Month: April 2024

Strategic attitude expressions as identity performance and identity creation in interaction

Latest Results

Abstract

We assess the strategic alignment of attitudes and the active construction of attitude-based identity across two studies. Study one assessed the twitter response (hashtags in English) to the war in Ukraine for five months after Russia’s first invasion of Ukraine 2022 (N = 8149). Results demonstrated that individuals publicly expressed hashtags similar to others close to them in the followership network, showing their support for Ukraine and condemnation of the Russian invasion in qualitatively different ways. Study two was a preregistered Prolific experiment with geographical European participants ran in September, 2022 (N = 1368). Results demonstrated that attitude interaction with ingroup members motivated interactants towards attitude alignment, and attitude alignment strengthened the identification that motivated the alignment in the first place. Results suggest that attitude expression is performative and constrained by one’s group relationship with one’s audience and the definition of social identity can be constrained by opinion-based identity performance.

A shift towards oration: teaching philosophy in the age of large language models

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Abstract

This paper proposes a reevaluation of assessment methods in philosophy higher education, advocating for a shift away from traditional written assessments towards oral evaluation. Drawing attention to the rising ethical concerns surrounding large language models (LLMs), we argue that a renewed focus on oral skills within philosophical pedagogy is both imperative and underexplored. This paper offers a case for redirecting attention to the neglected realm of oral evaluation, asserting that it holds significant promise for fostering students with some of our traditional academic values that we want to maintain. We identify implications of this shift in emphasis which situates our discipline to contribute positively to solving some of the most pressing socio-political issues. Additionally, our proposal aims to demonstrate how philosophy can solidify its relevancy to the twenty-first century student and academy more broadly.

Public support for withdrawal from international organizations: Experimental evidence from the US

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Abstract

The United States has helped create and lead many international organizations (IOs). Yet in the last six years, the US announced its withdrawal from several IOs including the World Health Organization, UNESCO, and the Universal Postal Union. Do Americans care about US withdrawals from IOs? When do Americans support withdrawing from IOs and support candidates who propose this? We argue that Americans’ support for multilateralism tends to divide along party lines, and that IO withdrawal can activate those preferences. We also argue that framing an IO withdrawal as benefiting US national interests can make Americans more likely to favor IO exit. Data from four US survey experiments during the 2016–2020 Trump administration support these arguments. Democrats tend to oppose IO withdrawals while Republicans tend to support them. Further, results show that IO withdrawal (and how it is framed) affects candidate choice and policy support. This suggests that announcing IO withdrawal can be used to rally domestic electoral support. Still, the data also show that a large proportion of the US public values remaining in IOs, even when IOs are imperfect or challenging. In these cases, we note that sunk cost fallacies, status quo bias, and loss aversion may pose friction points for supporting withdrawal. Our findings have important implications for research on public opinion about international cooperation, backlash against IOs, and their life cycles.

An integrated modeling approach for estimating monthly global rainfall erosivity

Latest Results

Abstract

Modeling monthly rainfall erosivity is vital to the optimization of measures to control soil erosion. Rain gauge data combined with satellite observations can aid in enhancing rainfall erosivity estimations. Here, we presented a framework which utilized Geographically Weighted Regression approach to model global monthly rainfall erosivity. The framework integrates long-term (2001–2020) mean annual rainfall erosivity estimates from IMERG (Global Precipitation Measurement (GPM) mission’s Integrated Multi-satellitE Retrievals for GPM) with station data from GloREDa (Global Rainfall Erosivity Database, n = 3,286 stations). The merged mean annual rainfall erosivity was disaggregated into mean monthly values based on monthly rainfall erosivity fractions derived from the original IMERG data. Global mean monthly rainfall erosivity was distinctly seasonal; erosivity peaked at ~ 200 MJ mm ha−1 h−1 month−1 in June–August over the Northern Hemisphere and ~ 700 MJ mm ha−1 h−1 month−1 in December–February over the Southern Hemisphere, contributing to over 60% of the annual rainfall erosivity over large areas in each hemisphere. Rainfall erosivity was ~ 4 times higher during the most erosive months than the least erosive months (December–February and June–August in the Northern and Southern Hemisphere, respectively). The latitudinal distributions of monthly and seasonal rainfall erosivity were highly heterogeneous, with the tropics showing the greatest erosivity. The intra-annual variability of monthly rainfall erosivity was particularly high within 10–30° latitude in both hemispheres. The monthly rainfall erosivity maps can be used for improving spatiotemporal modeling of soil erosion and planning of soil conservation measures.

An integrated modeling approach for estimating monthly global rainfall erosivity

Latest Results

Abstract

Modeling monthly rainfall erosivity is vital to the optimization of measures to control soil erosion. Rain gauge data combined with satellite observations can aid in enhancing rainfall erosivity estimations. Here, we presented a framework which utilized Geographically Weighted Regression approach to model global monthly rainfall erosivity. The framework integrates long-term (2001–2020) mean annual rainfall erosivity estimates from IMERG (Global Precipitation Measurement (GPM) mission’s Integrated Multi-satellitE Retrievals for GPM) with station data from GloREDa (Global Rainfall Erosivity Database, n = 3,286 stations). The merged mean annual rainfall erosivity was disaggregated into mean monthly values based on monthly rainfall erosivity fractions derived from the original IMERG data. Global mean monthly rainfall erosivity was distinctly seasonal; erosivity peaked at ~ 200 MJ mm ha−1 h−1 month−1 in June–August over the Northern Hemisphere and ~ 700 MJ mm ha−1 h−1 month−1 in December–February over the Southern Hemisphere, contributing to over 60% of the annual rainfall erosivity over large areas in each hemisphere. Rainfall erosivity was ~ 4 times higher during the most erosive months than the least erosive months (December–February and June–August in the Northern and Southern Hemisphere, respectively). The latitudinal distributions of monthly and seasonal rainfall erosivity were highly heterogeneous, with the tropics showing the greatest erosivity. The intra-annual variability of monthly rainfall erosivity was particularly high within 10–30° latitude in both hemispheres. The monthly rainfall erosivity maps can be used for improving spatiotemporal modeling of soil erosion and planning of soil conservation measures.

Finite-element modeling for static bending and free vibration analyses of double-layer non-uniform thickness FG plates taking into account sliding interactions

Latest Results

Abstract

The present article explores static bending and natural oscillation characteristics of double-layer non-uniform thickness functionally graded (FG) plates that are equipped with shear connectors. The fundamental equations are comprehensively described and developed by the utilization of the finite-element method (FEM), in conjunction with the widely recognized and straightforward first-order shear deformation plate theory (FSDT). The current hypothesis and computational framework have been validated through a comparative analysis of the numerical findings from this study with those reported in other esteemed publications. Parametric research is undertaken to explore the impact of geometrical and physical features on the structural response of the FG plate, with particular emphasis on the variation in thickness and distribution of shear connectors. The numerical findings obtained from this study can serve as a valuable point of reference for further orientation endeavors in the same domain. Furthermore, the proposed complex structural model can be referred to as an important idea for application in the fields of aerospace, nuclear, and military technology.

Finite-element modeling for static bending and free vibration analyses of double-layer non-uniform thickness FG plates taking into account sliding interactions

Latest Results

Abstract

The present article explores static bending and natural oscillation characteristics of double-layer non-uniform thickness functionally graded (FG) plates that are equipped with shear connectors. The fundamental equations are comprehensively described and developed by the utilization of the finite-element method (FEM), in conjunction with the widely recognized and straightforward first-order shear deformation plate theory (FSDT). The current hypothesis and computational framework have been validated through a comparative analysis of the numerical findings from this study with those reported in other esteemed publications. Parametric research is undertaken to explore the impact of geometrical and physical features on the structural response of the FG plate, with particular emphasis on the variation in thickness and distribution of shear connectors. The numerical findings obtained from this study can serve as a valuable point of reference for further orientation endeavors in the same domain. Furthermore, the proposed complex structural model can be referred to as an important idea for application in the fields of aerospace, nuclear, and military technology.

Boosting the intra-African digital trade in the AfCFTA context: does regulatory framework matter?

Latest Results

Abstract

Digital trade is one of the promising areas for the African Continental Free Trade Area (AfCFTA) and a factor of success of the African Union Digital Transformation Strategy (DTS) for Africa (2020–2030). However, the benefits of digital trade are not automatic and require an adequate regulatory environment. The objective of this study is to show how an adequate regulatory framework can boost the intra-African digital trade in the AfCFTA context. Our descriptive analysis shows that digital trade has increased across all regions in the world particularly in Africa since the beginning of the covid-19 pandemic. As a share of digitally deliverable services in total export services, digital trade represents 35% of total export services in Africa. Digital trade expansion faces regulatory barriers and the lack of a harmonized regulatory framework. Our econometrics results shows that digital trade and digital trade regulatory barriers (RDTII) are strongly negatively correlated in Africa. This result establishes the need to improve digital trade regulations framework in Africa.

Boosting the intra-African digital trade in the AfCFTA context: does regulatory framework matter?

Latest Results

Abstract

Digital trade is one of the promising areas for the African Continental Free Trade Area (AfCFTA) and a factor of success of the African Union Digital Transformation Strategy (DTS) for Africa (2020–2030). However, the benefits of digital trade are not automatic and require an adequate regulatory environment. The objective of this study is to show how an adequate regulatory framework can boost the intra-African digital trade in the AfCFTA context. Our descriptive analysis shows that digital trade has increased across all regions in the world particularly in Africa since the beginning of the covid-19 pandemic. As a share of digitally deliverable services in total export services, digital trade represents 35% of total export services in Africa. Digital trade expansion faces regulatory barriers and the lack of a harmonized regulatory framework. Our econometrics results shows that digital trade and digital trade regulatory barriers (RDTII) are strongly negatively correlated in Africa. This result establishes the need to improve digital trade regulations framework in Africa.

Community detection in directed weighted networks using Voronoi partitioning

Latest Results

Abstract

Community detection is a ubiquitous problem in applied network analysis, however efficient techniques do not yet exist for all types of network data. Directed and weighted networks are an example, where the different information encoded by link weights and the possibly high graph density can cause difficulties for some approaches. Here we present an algorithm based on Voronoi partitioning generalized to deal with directed weighted networks. As an added benefit, this method can directly employ edge weights that represent lengths, in contrast to algorithms that operate with connection strengths, requiring ad-hoc transformations of length data. We demonstrate the method on inter-areal brain connectivity, air transportation networks, and several social networks. We compare the performance with several other well-known algorithms, applying them on a set of randomly generated benchmark networks. The algorithm can handle dense graphs where weights are the main factor determining communities. The hierarchical structure of networks can also be detected, as shown for the brain. Its time efficiency is comparable or even outperforms some of the state-of-the-art algorithms, the part with the highest time-complexity being Dijkstra’s shortest paths algorithm ( \({\mathcal {O}}(|E| + |V|\log |V|)\) ).