Pomona College
  • Claremont, United States
Recent publications
Adolescence is a period of rapid social changes that may have important implications for the ways adolescents think, feel, and behave in their close relationships. According to family systems theory, adolescents’ attachment-related changes have the potential to spread throughout their family system, leading to coordinated changes in parents’ and adolescents’ attachment styles over time. The present study analyzed data from 205 adolescents (MageT1 = 14.0, SD = 0.9; 44% female, 56% male; 51% White, 33% African American, 3% Hispanic/Latino, 1% Asian American, 12% another race/ethnicity) and their parents (196 mothers, 105 fathers; median household incomeT1 = $100,000) who completed self-report measures of their general attachment styles annually for 5 years. Using a latent growth curve framework, we examined the extent of coordination among adolescents’ and parents’ long-term trajectories and shorter term fluctuations in attachment security. The results revealed a push-and-pull dynamic between mothers’ and adolescents’ long-term trajectories of attachment security. Mothers who reported higher initial levels of attachment anxiety tended to have adolescent children who reported higher initial levels of avoidance. Additionally, adolescents who increased in attachment avoidance over time tended to have mothers who increased in attachment anxiety. Mothers and fathers mirrored each other’s patterns of attachment security as their children navigated their teenage years, reporting similar initial levels of attachment avoidance and synchronized shorter term fluctuations in attachment anxiety and avoidance across time.
Losing Lauren Berlant in 2021 was depressing. For weeks I would wake abruptly in the early morning only to cry: my world—our world—had become profoundly impoverished with Lauren’s passing. Mourning with friends from the University of Chicago, where Berlant was the George M. Pullman Distinguished Service Professor of English, helped to communalize the experience. So did returning to their vast archive of work, which spans eight books (two co-authored), dozens of articles and chapters, and many interviews and recorded lectures over more than thirty years. To differing degrees, for all the contributors to this Critical Exchange, working through Berlant’s ideas and concepts was also a way of working through their loss and what it means for our discipline, especially as political theorists were becoming more aware of Berlant’s scholarship following the prescient intervention of Cruel Optimism (2011).
People place value on emotion categories that inform which emotions to cultivate and which to regulate in life. Here, we examined how people’s beliefs about emotion categories varied along three valence-related dimensions: evaluation (good, bad), hedonic feeling (pleasure, displeasure), and desirability (want to feel, do not want to feel). In Studies 1A and 1B, we found that evaluative (good/bad) and hedonic (pleasant/unpleasant) ratings were distinct for certain emotions including lust, anger, shame, fear, and guilt. In Study 2, we found that emotion valuation depended on cultural background in a sample of Asian Americans and Caucasian Americans. Overall, Asian American participants evaluated certain emotions (including, but not limited to, anger, sadness, guilt, and shame) more positively than Caucasian American participants, and this difference was more pronounced on the evaluative rating dimension. Finally, in Study 3, we examined how evaluative and hedonic dimensions further relate with the desire to experience certain emotions and the emotions that people believe they feel in everyday life. Our findings support a model in which evaluative and hedonic dimensions of emotion valuation predict desired emotional states, which in turn predicts beliefs about the reported frequency of emotions experienced in everyday life.
Network deconvolution (ND) is a method to reconstruct a direct-effect network describing direct (or conditional) effects (or associations) between any two nodes from a given network depicting total (or marginal) effects (or associations). Its key idea is that, in a directed graph, a total effect can be decomposed into the sum of a direct and an indirect effects, with the latter further decomposed as the sum of various products of direct effects. This yields a simple closed-form solution for the direct-effect network, facilitating its important applications to distinguish direct and indirect effects. Despite its application to undirected graphs, it is not well known why the method works, leaving it with skepticism. We first clarify the implicit linear model assumption underlying ND, then derive a surprisingly simple result on the equivalence between ND and use of precision matrices, offering insightful justification and interpretation for the application of ND to undirected graphs. We also establish a formal result to characterize the effect of scaling a total-effect graph. Finally, leveraging large-scale genome-wide association study data, we show a novel application of ND to contrast marginal versus conditional genetic correlations between body height and risk of coronary artery disease; the results align with an inferred causal directed graph using ND. We conclude that ND is a promising approach with its easy and wide applicability to both directed and undirected graphs.
Kahneman's criticism of neoclassical rationality was central to his research programme. He argued that rationality understood as temporal consistency among preferences and beliefs is inapt as a descriptive and prescriptive standard of decision-making. Descriptively, consistency ignores high decision costs and biases, such as framing effects. Prescriptively, it is problematic since it neglects the processual nature of choice and the crucial role of regret. Instead, Kahneman argued in favour of using reasonableness as a standard, though he did not fully develop the concept in his work.
This article serves as a commentary on Michael Hallsworth's 2023 piece, ‘A manifesto for applying behavioural science,’ featured in Nature Human Behaviour . The manifesto was prompted by methodological, practical and normative critiques directed at behavioural science and its role in public policy. In this commentary, I argue that the manifesto presents numerous insightful and constructive reform proposals regarding the scope, methods and values in behavioural science, which can help advance the field of behavioural public policy. While there is much to agree with, I contend in this commentary that applied behavioural science can and should delve deeper into the study of socially and culturally embedded processes of goal formation. Additionally, it should explore the institutional conditions necessary for individuals to formulate their goals competently and in a self-determined manner.
Climate change is currently one of humanity’s greatest threats. To help scholars understand the psychology of climate change, we conducted an online quasi-experimental survey on 59,508 participants from 63 countries (collected between July 2022 and July 2023). In a between-subjects design, we tested 11 interventions designed to promote climate change mitigation across four outcomes: climate change belief, support for climate policies, willingness to share information on social media, and performance on an effortful pro-environmental behavioural task. Participants also reported their demographic information (e.g., age, gender) and several other independent variables (e.g., political orientation, perceptions about the scientific consensus). In the no-intervention control group, we also measured important additional variables, such as environmentalist identity and trust in climate science. We report the collaboration procedure, study design, raw and cleaned data, all survey materials, relevant analysis scripts, and data visualisations. This dataset can be used to further the understanding of psychological, demographic, and national-level factors related to individual-level climate action and how these differ across countries.
Empathy requires the ability to understand another’s point of view and is critical for motivating a person to help others. However, little is known about the link between experiences of empathic emotional engagement in close friendships during adolescence and neural correlates of empathy in adulthood. Beginning in 1998, N = 88 participants drawn from a demographically diverse community sample were observed annually from ages 13 to 21 and rated on the amount of emotional engagement displayed toward a close friend during a support task. At approximately age 24, participants underwent functional brain imaging while a partner or stranger was under distress. Contrary to predictions, greater emotional engagement with close friends during adolescence corresponded prospectively with reduced temporal pole activity (a region associated with cognitive empathy and perspective taking) while observing threats directed at others. Results have implications for understanding the neurodevelopmental roots of empathy.
Modern poriferans are classified into four classes—Calcarea, Demospongiae, Hexactinellida and Homoscleromorpha—the recognition of which in fossil specimens almost exclusively relies on spicule morphology and arrangement. Early fossil representatives of the phylum Porifera are morphologically diverse, and many of them problematically display characteristics that are incompatible with the classification scheme developed for modern taxa. Critically, hexactine spicules—a diagnostic feature of hexactinellids among modern taxa—are found in various Cambrian and Ordovician taxa that cannot be accommodated within the hexactinellid body plan. Here we describe a new poriferan from the Drumian Marjum Formation of Utah, Polygoniella turrelli gen. et sp. nov., which exhibits a unique combination of complex anatomical features for a Cambrian form, including a syconoid-like organization, a thick body wall, and a multi-layered hexactin-based skeleton. The hexactinellid-like body wall architecture of this new species supports a Cambrian origin of the hexactinellid body plan and provides valuable insights into character evolution in early glass sponges.
During conversation, people often endeavor to convey information in an understandable way (finding common ground) while also sharing novel or surprising information (exploring new ground). Here, we test how friends and strangers balance these two strategies to connect with each other. Using fMRI hyperscanning, we measure a preference for common ground as convergence over time and exploring new ground as divergence over time by tracking dyads’ neural and linguistic trajectories over the course of semi-structured intimacy-building conversations. In our study, 60 dyads (30 friend dyads) engaged in a real-time conversation with discrete prompts and demarcated turns. Our analyses reveal that friends diverge neurally and linguistically: their neural patterns become more dissimilar over time and they explore more diverse topics. In contrast, strangers converge: neural patterns and language become more similar over time. The more a conversation between strangers resembles the exploratory conversations of friends, the more they enjoy it. Our results highlight exploring new ground as a strategy for a successful conversation.
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1,133 members
Laura L Mays Hoopes
  • Department of Biology
Yuqing Melanie Wu
  • Department of Computer Science
Gizem Karaali
  • Department of Mathematics
Kim B. Bruce
  • Department of Computer Science
Lise Abrams
  • Department of Linguistics and Cognitive Science
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Claremont, United States