Authors:louise.dupuis@dauphine.eu (Louise Dupuis de Tarlé; Matteo Michelini, AnneMarie Borg, Gabriella Pigozzi, Juliette Rouchier, Dunja Šešelja Christian Straßer Abstract: Louise Dupuis de Tarlé, Matteo Michelini, AnneMarie Borg, Gabriella Pigozzi, Juliette Rouchier, Dunja Šešelja and Christian Straßer: In this paper, we present an agent-based model for studying the impact of 'myside bias' on the argumentative dynamics in scientific communities. Recent insights in cognitive science suggest that scientific reasoning is influenced by `myside bias'. This bias manifests as a tendency to prioritize the search and generation of arguments that support one's views rather than arguments that undermine them. Additionally, individuals tend to apply more critical scrutiny to opposing stances than to their own. Although myside bias may pull individual scientists away from the truth, its effects on communities of reasoners remain unclear. The aim of our model is two-fold: first, to study the argumentative dynamics generated by myside bias, and second, to explore which mechanisms may act as a mitigating factor against its pernicious effects. Our results indicate that biased communities are epistemically less successful than non-biased ones, and that they also tend to be less polarized than non-biased ones. Moreover, we find that two socio-epistemic mechanisms help communities to mitigate the effect of the bias: the presence of a common filter on weak arguments, which can be interpreted as shared beliefs, and an equal distribution of agents for each alternative at the beginning. PubDate: Sat, 29 Jun 2024 12:59:00 +010
Authors:erezh51@gmail.com (Erez Hatna; Jeewoen Shin, Katelynn Devinney, Julia Latash, Vasudha Reddy, Beth Nivin, Alyssa Masor Sharon K. Greene Abstract: Erez Hatna, Jeewoen Shin, Katelynn Devinney, Julia Latash, Vasudha Reddy, Beth Nivin, Alyssa Masor and Sharon K. Greene: Large outbreaks of Shigella sonnei among children in Haredi Jewish (ultra-Orthodox) communities in Brooklyn, New York have occurred every 3–5 years since at least the mid-1980s. These outbreaks are partially attributable to large numbers of young children in these communities, with transmission highest in child care and school settings, and secondary transmission within households. As these outbreaks have been prolonged and difficult to control, we developed an agent-based model of shigellosis transmission among children in these communities to support New York City Department of Health and Mental Hygiene staff. Simulated children were assigned an initial susceptible, infectious, or recovered (immune) status and interacted and moved between their home, child care program or school, and a community site. We calibrated the model according to observed case counts as reported to the Health Department. Our goal was to better understand the efficacy of existing interventions and whether limited outreach resources could be focused more effectively. We evaluated how well disseminating hand washing education in child care programs can reduce the number of infected children. The model indicated that intervention efficacy may be as high as 24% when all intervention parameters are at optimal values but only approximately 7% for a more realistic, less stringent scenario. We ranked intervention parameters according to their permutation importance using a random-forest regression analysis. The most important parameter was the minimum number of reported cases in a child care program that triggers a visit to disseminate hand washing education, followed by the use of non-antibacterial soap in hand washing education, the number of additional visits to child care programs, and the probability of successfully obtaining information on child care program attendance via patient interview. Additional strategies should be considered, such as working with community partners to assist with hand hygiene education at facilities during an outbreak. PubDate: Sat, 29 Jun 2024 12:58:00 +010
Authors:deborah.manzi@unicatt.it (Deborah Manzi; Francesco Calderoni Abstract: Deborah Manzi and Francesco Calderoni: The resilience and resistance of criminal networks, particularly drug trafficking organizations, remain crucial issues in contemporary society. Existing studies have unrealistically modelled law enforcement interventions and fail to capture the complexity of the adaptations of criminal networks. This study introduces MADTOR, the first agent-based model that examines the responses of drug trafficking organizations to different types of law enforcement interventions. MADTOR addresses previous research gaps by enabling more realistic simulations of law enforcement interventions, modeling adaptations by organizations based on real-world operations, and allowing comparisons of different interventions. To demonstrate the possible applications of MADTOR, we assess the impact of arresting varying proportions of members on the resilience of drug trafficking organizations. Our results reveal the disruptive impact of arresting even a few members, and a non-linear relationship between the share of arrested members and disruptive impact, with diminishing returns as the proportion increases. Surviving organizations face increasing recovery difficulties as more members are arrested. These findings contribute to the development of strategies for effective interventions against drug trafficking. PubDate: Sat, 29 Jun 2024 12:57:00 +010
Authors:cheickameddiloma.traore@ucad.edu.sn (Cheick Amed Diloma Gabriel Traoré; Etienne Delay, Djibril Diop Alassane Bah Abstract: Cheick Amed Diloma Gabriel Traoré, Etienne Delay, Djibril Diop and Alassane Bah: Sahelian transhumance is a type of socio-economic and environmental pastoral mobility. It involves the movement of herds from their terroir of origin (i.e., their original pastures) to one or more host terroir, followed by a return to the terroir of origin. According to certain pastoralists, the mobility of herds is planned to prevent environmental degradation, given the continuous dependence of these herds on their environment. However, these herds emit Greenhouse Gases (GHGs) in the areas they cross. Given that GHGs contribute to global warming, our long-term objective is to quantify the GHGs emitted by Sahelian herds. The determination of these herds' GHG emissions requires: (1) the artificial replication of the transhumance, and (2) precise knowledge of the space used during their transhumance. This article presents the design of an artificial replication of this transhumance through an agent-based model called MSTRANS. MSTRANS determines the space used by transhumant herds, based on the decision-making process of Sahelian transhumants. MSTRANS integrates a constrained multi-objective optimization problem and algorithms into an agent-based model. The constrained multi-objective optimization problem encapsulates the rationality and adaptability of pastoral strategies. Interactions between transhumants and their socio-economic network are modelled using algorithms and diffusion processes within the multi-objective optimization problem. The dynamics of pastoral resources are formalized at various spatio-temporal scales using equations that are integrated into the algorithms. The results of MSTRANS have been validated using GPS data collected from transhumant herds in Senegal. The MSTRANS results highlight the relevance of integrated models and constrained multi-objective optimization for modelling and monitoring the movement of transhumant herds in the Sahel. We can state that specialists in calculating greenhouse gas emissions now have a reproducible and reusable tool for determining the space occupied by transhumant herds in a Sahelian country. In addition, decision-makers, pastoralists, veterinarians and traders have a reproducible and reusable tool to help them make environmental and socio-economic decisions. PubDate: Sat, 29 Jun 2024 12:56:00 +010
Authors:yang@kaist.ac.kr (Minyoung Choi; Jae-Suk Yang Abstract: Minyoung Choi and Jae-Suk Yang: Organizational silos pose a common challenge for many companies, as they create barriers to communication, coordination, and resource efficiency. Addressing these challenges necessitates successful negotiation, yet the realm of multi-level team negotiation remains understudied. This research employs a computational simulation model to explore the dynamics of two-level negotiation, encompassing interactions of individuals searching for an agreement within and between teams in the organization. Our model involves individuals and teams with conflicting opinions on mutual interest issues. Within the intra-team negotiation process, the model integrates loyalty-driven opinion adjustments and the influence of the collective opinions of team members on team decisions. Concurrently, the inter-team negotiation introduces parameters reflecting teams’ willingness to negotiate with each other, emphasizing their openness to opinion adjustments. Our findings highlight the importance of individual loyalty, the leader acceptance ratio, and team willingness to negotiate as pivotal factors for achieving successful negotiation. We shed light on the mechanisms involved in two-level negotiations, including both within a team and between teams. This contribution enriches the literature on organizational negotiation and team dynamics in the context of organizational conflict. Moreover, this study advances the field by developing a computational simulation model, laying the groundwork for future studies exploring the multi-level negotiation processes. The insights in this study can equip managers with strategies to foster a win-win mindset for improved team coordination. PubDate: Sat, 29 Jun 2024 12:55:00 +010
Open Access journal
