Sylvia Perry

Bias awareness—concern about one's propensity to express bias—has been linked togreater recognition of racial bias, but prior work has relied largely on self-reports. We testedwhether bias awareness predicts observable, real-time responses to interpersonal racism. Whiteadults (N=123) viewed videos depicting White children engaging in blatant and subtle racismtoward Black peers and then discussed each incident. We coded verbal tentativeness, nonverbalconfidence, and color-conscious and colorblind racial ideology (CBRI) language. Bias awarenesspredicted greater behavioral confidence—fewer tentative words and more nonverbal confidence.Participants responded more confidently and used greater color-conscious and less CBRIlanguage toward blatant (vs. subtle) racism. Contrary to predictions, bias awareness did notpredict responses to subtle racism, only predicting reduced CBRI language in the blatantcondition. These findings suggest that bias awareness is associated with White individuals’confidence when discussing racism, though subtle racism is likely downplayed, even amongthose higher in bias awareness.

Family discussions may be an important context for shaping White children’s developing racial attitudes, yet the majority of White parents in the U.S. report that they either de-emphasize or avoid discussions of race and racism with their White children. The current study presents a qualitative analysis of racial messages communicated during a guided discussion task designed to scaffold color-conscious conversations about vignettes depicting interpersonal racism. Participants, recruited from a Midwestern U.S. city between 2018 and 2020, included 87 self-identified White parents (91.5% women, 8.5% men; Mage = 42.57 years, SD = 5.14) and their parent-identified White children (ages 8–12; 53% girls, 47% boys; Mage = 8.95 years, SD = 1.16). Most parents were highly educated, middle-class or upper-middle-class, married, and liberal or liberal-leaning. Findings revealed that many parents and children used racial language and endorsed color-conscious messages, such as acknowledging that racial prejudice had occurred in the vignettes. However, some dyads redirected the conversation away from race or made external attributions for racist behavior rather than attributing responsibility to White perpetrators. Together, these findings suggest that structured scaffolding may support more explicit conversations about racism in White families while also highlighting variability in how parents and children interpret and discuss racist behavior.

Bias feedback indicating that one's responses may reflect racial bias despite egalitarian intentions can function as a moral threat to the self. Across three studies and four samples (N = 1,266), we tested whether high (vs. low) bias feedback elicits shame and defensiveness, whether bias awareness shapes those responses, and how shame and defensiveness relate to self-concept clarity, moral self-image, and self-esteem after feedback. High (vs. low) bias feedback increased both shame and defensiveness. Bias awareness was positively associated with shame and lower defensiveness, though effects varied across studies. Shame was most consistently associated with lower self-concept clarity, moral self-image, and self-esteem, indicating disruption in both self-understanding and self-evaluation. Defensiveness followed a narrower pattern in Studies 2 and 3, linked to relatively preserved self-concept clarity alongside lower moral self-image and self-esteem. Shame and defensiveness appear to be distinct responses to bias feedback with different short-term consequences for self-understanding and self-evaluation.

Graduate school can be a highly uncertain and stressful time. Stressors may be exacerbated for individuals with historically marginalized social identities within the academy (e.g., female students, students from low‐income backgrounds, and people of color). We predicted that female students and students of color would report more negative program experiences, and that these identities, along with financial status, would be associated with decreased intentions to pursue an academic career. In a survey of 1798 psychology doctoral students from 155 U.S. institutions, we examined students’ finances, program experiences, mental health, and intentions to remain in academia. On average, students reported feeling underpaid. Additionally, 29% of the sample reported that their stipends did not cover basic needs and 17% lacked university‐issued health insurance. Female students and students of color also reported more negative program experiences and worse mental health outcomes in comparison to male and White students, respectively. In a logistic regression including all factors predicting future career intentions, we found that female students, students who did not have university‐issued health insurance, and those with more negative program experiences were less likely to pursue an academic career after graduation. Experiences of psychology doctoral students in U.S. institutions may mirror and amplify racial, gender, and class inequities. For the field of psychology to become more equitable, better graduate funding and support for diversity and inclusion will be essential.

Democratic backsliding impacts both institutions and the psychological well-being of individuals living within them. In such contexts, individuals decide whether to support or oppose government actions that may erode democratic norms. In this longitudinal study, we examined partisan differences in subjective well-being during the early months of President Trump’s second term—a period marked by sweeping policy changes and heightened concerns about democratic decline. Across five weeks, Democrats consistently reported lower life satisfaction and happiness than Republicans. Republicans increased in well-being over time, whereas Democrats showed both linear and quadratic change, as initial decreases in well-being were followed by increases in well-being. Republicans were more supportive of the administration’s actions, while Democrats expressed greater support for actions taken against the administration. Greater support for administration actions was associated with higher well-being, whereas greater support for oppositional actions was correlated with lower well-being. These associations generally held even after controlling for political affiliation and demographics, suggesting that dissatisfaction with government actions carries psychological consequences beyond partisan identity. These findings highlight asymmetric well-being consequences during a period of democratic decline, showing that alignment with government actions may provide short-term psychological comfort, while opposition—though vital for democratic resilience—may carry psychological costs.

Across two studies, we investigate how public justifications of police violence and moral outrage emerge as competing responses with distinct implications for reform. In Study 1, we analyzed 257,401 comments from 57 widely viewed YouTube videos using large language models to detect justificatory rhetoric, expressions of outrage, and calls for accountability. Justifications were consistently associated with reduced reform-oriented discourse, whereas outrage strongly co-occurred with accountability language. When modeled together, each response showed stronger links to reform, consistent with mutual suppression and the idea that they function as opposing interpretive strategies. In Study 2, we experimentally manipulated victim race by exposing participants (N = 159) to severity-matched videos of police brutality. Justification and outrage again diverged, with justification associated with lower reform support and outrage associated with higher reform support. Participants were more likely to attribute superhuman traits to the Black victim—a racialized justification tied to reduced reform support and to weaker translation of outrage into reform. Outrage for the Black victim was also a more consistent predictor of reform than outrage for the White victim. Together, these findings show how justification and moral outrage function as competing responses to police violence, and how racialized justifications can shape the conditions under which outrage mobilizes collective demands for change.

Across two studies, we investigate how public justifications of police violence and moral outrage emerge as competing responses with distinct implications for reform. In Study 1, we analyzed 257,401 comments from 57 widely viewed YouTube videos using large language models to detect justificatory rhetoric, expressions of outrage, and calls for accountability. Justifications were consistently associated with reduced reform-oriented discourse, whereas outrage strongly co-occurred with accountability language. When modeled together, each response showed stronger links to reform, consistent with mutual suppression and the idea that they function as opposing interpretive strategies. In Study 2, we experimentally manipulated victim race by exposing participants (N = 159) to severity-matched videos of police brutality. Justification and outrage again diverged, with justification associated with lower reform support and outrage associated with higher reform support. Participants were more likely to attribute superhuman traits to the Black victim—a racialized justification tied to reduced reform support and to weaker translation of outrage into reform. Outrage for the Black victim was also a more consistent predictor of reform than outrage for the White victim. Together, these findings show how justification and moral outrage function as competing responses to police violence, and how racialized justifications can shape the conditions under which outrage mobilizes collective demands for change.

In this work, we introduce the Experience-Outcome Model of honest conversation. Our model advances three key ideas. First, a communicator’s decision to initiate a conversation is influenced by their expected experience during a conversation, in addition to the expected outcomes following the conversation. Second, these same factors influence a communicator’s decision to speak truthfully within a conversation, conditional on initiation. Third, when communicators expect the experience of a conversation to be negative but the outcomes of a conversation to be positive, this leads to self-regulatory conflict. After introducing the Experience-Outcome Model, we explain its implications for difficult conversations—conversations that are aversive because they can cause interpersonal harm. The Experience-Outcome Model explains why communicators fail to initiate difficult conversations and why they communicate dishonestly within them, even when communicators expect the conversations to lead to positive outcomes: The negative experience associated with harm aversion creates self-regulatory conflict. Drawing from the literature on self-regulation, we develop six key propositions that explain how psychological distance influences the experience of harm aversion within difficult conversations and, therefore, a communicator’s likelihood of overcoming this conflict. Our model deepens the current understanding of the psychological dynamics underlying honesty and social engagement. By applying the Experience-Outcome Model to difficult conversations, we provide insight into the psychology of self-regulation and everyday harm as well as provide practical guidance on managing, mentoring, and promoting others’ growth.

Objectives: Graduate school can be a highly uncertain and stressful time. Stressors may be exacerbated for individuals with historically marginalized social identities within the academy (e.g., female students, students from low-income backgrounds, and people of color). We predicted that female students and students of color would report more negative program experiences, and that these identities along with financial status, would be associated with a decreased intentions to pursue an academic career. Method: In a survey of 1,798 psychology doctoral students from 155 U.S. institutions, we examined students’ finances, program experiences, mental health, and intentions to remain in academia. Results: On average, students reported feeling underpaid. Additionally, 29% of the sample reported that their stipends did not cover basic needs and 17% lacked university-issued health insurance. Female students and students of color also reported more negative program experiences and worse mental health outcomes in comparison to male and White students, respectively. In a logistic regression including all factors predicting future career intentions, we found that female students, students who did not have university-issued health insurance, and those with more negative program experiences were less likely to pursue an academic career after graduation. Conclusions: Experiences of psychology doctoral students in US institutions may mirror and amplify racial, gender, and class inequities. For the field of psychology to become more equitable, better graduate funding and support for diversity and inclusion will be essential.

The study of how cognition and society interact is a complex endeavor that demands multiple methods and tools. Yet research in social cognition has only begun to capitalize on unsupervised machine learning (UML) tools that can uncover hidden patterns in data. In this tutorial we introduce UML as a complementary approach to traditional statistical methods. We illustrate four methods (K-means clustering, DBSCAN, PCA, and Market Basket Analysis) applied to data from Project Implicit and the Implicit Association Test. In the process, we show how UML can identify patterns and relationships that conventional methods might overlook. Throughout, we provide clear (and openly available) code and highlight important researcher decision-points in implementing UML in social cognition work. By bringing the advances of UML into social cognition we will be better equipped to tackle larger, more diverse, or multi-level datasets that reveal the complexities of our social world.