Scopus

This article examines objections to the use of artificial intelligence (AI) in decisions affecting humans and argues that most objections rest on anthropocentric assumptions rather than evidence about decision quality. Critics often presume that human decision makers are uniquely capable of moral and contextual judgment, while AI systems are inferior, opaque or hostile. The article challenges this view arguing that modern AI systems are an expression of collective human intelligence and ethics, built on the image of human cognition, trained on curated human decisions and operating on best decision making frameworks. Drawing on empirical studies the article shows that modern AI systems offer unique advantages in decision-making, thus may already in some domains be as good at making good decisions as an average individual human. The article deconstructs main criticisms of AI decision-making and introduces the novel argument of inseparability between human and AI decisions. Human and AI contributions are increasingly intertwined, AI involvement is latent and appropriated by humans, making existing accountability frameworks based on a clear human–AI boundary obsolete. The article advocates for the development of agnostic decision-making frameworks that apply universal accountability to both human and non-human agents and provide a path to better decisions.

Performance-based funding systems (PBFSs) are widely used to steer national research, but their effects vary significantly, particularly in countries with emerging research ecosystems. Relatively little attention has been paid to PBFSs and their concomitant policy dynamics in these countries, where the pressure to internationalise creates unique challenges. This paper presents a detailed study of the development of the Lithuanian PBFS from 2005 to 2022. Using a multi-level, multi-actor, and multi-issue framework, we combine policy analysis, semi-structured interviews, and bibliometric data to analyse the system’s evolution. Our findings reveal a dynamic of ‘insular policy feedback,’ where a concentrated scientific elite, operating across all levels of governance, shapes policy to its advantage. This results in predictable cycles of strategic gaming, such as the proliferation of domestic journals, by reactive and often inconsistent state countermeasures. The Lithuanian case serves as a model for understanding how concentrated power structures can undermine reform, offering a crucial insight for policymakers: meaningful reform must address the governance structures that empower performance metrics, not just the metrics themselves.

Nature connectedness, a widely used psychological construct which encompasses affective and cognitive aspects of the relationship a person has with nature, has become a central variable of interest in environmental psychology literature. This interest is motivated partially by its enhancing effects on well-being outcomes. However, comprehensive international evaluations of the link between nature connectedness and well-being remain sparse. In this registered report, we propose a secondary analysis of previously collected data to examine how individual differences in nature connectedness relate to multiple aspects of well-being (i.e., purpose in life, hope, mindfulness, life satisfaction, and optimism) across 75 countries (N = 36,803). Within-country and between-country analyses (linear and mixed regressions) suggested that nature connectedness is a robust positive predictor of well-being. Our findings highlight the importance of nature connected for well-being globally, especially for communities with low access to nature and social resources.

Resilience stress testing has emerged as an established method for evaluating how critical infrastructure performs under disruption. Methods that have matured around it parameterize physical components in detail while representing operators as constants, abstractions, or sources of error. Human performance variability deserves analytical treatment comparable to that given to physical assets. We define human factors here as the cognitive, behavioral, and organizational characteristics of operators, supervisors, and decision-makers that shape system response. The paper reviews prior efforts to integrate human factors with infrastructure resilience analysis, identifies where those efforts fall short at the operational layer, and sets out five research priorities: measurement that is feasible at operational scale; data practices that turn existing records into modeling-ready inputs; hybrid modeling that combines agent-based, system dynamics, and network methods; cross-scale and cross-domain integration that does not overstate transferability; and governance that protects both data quality and the people who generate it. Human performance can be quantified in forms that operators will adopt, provided the tools fit operational reality.

Scope 3 greenhouse gas (GHG) emissions and cyber-physical resilience are typically governed through separate institutional and operational frameworks, despite their growing interdependence in digitally mediated supply chains. This separation creates an execution gap that fragments decarbonization, resilience, and investment decisions across data architectures and organizational functions. Grounded in resilience theory and a transdisciplinary systems perspective, this study advances the testable hypothesis that institutional separation of Scope 3 emissions management and cyber-physical resilience is associated with lower system performance, whereas integration through digital governance mechanisms improves operational resilience, emissions measurement accuracy, and financial decision coherence. System performance is operationalized through three dimensions: (1) supply-chain observability and data integration; (2) resilience capacity across the prepare–absorb–recover–adapt cycle; and (3) coherence of investment decision-making under dual materiality. The study applies a structured integrative review with analytical triangulation across sectoral datasets, cyber-risk distributions, and governance frameworks, complemented by an illustrative application in emergency medical services (EMS) in Lithuania. Findings indicate that Scope 3 burdens and cyber-physical risks co-locate in supplier-intensive and digitally dependent sectors, revealing systemic vulnerability; and that effective integration requires a joint governance architecture linking digital observability, standards, financial evaluation, and human-centered decision-making. The article contributes an integrative framework that reframes decarbonization and cyber-physical resilience as a unified systems problem and provides an operational basis for coordinated governance across sustainable supply chains.

Network simulation is a cost-effective, widely adopted method for testing and improving new protocols and solutions in Mobile Ad Hoc Networks (MANETs). Despite the prevalence of simulation-based studies, the absence of unified, extensible frameworks limits the modelling of end-to-end communication and the generation of reusable datasets necessary for research reproducibility. Our paper introduces a simulation framework for evaluating MANETs in Search and Rescue (SAR) scenarios, developed entirely in NS-3 to streamline both simulation and dataset generation. The framework incorporates mobility modelling, energy tracking, communication dynamics, and quality of service (QoS) logging within a modular architecture. It implements heterogeneous nodes with role-specific behaviours and supports discovery mechanisms such as line-of-sight, beacon broadcasting, and signal-based detection. Two simulation versions are implemented using different propagation loss models to assess performance under ideal and obstructed conditions. Routing protocols, including AODV, OLSR, and DSDV, are evaluated across varying scalability levels. Our results confirm established trends in MANET routing and demonstrate the framework’s flexibility in simulating mission-driven environments. The work presents multiple datasets and a reusable, extensible, scenario-driven simulation environment for researchers investigating MANET behaviour in complex applications such as disaster relief and tactical communications.

This study investigates how audience segmentation can support strategies to address climate change disinformation. A nationally representative survey conducted in Lithuania in 2024 used latent class analysis (LCA) to identify four audience segments based on perceptions of science, trust in research, and media use: “Engaged Enthusiasts,”” Informed Sceptics,” “Occasional Observers,” and the “Hard-to-Reach.” While the segmentation structure is comparable to earlier findings from Switzerland, differences were observed in demographic composition, media practices, and engagement levels. The questionnaire was adapted to the Lithuanian context by including nationally relevant media sources and a section on climate change. Attitudes toward climate change vary across the segments. “Engaged Enthusiasts” strongly align with the scientific consensus and support climate science. “Informed Sceptics” also accept the reality and human causes of climate change, despite their more critical views of science. “Occasional Observers” show the weakest agreement with key climate statements, reflecting low scientific interest. The “Hard-to-Reach” segment, although disengaged from science generally, expresses relatively strong concern about climate change. These findings suggest that counter-disinformation strategies should differentiate between audience segments and align communication with their trust levels and information behaviors.

Renewable energy is a key driver of the sustainable energy transition. To accelerate deployment, the Renewable Energy Directive was amended by Directive (EU) 2023/2413, commonly referred to as ‘RED III’, which raised the Union’s renewable energy target and introduced territorial instruments such as coordinated mapping and renewables acceleration areas. This article examines the legal mechanisms of RED III that have a territorial impact and assesses their interaction with spatial-planning, asking how implementation reshapes the relationship between EU-level regulatory influence and Member State discretion. Utilising doctrinal legal research and concepts from spatial-planning scholarship, the article analyses how RED III operationalises these area-based planning instruments and links them to project authorisation. Lithuania is used as an illustrative implementation example. The findings suggest that RED III does not establish an EU spatial-planning system but strengthens the territorially oriented governance of renewables by connecting plan-level choices to permitting. At the same time, it leaves Member States with substantial discretion over legal form and integration into national planning hierarchies. The article concludes that RED III is a turning point in a specific sense: it makes territorial steering a more explicit and legally structured component of EU renewables governance, without harmonising national spatial planning systems.

Simulation-based training is used to improve child interviewers’ questioning skills. However, not all trainees benefit equally. While some show clear improvement, others make little or no progress. To better understand this variation, we conducted a mega-analysis of four studies (interviews N = 4,634; participants N = 1,838). We examined whether interviewers’ task appraisals, specifically viewing the task as a challenge rather than a threat, could predict their performance in avatar-based child interview simulations. The results showed that higher challenge appraisals were associated with better performance during the immediately following interview simulation. In addition, interviewers who increasingly viewed the task as a challenge over time also demonstrated greater learning gains, such as asking more recommended questions and obtaining more accurate information. These effects were especially strong among those with less prior experience. However, interviewers with more experience did not always improve, and in some cases performed worse. These findings suggest that how interviewers evaluate the task potentially plays a key role in both immediate performance and long-term learning. Training programs should address evolving appraisals to enhance effectiveness.

Introduction – E-learning is a central component of higher education, yet maintaining student motivation remains difficult. Although personality traits, mental health, and peer support have each been linked to learning motivation, they are seldom examined simultaneously within an integrative framework. Drawing on Self-Determination Theory, this study examined the associations among personality traits, anxiety and depression, peer-to-peer confirmation, and learning motivating factors in e-learning. Methods – A cross-sectional online survey was completed by 595 e-learners from Lithuanian universities and Turing College. Data were collected using an online self-report questionnaire. Participants completed the Learning Motivating Factors Questionnaire, the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder Scale (GAD-7), Student-to-Student Confirmation Scale, and Big Five Inventory-2 (BFI-2). Pearson correlational analyses and structural equation modeling (SEM) were used to estimate associations and indirect pathways. Results – Extraversion, agreeableness, conscientiousness, and openness to experience showed positive correlations with e-learning motivation (r = 0.08–0.39, p < 0.01), whereas neuroticism and mental health symptoms were negatively correlated. The integrated SEM indicated acceptable fit: χ2 (39) = 221, p < 0.001; CFI = 0.921; TLI = 0.888; RMSEA = 0.089 (90% CI [0.077, 0.100]), RMSEA p < 0.001, and SRMR = 0.075. The association between personality traits and e-learning motivation was primarily indirect via peer-to-peer confirmation (β = 0.062), whereas the indirect pathway via mental health was not significant. Peer-to-peer confirmation was positively associated with e-learning motivation (β = 0.256, p < 0.001). Conclusion – Within the proposed model, peer-to-peer confirmation showed the strongest association with e-learning motivation, indicating the relevance of supportive peer interaction for e-learning motivation.