An examination of ingroup preferences among people with multiple socially stigmatized identities

Jiang, Congjiao; Vitiello, Christine; Axt, Jordan; Campbell, Jessica T.; Ratliff, Kate A.

doi:10.1080/15298868.2019.1657937

Cited by 13 publications

(11 citation statements)

References 38 publications

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“…Although an empirical question that is not yet answered, it is possible that when racial identity is made salient through, for example, contemporary social movements (e.g., Black Lives Matter), people of color may further embrace and celebrate their race and ethnicity and support prototypical candidates of color to a greater extent, including those with darker skin tones. In fact, studies suggest that when racial and ethnic identities are made salient, certain cognitive processes are activated (e.g., Benjamin et al., 2010; Vecci & Zelinsky, 2019) which then may lead people to show more in‐group preferences (Jiang et al., 2021). Additionally, SIT suggests that in the eye of the evaluators, the perception of a prototypical leader changes depending on the group the evaluators belong to (Hogg, 2001; Hogg et al., 2006).…”

Section: Discussionmentioning

confidence: 99%

“…In line with research on the effects of comparison groups and reference groups on interpersonal judgments (e.g., Boyce et al., 2010; Richins, 1991), we also anticipated that candidates who identify as African American would be received more positively than Mexican American candidates of the same skin tone, who may be seen as darker in relative skin tone for their group and higher in cultural foreignness. Conversely, we expected non‐White participants, whose racial and ethnic identity may have been made salient by the most recent social justice movements (e.g., Black Lives Matter), to express more positive attitudes toward the more dark‐skinned candidates and favor in‐group members (Jiang et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

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Dark faces in white spaces: The effects of skin tone, race, ethnicity, and intergroup preferences on interpersonal judgments and voting behavior

Chirco

Buchanan

2022

Anal Soc Iss & Public Policy

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Across three experimental studies, we explored how a political candidate's intersections of skin tone, race, and ethnicity affect voting preferences and interpersonal judgments (e.g., warmth, trustworthiness, expertise). Study 1 assessed whether White participants would favor a light‐skinned (vs. dark‐skinned) African American candidate. Study 2 investigated participant (White vs. non‐White) voting preferences based on the interaction between candidate race/ethnicity and relative skin tone (lighter vs. darker). In Study 3, we examined the influence of candidate race/ethnicity on voters’ preferences as well as the accuracy and impact of memory for candidate skin tone. Supporting our hypotheses, White participants generally held more negative attitudes (e.g., expressed less warmth, perceived candidates as less trustworthy) and were less likely to vote for underrepresented candidates with darker skin tones than non‐White participants were. Additionally, voters remembered politicians as having a lighter skin tone, and the extent of such bias predicted warmth, perceived trustworthiness, and expertise of the candidate. While candidate race/ethnicity on its own did not affect voting preferences and attitudes, it significantly influenced voters when race/ethnicity was associated with certain skin tones (i.e., brown skin tone). Theoretical, practical, and political implications for judgments influenced by skin tone and race/ethnicity of candidates are discussed.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dark faces in white spaces: The effects of skin tone, race, ethnicity, and intergroup preferences on interpersonal judgments and voting behavior

Chirco

Buchanan

2022

Anal Soc Iss & Public Policy

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“…. Black participants’ explicit attitudes reflected an ingroup preference” ( Jiang et al, 2019 ). In 2007, Cunningham wrote that the “distinction between automatic and controlled processes now lies at the heart of several of the most influential models of evaluative processing” ( Cunningham & Zelazo, 2007 , p. 97).…”

Section: Explicit Responsementioning

confidence: 99%

Invalid Claims About the Validity of Implicit Association Tests by Prisoners of the Implicit Social-Cognition Paradigm

Schimmack

2021

Perspect Psychol Sci

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In a prior publication, I used structural equation modeling of multimethod data to examine the construct validity of Implicit Association Tests. The results showed no evidence that IATs measure implicit constructs (e.g., implicit self-esteem, implicit racial bias). This critique of IATs elicited several responses by implicit social-cognition researchers, who tried to defend the validity and usefulness of IATs. I carefully examine these arguments and show that they lack validity. IAT proponents consistently ignore or misrepresent facts that challenge the validity of IATs as measures of individual differences in implicit cognitions. One response suggests that IATs can be useful even if they merely measure the same constructs as self-report measures, but I find no support for the claim that IATs have practically significant incremental predictive validity. In conclusions, IATs are widely used without psychometric evidence of construct or predictive validity.

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“…How an individual perceives oneself influences how they perceive actions such as disabling actions towards themselves [68], which in turn influences what role they see themselves occupying in relation to AI/ML discourses. It also influences intergroup relationships [68,69] between disabled and non-disabled people within the AI/ML discourses and the relationship between different disability groups linked to different identities of self.…”

Section: Portrayal and Role Identity And Stake Narrative Of Disablementioning

confidence: 99%

“…It also entails the danger that others instrumentalize disabled people of the consumer flavor to question disabled people that are looking at issues beyond consumerism. As such, AI/ML discourses that focus so exclusively on therapeutic and non-therapeutic consumer identities influence intergroup relationships [68,69] between disabled and non-disabled people within the AI/ML discourses and between disability groups and disabled people exhibiting different identities, roles, and stakes.…”

Section: Linking Techno-optimism To the Role Identity And Stake Narmentioning

confidence: 99%

Coverage of Artificial Intelligence and Machine Learning within Academic Literature, Canadian Newspapers, and Twitter Tweets: The Case of Disabled People

Lillywhite

Wolbring

2020

Societies

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Artificial intelligence (AI) and machine learning (ML) advancements increasingly impact society and AI/ML ethics and governance discourses have emerged. Various countries have established AI/ML strategies. “AI for good” and “AI for social good” are just two discourses that focus on using AI/ML in a positive way. Disabled people are impacted by AI/ML in many ways such as potential therapeutic and non-therapeutic users of AI/ML advanced products and processes and by the changing societal parameters enabled by AI/ML advancements. They are impacted by AI/ML ethics and governance discussions and discussions around the use of AI/ML for good and social good. Using identity, role, and stakeholder theories as our lenses, the aim of our scoping review is to identify and analyze to what extent, and how, AI/ML focused academic literature, Canadian newspapers, and Twitter tweets engage with disabled people. Performing manifest coding of the presence of the terms “AI”, or “artificial intelligence” or “machine learning” in conjunction with the term “patient”, or “disabled people” or “people with disabilities” we found that the term “patient” was used 20 times more than the terms “disabled people” and “people with disabilities” together to identify disabled people within the AI/ML literature covered. As to the downloaded 1540 academic abstracts, 234 full-text Canadian English language newspaper articles and 2879 tweets containing at least one of 58 terms used to depict disabled people (excluding the term patient) and the three AI terms, we found that health was one major focus, that the social good/for good discourse was not mentioned in relation to disabled people, that the tone of AI/ML coverage was mostly techno-optimistic and that disabled people were mostly engaged with in their role of being therapeutic or non-therapeutic users of AI/ML influenced products. Problems with AI/ML were mentioned in relation to the user having a bodily problem, the usability of AI/ML influenced technologies, and problems disabled people face accessing such technologies. Problems caused for disabled people by AI/ML advancements, such as changing occupational landscapes, were not mentioned. Disabled people were not covered as knowledge producers or influencers of AI/ML discourses including AI/ML governance and ethics discourses. Our findings suggest that AI/ML coverage must change, if disabled people are to become meaningful contributors to, and beneficiaries of, discussions around AI/ML.

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An examination of ingroup preferences among people with multiple socially stigmatized identities

Cited by 13 publications

References 38 publications

Dark faces in white spaces: The effects of skin tone, race, ethnicity, and intergroup preferences on interpersonal judgments and voting behavior

Dark faces in white spaces: The effects of skin tone, race, ethnicity, and intergroup preferences on interpersonal judgments and voting behavior

Invalid Claims About the Validity of Implicit Association Tests by Prisoners of the Implicit Social-Cognition Paradigm

Coverage of Artificial Intelligence and Machine Learning within Academic Literature, Canadian Newspapers, and Twitter Tweets: The Case of Disabled People

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