There is growing concern about the impact of declining political trust on democracies. Psychological research has introduced the concept of epistemic (mis)trust as a stable disposition acquired through development, which may influence our sociopolitical engagement. Given trust’s prominence in current politics, we examined the relationship between epistemic trust and people’s choices of (un)trustworthy political leaders. In two representative samples in the UK and US (N = 1096), we tested whether epistemic trust predicts political leader choices through three political dimensions: dogmatism, political trust, and ideology. Although epistemic trust did not directly predict choices of political leaders, it predicted dogmatism and political ideology, which in turn predicted choices of political leaders. A network analysis revealed that epistemic trust and political dimensions only interact through their common connection with dogmatism. These findings suggest that cognitive and affective development may underlie an individual’s political ideology and associated beliefs.

Aircraft ground taxiing contributes significantly to carbon emissions and engine wear. The electric towing tractor (ETT) addresses these issues by towing the aircraft to the runway end, thereby minimising ground taxiing. As the complexity of ETT towing operations increases, both the towing distance and time increase significantly, and the original method for estimating the number of ETTs is no longer applicable. Due to the substantial acquisition cost of ETT and the need to reduce waste while ensuring operational efficiency, this paper introduces for the first time an ETT quantity estimation model that combines simulation and vehicle scheduling models. The simulation model simulates the impact of ETT on apron operations, taxiing on taxiways and takeoffs and landings on runways. Key timing points for ETT usage by each aircraft are identified through simulation, forming the basis for determining the minimum number of vehicles required for airport operations using a hard-time window vehicle scheduling model. To ensure the validity of the model, simulation model verification is conducted. Furthermore, the study explores the influence of vehicle speed and airport scale on the required number of ETTs. The results demonstrate the effective representation of real-airport operations by the simulation model. ETT speed, airport runway and taxiway configurations, takeoff and landing frequencies and imbalances during peak periods all impact the required quantity of ETTs. A comprehensive approach considering these factors is necessary to determine the optimal number of ETTs.

Every complex organization is sometimes marked by preference heterogeneity, disagreement, and conflict. Within political parties, such frictions are traditionally viewed negatively, while recent research has started to perceive them more positively. How might such contradictory evaluations be explained? Through a three-step conceptual analysis we (1) identify two analytical perspectives on intraparty friction, one rooted in a primarily structural conception of parties, one in a primarily behavioral conception; and (2) specify a minimal definition of intraparty friction, which underpins a hierarchical concept structure to (3) suggest a way to resolve contradictions in the consequences attributed to intraparty frictions. Structuralist accounts often view frictions as negative due to a more demanding conceptual threshold, suggesting different types and levels of risk taking by conflict partners. Conversely, behavioralist perspectives see friction more often as beneficial because they focus on expressed disagreement without necessitating an organizational response. Our conceptual tools have important implications for research on membership organizations generally.

What challenges do researchers encounter in authentically engaging with the field site and academia when certain aspects of their true identities diverge from the established norms within those domains? Using the case of female political scientists who conduct research on gender politics in the Middle East and North Africa, I highlight the ethical, logistical, and epistemological challenges of carrying out research in a politically and socially closed context. Few studies have investigated how the research process and the knowledge it produces are affected by the intertwinement of authoritarianism and patriarchy, and by the researcher’s positionality within this context. This study fills this gap by drawing upon interviews with feminist political scientists who were born and raised in the region but are based in Western academic institutions to examine the impact of authoritarianism, patriarchy, and the researchers’ insider/outsider positionality on the research process. The analysis shows three key findings. First, researching gender politics is a contentious topic that places researchers on the radar of the state. For scholars who are originally from the region, the issue is compounded by the fact that they are sometimes viewed as traitors by the regime in their country of origin, which accuses them of tarnishing the image of the government and scrutinizing its gender policies. Second, within the wider society, the politics of representation also impose certain limitations and expectations on female scholars. Such limitations include gendered restrictions on their access and mobility in the field. Finally, feminist researchers share how the knowledge they produce, which centers social justice demands, is not always valued in the discipline of political science. The article contributes to this discipline by expanding our understanding of the interplay between identity politics, fieldwork practices, and knowledge production in complex political and social settings.

Why did Vladimir Putin order the invasion of Ukraine in February 2022, despite numerous warnings from Western countries about the consequences of such an action? This article argues that misperceptions about having the upper hand vis-à-vis Western countries, formed and proliferated among the Russian leadership, emboldened the Kremlin to launch the military invasion of Ukraine, assuming that the West would stand down in the face of the attack. Based on a detailed analysis of Russian elites’ discourse through the theoretical lens of interdependence studies, this study demonstrates that Putin miscalculated Western resolve largely because of two key misperceptions. First, Putin’s elites were convinced that the West was asymmetrically dependent on Russia, viewing it as a strategic resource that would tie the hands of Western and EU countries, eventually making them accept the outcome of the war. Second, the Kremlin believed that Ukraine occupied a secondary role in Western interests that would further limit the West’s involvement in the conflict, as it would not risk exposing its dependence on Moscow for the sake of an issue that, in the Kremlin’s eyes, was marginal to European and American security.

This work introduces a novel compact ultra-wideband (UWB) antenna designed for wearable applications, employing a bioinspired structure and machine learning (ML) techniques to achieve exceptional performance in the 3.10–10.42 GHz range. The antenna is fabricated by positioning conductive fabric on a polydimethylsiloxane polymer of 1 mm thickness to augment high flexibility and durability. Additionally, it pioneers integrating a complete ground plane to mitigate back radiation toward the human body, presenting a compact (35.5 × 30.5 × 1 mm3) UWB antenna design compliant with IEEE 802.15.6 standards. The design methodology includes using bandwidth enhancement techniques such as chamfering edges, slots, and adding stubs in the feed, along with applying ML to optimize the antenna’s dimensions for desired return loss characteristics. The proposed antenna demonstrates exceptional resilience to human body loading and physical deformation. The simulation and measurement results have good agreement. The K-nearest neighbour method beat the other ML algorithms maximum accuracy of 99.62% to predict the S11. According to the author’s best knowledge, this is the first compact UWB antenna with full ground specified by IEEE.802.15.6 with ML reported.

Regularization can improve statistical estimates made with highly correlated data. However, any regularization procedure embeds assumptions about the data generating process that can have counterintuitive consequences when those assumptions are untenable. We show that rather than simply shrinking estimates, regularization can reopen backdoor causal paths, inflating the estimates of some effects, and in the wrong circumstances, even reversing their direction. Recently, Cavari and Freedman (2023), argued that declining cooperation rates in surveys have inflated measures of mass polarization. We show that this finding is driven by large penalty terms in their regularized regressions, which leads to the estimates being confounded with time. Alternative methods do not show a clear positive or negative effect of declining cooperation on estimated levels of mass polarization.

Based on correlational and factorial analysis of data collected from 384 middle and high school students in South Korea, Al–Hoorie et al. (2024) claimed the existence of a discriminant validity crisis within the L2 motivational self-system research tradition and advocated for abandoning research in this area. In this response, we critically examined the evidence presented, re-analyzed their data, and argued that their findings actually support the discriminant validity of the target scales. We also discussed issues related to the design and implementation of their study and refuted their assertion regarding a discriminant validity crisis in this field. Finally, we emphasized the necessity of prioritizing definitional validity in the ongoing methodological reforms of L2 motivation research.