings are broadly consistent with the view that liberal values of equality and democratic tolerance contribute to ideological asymmetries in the expression of online prejudice, and they are inconsistent with the view that liberals and conservatives are equally prejudiced.

All human social groups are human, but some are more human than others: A comprehensive investigation of the implicit association of "Human" to US racial/ethnic groups

All human groups are equally human, but are they automatically represented as such? Harnessing data from 61,377 participants across 13 experiments (six primary and seven supplemental), a sharp dissociation between implicit and explicit measures emerged. Despite explicitly affirming the equal humanity of all racial/ethnic groups, White participants consistently associated Human (relative to Animal) more with White than Black, Hispanic, and Asian groups on Implicit Association Tests (IATs; experiments 1-4). This effect emerged across diverse representations of Animal that varied in valence (pets, farm animals, wild animals, and vermin; experiments 1-2). Non-White participants showed no such Human=Own Group bias (e.g., Black participants on a White-Black/Human-Animal IAT). However, when the test included two outgroups (e.g., Asian participants on a White-Black/Human-Animal IAT), non-White participants displayed Human=White associations. The overall effect was largely invariant across demographic variations in age, religion, and education but did vary by political ideology and gender, with self-identified conservatives and men displaying stronger Human=White associations (experiment 3). Using a variance decomposition method, experiment 4 showed that the Human=White effect cannot be attributed to valence alone; the semantic meaning of Human and Animal accounted for a unique proportion of variance. Similarly, the effect persisted even when Human was contrasted with positive attributes (e.g., God, Gods, and Dessert; experiment 5a). Experiments 5a-b clarified the primacy of Human=White rather than Animal=Black associations. Together, these experiments document a factually erroneous but robust Human=Own Group implicit stereotype among US White participants (and globally), with suggestive evidence of its presence in other socially dominant groups.