Thuy Nguyen

Desde 1990, paralelamente à abrangente renovação do Vietnã, a vida religiosa no país passou por profundas transformações em termos de escala, formas de prática religiosa e relações com o Estado. Nesse contexto, a comunicação religiosa emergiu como uma parte importante dos assuntos religiosos, servindo como um mecanismo intermediário para a transmissão das políticas e leis religiosas do Partido Comunista do Vietnã e do Estado vietnamita às comunidades religiosas e ao clero, ao mesmo tempo em que reflete as necessidades, as aspirações e a dinâmica da vida religiosa no seio da sociedade. Este artigo analisa a comunicação religiosa no Vietnã de 1990 até o presente através de uma análise de dois casos representativos: o budismo e o catolicismo. Ao aplicar o referencial metodológico do materialismo dialético e do materialismo histórico, o artigo elucida a relação entre as condições religiosas, a política religiosa e as práticas de comunicação; avalia a situação atual, as conquistas e os desafios da comunicação religiosa conduzida sob a liderança do Partido Comunista do Vietnã; e propõe diversas implicações teóricas e práticas para melhorar a qualidade e a eficácia da comunicação religiosa no contexto da globalização e do rápido desenvolvimento das mídias digitais.

This study aims to determine whether political connections and foreign investments influence the level of Environmental, Social, and Governance (ESG) disclosure among listed firms. To empirically explore these relationships, we utilized a novel dataset of 111 listed manufacturing firms on the HOSE stock exchange in Vietnam, covering the period from 2015 to 2022. Content analysis was conducted to assess the levels of ESG disclosure, while ordered logit and random effect estimators, along with several robustness checks, were applied to quantify the impacts of political connections and foreign investments. Our findings reveal that foreign connections are positively correlated with higher levels of ESG disclosure, whereas politically connected firms are associated with negative impacts and lower levels of ESG disclosure compared to those with foreign connections. These results address the research questions effectively and contribute to the literature by offering an updated view of current ESG practices in Vietnam, an emerging economy with evolving ESG norms. The findings provide both theoretical and practical contributions to the understanding of ESG disclosure, with important implications for policy-makers and business leaders.

Artificial Intelligence (AI) powered machines are increasingly mediating our work and many of our managerial, economic, and cultural interactions. While technology enhances individual capability in many ways, how do we know that the sociotechnical system as a whole, consisting of a complex web of hundreds of human–machine interactions, is exhibiting collective intelligence? Research on human–machine interactions has been conducted within different disciplinary silos, resulting in social science models that underestimate technology and vice versa. Bringing together these different perspectives and methods at this juncture is critical. To truly advance our understanding of this important and quickly evolving area, we need vehicles to help research connect across disciplinary boundaries.This paper advocates for establishing an interdisciplinary research domain—Collective Human-Machine Intelligence (COHUMAIN). It outlines a research agenda for a holistic approach to designing and developing the dynamics of sociotechnical systems. In illustrating the kind of approach, we envision in this domain, we describe recent work on a sociocognitive architecture, the transactive systems model of collective intelligence, that articulates the critical processes underlying the emergence and maintenance of collective intelligence and extend it to human–AI systems. We connect this with synergistic work on a compatible cognitive architecture, instance-based learning theory and apply it to the design of AI agents that collaborate with humans. We present this work as a call to researchers working on related questions to not only engage with our proposal but also develop their own sociocognitive architectures and unlock the real potential of human–machine intelligence.

Circular economy (CE), a sustainability concept that promotes resource efficiency and waste re-duction, has garnered significant popularity in recent years due to its potential to address pressing environmental and economic challenges. This study develops the Bayesian Mindsponge Mindspongeconomics (BMM) framework/analytic method based on Bayesian Mindsponge framework (BMF) to the factors influencing young adults' pro-environmental behavior and purchases of green products at different price levels. The findings indicate that young adults who are knowledgeable about CE and value environmental protection and energy conservation are more likely to engage in waste sorting, while the factors that affect their willingness to pay (WTP) more for green and en-ergy-saving products vary at different price tiers. The study demonstrates that CE knowledge, daily waste sorting habits, and environmental concern positively impact young adults' WTP for products that are 5%, 10%, and 15% higher-priced, respectively. Besides, the study also highlights the po-tential of educational programs and cultural influences in nurturing a generation that prioritizes environmental value. The research integrates multidisciplinary perspectives and offers practical implications for policymakers, educators, and businesses seeking to promote green literacy and foster an environmental culture among the youth, contributing to the broader goals of green transformation and sustainable development associated with CE and green economy, especially in urban areas of emerging countries and beyond.

A major challenge for research in artificial intelligence is to develop systems that can infer the goals, beliefs, and intentions of others (i.e., systems that have theory of mind, ToM). In this research, we propose a cognitive ToM framework that uses a well-known theory of decisions from experience to construct a computational representation of ToM. Instance-based learning theory (IBLT) is used to construct a cognitive model that generates ToM from the observation of other agents' behavior. The IBL model of the observer distinguishes itself from previous models of ToM that make unreasonable assumptions about human cognition, are hand-crafted for particular settings, complex, or unable to explain a cognitive development of ToM compared to human's ToM. The IBL model learns from the observation of goal-directed agents' behavior in a gridworld navigation task, and it infers and predicts the behaviors of the agents in new gridworlds across different degrees of decision complexity in similar ways to the way human observers do. We provide evidence for the alignment of the IBL observer's predictions under various levels of decision complexity. We also advance the demonstration of the IBL predictions using a classic test of false beliefs (the Sally–Anne test), which is commonly used to test ToM in humans. We discuss our results and the potential of the IBL observer model to improve human–machine interactions.

We investigate a system of two species exploiting a common resource. We consider both abiotic (i.e. with a constant resource supply rate) and biotic (i.e. with resource reproduction and self-limitation) resources. We are interested in the asymmetric competition where a given consumer is the locally superior resource exploiter (LSE) and the other is the locally inferior resource exploiter (LIE). They also interact directly via interference competition in the sense that LIE individuals can use two opposite strategies to compete with LSE individuals: we assume, in the first case, that LIE uses an avoiding strategy, i.e. LIE individuals go to a non-competition patch to avoids competition with LSE individuals, and in the second one, LIE uses an aggressive strategy, i.e. being very aggressive so that LSE individuals have to go to a non-competition patch. We further assume that there is no resource in the non-competition patch so that individuals have to come back to the competition patch for their maintenance, and the migration process acts on a fast time scale in comparison with demography and competition processes. The models show that being aggressive is efficient for LIE’s survival and even provoke global extinction of the LSE and this result does not depend on the nature of resource.

We present a mathematical model of two competing marine species that are harvested. We consider three models according to different levels of complexity, without and with species refuge and density-independent and density-dependent species movement between fishing area and refuge. We particularly study the effects of the fishing pressure on the outcome of the competition. We focus on conditions that allow an inferior competitor to invade as a result of fishing pressure. The model is discussed in relationship to the case of the thiof and the octopus along the Atlantic West African coast. At the origin, the thiof was abundant and the octopus scarce in that region. Since, the fishing pressure has strongly increased in some fishing areas leading to the depletion of the thiof and the invasion of its competitor, the octopus.