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Disconnected and distressed: The moderating role of thwarted belongingness in the racism–depression link

Steven M. Sanders, Lorelei A.M. Inaba, Emily M. Nguyen, Aliya Zehra, Tiffany R. Williams

Journal of Affective Disorders·2026

Objective Black individuals in Western countries face disproportionately high rates of depression, exacerbated in recent years by sociopolitical and structural stressors. The present study examines the associations between racism—across recent, lifetime, and stress-related domains—and depressive symptoms among Black Americans. By introducing thwarted belongingness as a potential moderator, the study aims to expand existing literature by exploring how social disconnection may intensify the psychological impact of racism and contribute to elevated depression risk. Methods A total of 314 Black Americans completed an online survey assessing their experiences of racism, symptoms of depression, and perceptions of thwarted belongingness. Results The findings align with extant literature that there is a relationship between racism and depression. Regression analysis indicated support for the hypotheses that thwarted belongingness moderates the relationship between depression and racism for Black people. All domains of racism were positively associated with depressive symptomology Thwarted belongingness behaved as a statistically significant moderator of the racism-depression relationship. In other words, participants who felt more social isolation and disconnection experienced more depression derived from their experiences with racism. Conclusions Sense of belonging is crucial to Black people, as lacking that support can contribute to worsen depression and racism. These results highlight the compounded burden of racism and social disconnection, especially in a sociopolitical climate marked by diminishing support for equity and inclusion.

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Redemptive Suffering and Sectarian Hostility: Shiʿi Islam as a Minority Faith

Ahab Bdaiwi

Identity and Vocation of Christian Minority Communities A Conversation with Religious Sources (eds. Edited By Bernhard J.G. Reitsma, Erika van Nes-Visscher)·2026

This contribution examines the historical and theological construction of minority identity in Shiʿi Islam within the broader Muslim world. It traces how political marginalization, sectarian polemics, and cultural memory, especially the martyrdom of

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Early Byzantine Apocalyptic Discourses

Ryan W. Strickler

2026

No abstract available

★ 4.0 (1)

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Prediction Market Accuracy: Crowd Wisdom or Informed Minority?

Roberto Gomez Cram, Yunhan Guo, Theis Ingerslev Jensen, Howard Kung

2026

Prediction markets are remarkably accurate, yet the source of this accuracy remains poorly understood. The conventional view attributes it to crowd wisdom, whereby prices aggregate information from a large and diverse pool of participants. We show instead that accuracy is driven by a small minority of informed traders. Using the universe of transactions from a large prediction market platform, we identify these traders and show that they, around 3% of all accounts, generate the bulk of price discovery. Their trades predict future prices and final outcomes, make prices more accurate throughout a market's lifespan, and react to news the moment it arrives. The remaining majority does not produce accuracy; rather, it funds it. Their trades generate most of the volume, but little of the information, and their losses flow as profits to the informed minority. Prediction market accuracy thus reflects the wisdom of an informed minority, not the wisdom of the crowd.

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ArchSem: Reusable Rigorous Semantics of Relaxed Architectures

THIBAUT PÉRAMI, THOMAS BAUEREISS, BRIAN CAMPBELL, ZONGYUAN LIU, NILS LAUERMANN, ALASDAIR ARMSTRONG, PETER SEWELL

2026

The specifications of mainstream processor architectures, such as Arm, x86, and RISC-V, underlie modern computing, as the targets of compilers, operating systems, and hypervisors. However, despite extensive research and tooling for instruction-set architecture (ISA) and relaxed-memory semantics, recently including systems features, there still do not exist integrated mathematical models that suffice for foundational formal verification, of concurrent architecture properties or of systems software. Previous proof-assistant work has had to substantially simplify the ISA semantics, the concurrency model, or both. We present ArchSem, an architecture-generic framework for architecture semantics, modularly combining ISA and concurrency models along a tractable interface of instruction-semantics effects, that covers a range of systems aspects. To do so, one has to handle many issues that were previously unclear, about the architectures themselves, the interface, the proper definition of reusable models, and the Rocq and Isabelle idioms required to make it usable. We instantiate it to the Arm-A and RISC-V instruction-set architectures and multiple concurrency models. We demonstrate usability for proof, despite the scale, by establishing that the Arm architecture (in a particular configuration) provides a provable virtual memory abstraction, with a combination of Rocq, Isabelle, and paper proof. Previous work provides further confirmation of usability: the AxSL program logic for Arm relaxed concurrency was proved sound above an earlier version of ArchSem. This establishes a basis for future proofs of architecture properties and systems software, above production architecture specifications.

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Experimental Realisation of Nut Graphs Using Coaxial Cable Networks

Maxine M. McCarthy, David M. Whittaker, Patrick W. Fowler, Barry T. Pickup

Match Communications in Mathematical and in Computer Chemistry·2026

A nut graph is a connected simple graph with nullity one that has a full kernel eigenvector. In the context of π systems, chemical nut graphs are identical with the subcubic nut graphs. Chemical nut graphs are of interest for at least two reasons: the possibility of fully distributed radical reactivity arising from partial occupation of their sole non-bonding orbital, and their identification with the class of strong omniconductors of nullity one in source-and-sink models of ballistic molecular conduction. In this note, a mapping between the H¨uckel tight-binding theory of π-conjugated carbon frameworks and the Telegraph equations for networks of coaxial cables is described. This mapping motivates experimental realisation of chemical nut graphs, where the radio-frequency resonances of the cable network correspond to the spectrum of a weighted version of the molecular graph. In particular, measurements with a vector network analyser give direct access to the nullstate of the cable network, and hence to a simulation of the non-bonding molecular orbital of the π system. We demonstrate the distributed nature of the kernel eigenvector, which underpins the description of chemical reactivity, omni-conduction and electrical properties, for the cable models of the smallest chemical nut graph, and the three smallest nut graphs. We also show the feasibility of larger cable networks obtainable by known constructions for infinite families of nut graphs

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Toward Better Temporal Structures for Geopolitical Events Forecasting

Kian Ahrabian, Eric Boxer, Jay Pujara

arXiv·2026

Forecasting on geopolitical temporal knowledge graphs (TKGs) through the lens of large language models (LLMs) has recently gained traction. While TKGs and their generalization, hyper-relational temporal knowledge graphs (HTKGs), offer a straightforward structure to represent simple temporal relationships, they lack the expressive power to convey complex facts efficiently. One of the critical limitations of HTKGs is a lack of support for more than two primary entities in temporal facts, which commonly occur in real-world events. To address this limitation, in this work, we study a generalization of HTKGs, Hyper-Relational Temporal Knowledge Generalized Hypergraphs (HTKGHs). We first derive a formalization for HTKGHs, demonstrating their backward compatibility while supporting two complex types of facts commonly found in geopolitical incidents. Then, utilizing this formalization, we introduce the htkgh-polecat dataset, built upon the global event database POLECAT. Finally, we benchmark and analyze popular LLMs on the relation prediction task, providing insights into their adaptability and capabilities in complex forecasting scenarios.

★ 2.0 (1)

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Ideological bias in the production of research findings

George J. Borjas, Nate Breznau

Science Advances·2026

When studying policy-relevant topics, researchers’ policy preferences may shape analytical decisions and results interpretations. Detecting this bias is challenging because the research process is not normally part of an observed experimental setting. Our study exploits an opportunity to observe 158 researchers working independently in 71 teams during an experiment. After being asked their position on immigration policy, they used the same data to answer the same empirical question: Does immigration affect public support for social welfare programs? The researchers estimated 1253 alternative regression models, and the estimated impacts ranged from strongly negative to strongly positive. We find that teams composed of pro-immigration researchers estimated more positive impacts of immigration on public support for social programs, while anti-immigration teams estimated more negative impacts. The differences arise because different teams adopted different model specifications. The underlying research design decisions are the mechanism through which ideology enters the process of producing parameter estimates.

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Oldest Papers

Disconnected and distressed: The moderating role of thwarted belongingness in the racism–depression link

Redemptive Suffering and Sectarian Hostility: Shiʿi Islam as a Minority Faith

Early Byzantine Apocalyptic Discourses

Prediction Market Accuracy: Crowd Wisdom or Informed Minority?

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ArchSem: Reusable Rigorous Semantics of Relaxed Architectures

Experimental Realisation of Nut Graphs Using Coaxial Cable Networks

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