Hasil untuk "Philosophy. Psychology. Religion"

Yicheng Di, Yuan Liu, Zhi Chen et al.

Sequential recommender infers users' evolving psychological motivations from historical interactions to recommend the next preferred items. Most existing methods compress recent behaviors into a single vector and optimize it toward a single observed target item, but lack explicit modeling of psychological motivation shift. As a result, they struggle to uncover the distributional patterns across different shift degrees and to capture collaborative knowledge that is sensitive to psychological motivation shift. We propose a general framework, the Sequential Recommender System Based on User Psychological Motivation, to enhance sequential recommenders with psychological motivation shift-aware user modeling. Specifically, the Psychological Motivation Shift Assessment quantitatively measures psychological motivation shift; guided by PMSA, the Shift Information Construction models dynamically evolving multi-level shift states, and the Psychological Motivation Shift-driven Information Decomposition decomposes and regularizes representations across shift levels. Moreover, the Psychological Motivation Shift Information Matching strengthens collaborative patterns related to psychological motivation shift to learn more discriminative user representations. Extensive experiments on three public benchmarks show that SRSUPM consistently outperforms representative baselines on diverse sequential recommender tasks.

Antonis Antoniou

In the 1960s and 1970s a series of observations and theoretical developments highlighted the presence of several anomalies which could, in principle, be explained by postulating one of the following two working hypotheses: (i) the existence of dark matter, or (ii) the modification of standard gravitational dynamics in low accelerations. In the years that followed, the dark matter hypothesis as an explanation for dark matter phenomenology attracted far more attention compared to the hypothesis of modified gravity, and the latter is largely regarded today as a non-viable alternative. The present article takes an integrated history and philosophy of science approach in order to identify the reasons why the scientific community mainly pursued the dark matter hypothesis in the years that followed, as opposed to modified gravity. A plausible answer is given in terms of three epistemic criteria for the pursuitworthiness of a hypothesis: (a) its problem-solving potential, (b) its compatibility with established theories and the feasibility of incorporation, and (c) its independent testability. A further comparison between the problem of dark matter and the problem of dark energy is also presented, explaining why in the latter case the situation is different, and modified gravity is still considered a viable possibility.

Junzhe Wang, Bichen Wang, Xing Fu et al.

In recent years, Large Language Models (LLMs) have made significant progress in automated psychological counseling. However, current research focuses on single-session counseling, which doesn't represent real-world scenarios. In practice, psychological counseling is a process, not a one-time event, requiring sustained, multi-session engagement to progressively address clients' issues. To overcome this limitation, we introduce a dataset for Multi-Session Psychological Counseling Conversation Dataset (MusPsy-Dataset). Our MusPsy-Dataset is constructed using real client profiles from publicly available psychological case reports. It captures the dynamic arc of counseling, encompassing multiple progressive counseling conversations from the same client across different sessions. Leveraging our dataset, we also developed our MusPsy-Model, which aims to track client progress and adapt its counseling direction over time. Experiments show that our model performs better than baseline models across multiple sessions.

Kateřina Hlaváčková-Schindler, Rainer Wöß, Vera Pecorino et al.

Not much has been written about the role of triggers in the literature on causal reasoning, causal modeling, or philosophy. In this paper, we focus on describing triggers and causes in the metaphysical sense and on characterizations that differentiate them from each other. We carry out a philosophical analysis of these differences. From this, we formulate a definition that clearly differentiates triggers from causes and can be used for causal reasoning in natural sciences. We propose a mathematical model and the Cause-Trigger algorithm, which, based on given data to observable processes, is able to determine whether a process is a cause or a trigger of an effect. The possibility to distinguish triggers from causes directly from data makes the algorithm a useful tool in natural sciences using observational data, but also for real-world scenarios. For example, knowing the processes that trigger causes of a tropical storm could give politicians time to develop actions such as evacuation the population. Similarly, knowing the triggers of processes that cause global warming could help politicians focus on effective actions. We demonstrate our algorithm on the climatological data of two recent cyclones, Freddy and Zazu. The Cause-Trigger algorithm detects processes that trigger high wind speed in both storms during their cyclogenesis. The findings obtained agree with expert knowledge.

Shoaib Ahmed Malik

This article explores Fakhr al-Dīn al-Rāzī’s (d. 1210) theological insights on the metaphysical hierarchy of creation to address the question: Can there be extraterrestrial intelligence (ETI) superior to human intelligence? By revisiting a long-standing debate in the Islamic tradition concerning the superiority (afḍaliyyah) of angels versus humans, this article positions al-Rāzī as a pivotal case who diverges from the majority Ashʿarī stance by advocating for angelic superiority. Through a detailed analysis of al-Rāzī’s deconstruction of pro-human superiority arguments and his construction of arguments favoring angels, the article demonstrates how his framework challenges anthropocentric assumptions and broadens theological possibilities. If al-Rāzī’s arguments are deemed successful, his scripturally and rationally grounded framework provides a foundation for envisioning ETI that may surpass humanity in spiritual or intellectual rank. This article contributes uniquely by unveiling al-Rāzī’s underexplored ideas on angelic superiority and integrating them into the context of Islam and ETI, thereby advancing modern discourse on Islamic theological anthropology.

Fiona Preston-Whyte , Toshka Barnardo , Danica Marlin et al.

Data gaps limit solutions and policy development for environmental issues. Citizen science offers a possible solution to reduce data gaps at a limited cost while enhancing environmental education (EE). While highly effective in the latter, citizen science campaigns rarely produce reliable, comparable, and meaningful data. This often results from fragmented awareness, varying data collection methods, and little training prior to data collection. This article explores how Massive Open Online Courses (MOOCs) can be used to train citizen scientists, increase the value of citizen science data, and ensure that resources invested in citizen science initiatives are used more efficiently. We use a beach macrolitter monitoring course developed by Sustainable Seas Trust (SST) (NGO/NPO) and GRID-Arendal (a research foundation) as a case study in Africa, since the marine litter issue has widespread public support, and beaches are pleasant locations that attract potential citizen scientists. Beach macrolitter surveys utilise everyday equipment, and monitoring methods are simple if individuals are supported with appropriate training. This is especially relevant in Africa, where plastic pollution is forecasted to increase faster than other regions, and resources for research can be limited. This article gives a modified problemsolution model (mPSM) perspective, considering the challenges and solutions of MOOC development by two organisations working in the same space with limited resources. Challenges to inclusivity for online training in Africa included language barriers and limited technological access. Using Africa as a case study, we show that by combining professional abilities, inclusive digital education can be achieved using data-light MOOCs, offline engagement and other inclusive strategies to overcome the challenges of m- (mobile) and e- (electronic) learning. This kind of EE can be a powerful tool in developing reliable data while enhancing citizens’ agency in working towards Sustainable Development Goals (SDGs).

Qiaoli Bai, Yaping Bai

ObjectiveTo probe the heterogeneity and the influences of clinical nurses’ perceptions of differential atmosphere, and to investigate the relationship between each profile of differential atmosphere perception and organizational silence.MethodsWe adopted the General Information Questionnaire, the Differential Atmosphere Scale, and the Nurses’ Organizational Silence Assessment Questionnaire to survey 523 clinical nurses in three tertiary general hospitals in Shaanxi Province. And we estimated the potential categories of clinical nurses’ differential atmosphere perceptions via latent profile analysis, and quantified the influences on each profile via χ2 and logistic regression analyses, and probed the differences in the organizational silence scores of individuals with three differential atmosphere perception profiles through the least significant difference (LSD) method.ResultsThe differential atmosphere perception of clinical nurses was divided into “Insiders” (16.25%), “Go-betweens” (57.55%), and “Outsiders” (26.20%). Monthly income and years of working experience were the influencing factors of different categories of nurses’ differential atmosphere perceptions. There was a significant difference on the total organizational silence score and on the three profiles (p < 0.001), specifically, “Outsiders” > “Go-betweens” > “Insiders.”ConclusionThis study has identified three distinct subgroups in the differential atmosphere perception of nurses and their influencing factors. The findings demonstrated the heterogeneity among the clinical nursing population. Nursing managers may take prompt and targeted measures to reduce differential atmosphere perception, so as to improve the development of the nursing team.

Eunhae Lee, Pat Pataranutaporn, Judith Amores et al.

Could belief in AI predictions be just another form of superstition? This study investigates psychological factors that influence belief in AI predictions about personal behavior, comparing it to belief in astrology- and personality-based predictions. Through an experiment with 238 participants, we examined how cognitive style, paranormal beliefs, AI attitudes, personality traits, and other factors affect perceived validity, reliability, usefulness, and personalization of predictions from different sources. Our findings reveal that belief in AI predictions is positively correlated with belief in predictions based on astrology and personality psychology. Notably, paranormal beliefs and positive attitudes about AI significantly increased perceived validity, reliability, usefulness, and personalization of AI predictions. Conscientiousness was negatively correlated with belief in predictions across all sources, and interest in the prediction topic increased believability across predictions. Surprisingly, we found no evidence that cognitive style has an impact on belief in fictitious AI-generated predictions. These results highlight the "rational superstition" phenomenon in AI, where belief is driven more by mental heuristics and intuition than critical evaluation. This research advances our understanding of the psychology of human-AI interaction, offering insights into designing and promoting AI systems that foster appropriate trust and skepticism, critical for responsible integration in an increasingly AI-driven world.

Theodore Longtchi, Rosana Montañez Rodriguez, Kora Gwartney et al.

Malicious emails including Phishing, Spam, and Scam are one significant class of cyber social engineering attacks. Despite numerous defenses to counter them, the problem remains largely open. The ineffectiveness of current defenses can be attributed to our superficial understanding of the psychological properties that make these attacks successful. This problem motivates us to investigate the psychological sophistication, or sophistication for short, of malicious emails. We propose an innovative framework that accommodates two important and complementary aspects of sophistication, dubbed Psychological Techniques, PTechs, and Psychological Tactics, PTacs. We propose metrics and grading rules for human experts to assess the sophistication of malicious emails via the lens of these PTechs and PTacs. To demonstrate the usefulness of the framework, we conduct a case study based on 1,036 malicious emails assessed by four independent graders. Our results show that malicious emails are psychologically sophisticated, while exhibiting both commonalities and different patterns in terms of their PTechs and PTacs. Results also show that previous studies might have focused on dealing with the less proliferated PTechs such as Persuasion and PTacs such as Reward, rather than the most proliferated PTechs such as Attention Grabbing and Impersonation, and PTacs such as Fit and Form and Familiarity that are identified in this study. We also found among others that social events are widely exploited by attackers in contextualizing their malicious emails. These findings could be leveraged to guide the design of effective defenses against malicious emails.

Dmitry Ryvkin, Qin Wu

We study the optimal allocation of prizes in rank-order tournaments with loss averse agents. Prize sharing becomes increasingly optimal with loss aversion because more equitable prizes reduce the marginal psychological cost of anticipated losses. Furthermore, loss aversion can boost effort if prizes are sufficiently equitable, but otherwise effort declines with loss aversion. Overall, these results give credence to more equitable allocations of competitive rewards. A win-win scenario is where optimal prizes are equitable even under loss neutrality, in which case the principal benefits from agents' loss aversion.

Marta Kwiatkowska, Gethin Norman, David Parker et al.

Game theory provides an effective way to model strategic interactions among rational agents. In the context of formal verification, these ideas can be used to produce guarantees on the correctness of multi-agent systems, with a diverse range of applications from computer security to autonomous driving. Psychological games (PGs) were developed as a way to model and analyse agents with belief-dependent motivations, opening up the possibility to model how human emotions can influence behaviour. In PGs, players' utilities depend not only on what actually happens (which strategies players choose to adopt), but also on what the players had expected to happen (their belief as to the strategies that would be played). Despite receiving much attention in fields such as economics and psychology, very little consideration has been given to their applicability to problems in computer science, nor to practical algorithms and tool support. In this paper, we start to bridge that gap, proposing methods to solve PGs and implementing them within PRISM-games, a formal verification tool for stochastic games. We discuss how to model these games, highlight specific challenges for their analysis and illustrate the usefulness of our approach on several case studies, including human behaviour in traffic scenarios.

Marcelo Viktor Gilge

Ernst Haeckel (1834-1919) foi um renomado pesquisador alemão da segunda metade do século XIX e início do século XX. Parte de sua produção científica foi devotada a defender e divulgar as ideias darwinianas de modificação das espécies em seu país. Entre as ideias de Haeckel, destaca-se a Lei Biogenética Fundamental, na qual ele afirmava que os estágios de desenvolvimento pelos quais passam os embriões recapitulam a história evolutiva do filo. Para explicar essa ideia, na obra Natürliche Schöpfungsgeschichte (História Natural da Criação) de 1868, Haeckel utilizou ilustrações de embriões que foram alvo de críticas e acusações de fraude e plágio. Este artigo tem por objetivos analisar o uso que Ernst Haeckel fez dessas ilustrações, relatando algumas das críticas de cientistas contemporâneas e posteriores e proporcionar um material para atividades pedagógicas voltadas ao ensino de evolução biológica e desenvolvimento embrionário. Em aproximação a análises realizadas por alguns historiadores da ciência, conclui-se que Haeckel se defendeu razoavelmente e que a motivação maior das críticas era o ataque ao darwinismo.

Ross Hyman, Deb Otis, Seamus Allen et al.

We present the core support criterion, a voting criterion satisfied by Instant Runoff Voting (IRV) that is analogous to the Condorcet criterion but reflective of a different majority rule philosophy. Condorcet methods can be thought of as conducting elections between each pair of candidates, counting all ballots to determine the winner of each pair-election. IRV can also be thought of as conducting elections between all pairs of candidates but for each pair-election only counting ballots from voters who do not prefer another major candidate (as determined self-consistently from the IRV social ranking) to the two candidates in contention. The appropriateness of including all ballots or a subset of ballots for a pair-election, depends on whether the society deems the entire or a selected ballot set in compliance with freedom of association (which implies freedom of non-association) for a given pair election. Arguments based on freedom of association rely on more information about an electorate than can be learned from ranked ballots alone. We present a freedom-of-association based argument to explain why IRV may be preferable to Condorcet in some circumstances, including the 2022 Alaska special congressional election, based on the political context of that election.

Anastasiia Tkalich, Darja Smite, Nina Haugland Andersen et al.

Psychological safety is a precondition for learning and success in software teams. Companies such as SavingsBank, which is discussed in this article, have developed good practices to facilitate psychological safety, most of which depend on face-to-face interaction. However, what happens to psychological safety when working remotely? In this article, we explore how Norwegian software developers experienced pandemic and post-pandemic remote work and describe simple behaviors and attitudes related to psychological safety. We pay special attention to the hybrid work mode, in which team members alternate days in the office with days working from home. Our key takeaway is that spontaneous interaction in the office facilitates psychological safety, while remote work increases the thresholds for both spontaneous interaction and psychological safety. We recommend that software teams synchronize their office presence to increase chances for spontaneous interaction in the office while benefitting from focused work while at home.

Jiyun Luo, Yan Yang, Valerie Nayak et al.

Searcher struggle is important feedback to Web search engines. Existing Web search struggle detection methods rely on effort-based features to identify the struggling moments. Their underlying assumption is that the more effort a user spends, the more struggling the user may be. However, recent studies have suggested this simple association might be incorrect. This paper proposes a new feature modulation method for struggle detection and refers to the reversal theory in psychology. The reversal theory (RT) points out that instead of having a static personality trait, people constantly switch between opposite psychological states, complicating the relationship between the efforts they spend and the level of frustration they feel. Supported by the theory, our method modulates the effort-based features based on RT's bi-modal arousal model. Evaluations on week-long Web search logs confirm that the proposed method can statistically significantly improve state-of-the-art struggle detection methods.

Mohit Chandra, Manvith Reddy, Shradha Sehgal et al.

The COVID-19 pandemic has disrupted people's lives driving them to act in fear, anxiety, and anger, leading to worldwide racist events in the physical world and online social networks. Though there are works focusing on Sinophobia during the COVID-19 pandemic, less attention has been given to the recent surge in Islamophobia. A large number of positive cases arising out of the religious Tablighi Jamaat gathering has driven people towards forming anti-Muslim communities around hashtags like #coronajihad, #tablighijamaatvirus on Twitter. In addition to the online spaces, the rise in Islamophobia has also resulted in increased hate crimes in the real world. Hence, an investigation is required to create interventions. To the best of our knowledge, we present the first large-scale quantitative study linking Islamophobia with COVID-19. In this paper, we present CoronaBias dataset which focuses on anti-Muslim hate spanning four months, with over 410,990 tweets from 244,229 unique users. We use this dataset to perform longitudinal analysis. We find the relation between the trend on Twitter with the offline events that happened over time, measure the qualitative changes in the context associated with the Muslim community, and perform macro and micro topic analysis to find prevalent topics. We also explore the nature of the content, focusing on the toxicity of the URLs shared within the tweets present in the CoronaBias dataset. Apart from the content-based analysis, we focus on user analysis, revealing that the portrayal of religion as a symbol of patriotism played a crucial role in deciding how the Muslim community was perceived during the pandemic. Through these experiments, we reveal the existence of anti-Muslim rhetoric around COVID-19 in the Indian sub-continent.

Ninfa Cardenas, Jorge Iván Parra

La narradora argentina Samanta Schweblin, perteneciente a las selecciones Granta y Bogotá 39, es autora de las novelas Kentukis, Distancia de rescate y los libros de cuentos Siete casas vacías y Pájaros en la boca. Su narrativa, por sus características, puede considerarse femenina (incluso feminista), en tanto crea universos desde la perspectiva de la mujer, en los cuales su mundo —con todos sus objetos, situaciones, roles, vivencias— se pone en evidencia y se cuestiona, incluso desde las técnicas de escritura. Este artículo ofrece una lectura del ámbito familiar construido en la narrativa de la autora argentina, los libros Distancia de rescate (2014) y Pájaros en la boca (2009), desde una voz femenina que puede considerarse parte de ese “nuevo canon” en la literatura latinoamericana.

Viviane Magno

This article offers an overview of Marilena Chaui’s reading of the <i>Tractatus Theologico-Politicus</i> (TTP). Chaui has published numerous books and essays on Baruch Spinoza. Her two-volume study <i>The Nerve of Reality</i> is the culmination of a decades-long engagement with the Dutch philosopher, and her research has been a valuable resource for generations of Latin American scholars. From this extensive output, we focus on Chaui’s main texts on the theological-political, concentrating on her analysis of the concept of superstition and the philosophical language of the TTP, which Chaui calls a “counter-discourse”. Spinoza’s enduring relevance for the interpretation of contemporary phenomena is clarified by Chaui’s analysis of the TTP, which establishes a fundamentally political understanding of superstition.

Saku Sugawara, Pontus Stenetorp, Akiko Aizawa

Machine reading comprehension (MRC) has received considerable attention as a benchmark for natural language understanding. However, the conventional task design of MRC lacks explainability beyond the model interpretation, i.e., reading comprehension by a model cannot be explained in human terms. To this end, this position paper provides a theoretical basis for the design of MRC datasets based on psychology as well as psychometrics, and summarizes it in terms of the prerequisites for benchmarking MRC. We conclude that future datasets should (i) evaluate the capability of the model for constructing a coherent and grounded representation to understand context-dependent situations and (ii) ensure substantive validity by shortcut-proof questions and explanation as a part of the task design.

Alessandro Sarti, Anna Longo