Replicability and reproducibility are essential for scientific credibility, and both are promoted through open science practices and replications. In the area of ââmental health, there is low adherence to these practices. Moreover, there is low replicability of classic studies of human behavior, which makes it essential that studies in replication-extension models be better investigated. Fischhoff's (1975) seminal study gave rise to the âhindsight bias,â one of the most studied decision-making phenomena, described as a belief that the outcome of an event could have been predicted after it had already happened. However, this study has only one published replication. In addition, recent studies have revealed associations between hindsight bias and depressive symptoms under the memory design and with emotionally relevant outcomes. This association has not yet been investigated in a hypothetical design with neutral outcomes, such as Fischhoff's (1975) experiments. In the present study, we conducted a preregistered direct replication of Fischhoffâs Experiment 2 in the Brazilian population (n = 431) with extensions to investigate associations with sociodemographic variables and depressive symptoms. There was no difference (p < 0.05) between retrospective and prospective judgments in our sample. No significant association (p < 0.05) was found between hindsight bias and depressive symptoms or other sociodemographic variables. An exploratory analysis aggregating all comparisons obtained a small effect size for hindsight bias (d = 0.12; 95% CI [0.07; 0.37]). These results suggest a low replicability of Fischhoff's (1975) seminal experiment as well as the absence of associations with depressive symptoms when the phenomenon is obtained through a hypothetical design and with neutral outcomes.
Political Science | Economics
Oligarchic Networks of Influence and Legislatures in Developing Democracies: Evidence from Ukraine
State capture by extremely wealthy elites is a widespread phenomenon in developing democracies, yet the mechanisms through which it works and the impact it has on political and policy outcomes remain poorly understood. I develop a network-based approach to studying captured institutions. Focusing on the national legislature and using social network and regression analyses of unique quantitative data and original interview-based evidence on the case of Ukraine (2014-2022), I demonstrate that oligarchs seek to defend their wealth by promoting as members of parliament individuals who are linked to them via interpersonal ties. The connections between oligarchs and legislators take the form of a highly fragmented, weakly connected, and decentralized network with distinct clusters, in which oligarchs occupy central positions, and influence the adoption of policies related to oligarchs' economic interests. The study has important implications for the scholarship on money in politics, oligarchy, state capture, political connections, neopatrimonialism, legislative politics, political parties, and political representation.
Artificial Intelligence Applications to Deterrence
Daniel Sazhin, Tyler Gandee, Christopher Stevens, Lorraine Borghetti
Deterrence is a cornerstone of military strategy, yet its theoretical foundations, particularly the conflicting predictions of Classical (CDT) and Perfect Deterrence Theory (PDT), lack the empirical validation required to develop effective AI-enabled decision aids. To address this limitation, we propose using experimental methods, primarily the Mutual Deterrence Game (MDG), to rigorously test theoretical predictions and investigate how psychosocial factors like risk aversion and strategic reasoning (k-level thinking) influence human deterrence decisions. Second, it advocates for leveraging these empirical insights to inform the development of AI tools. We demonstrate through simulation that a Reinforcement Learning (RL) agent in an iterated MDG can successfully learn an adversaryâs preferences such as aversion to inequity, challenger gains, or defender losses to model escalatory behavior over time. Recognizing the limitations and inherent escalatory biases of autonomous AI, we contend that a human-machine co-learning framework is the most effective implementation. In this model, humans and AI, including RL and Large Language Models (LLMs), work interdependently to update beliefs, generate courses of action, and model adversarial intent. This integrated research program provides the necessary theoretical and technical foundation for creating advanced decision aids that can help policymakers reduce the likelihood of conflict.
Three Devices in One: Participatory Research, Public Engagement, Three Devices in One: Participatory Research, Public Engagement, and Engineering Workforce Development in the My Streetscape and Engineering Workforce Development in the My Streetscape Summer Research Institute
Cristian Capotescu, Gil Eyal, Jennifer Laird, Jason O. Hallstrom, Donna Chamely-Wilk, Jenny Fondren, Fernanda Martinez, Andrew Smyth
This article examines the My Streetscape Summer Research Institute at the NSF Center for Smart Streetscapes (CS3), a six-week program for rising high school seniors hosted at Columbia University and Florida Atlantic University. The institute integrates engineering workforce development, participatory research, and public engagement in urban testbeds in Harlem, New York, and West Palm Beach, Florida, with a focus on youth from communities historically affected by technological interventions. The authors present the programâs underlying triadic model in which local youth receive interdisciplinary training, conduct fieldwork, and act as intermediaries between university researchers and neighborhood residents. Through mixed-methods activitiesâincluding interviews, surveys, ethnographic observation, and photovoiceâyouth participants elicit community perspectives on emerging urban technologies such as sensing infrastructure, smart crosswalks, and mobility systems, paying particular attention to how community members navigate questions of privacy, safety, and institutional trust. In this program, student-generated deliverables (e.g., needs assessment and research reports, photovoice exhibits, technology demonstrations, and conceptual prototypes) function as recurring, youth-led needs assessments that shape CS3âs research agenda and co-design efforts. The article argues that positioning youth as community researchers within this organizational and public feedback loop reframes trust-building and public engagement as core youth development outcomes within a new approach to engineering education in the United States.
Generative AI Adoption Among Business School Students: Drivers of Use and Policy Implications
The rapid integration of generative Artificial Intelligence (GenAI) tools into higher education presents both transformative potential and pedagogical challenges. This study researches the key factors influencing the adoption of GenAI among business school students, utilizing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) as its theoretical framework. Drawing on survey data from 441 students across the Baltic Sea region, the research employed partial least squares structural equation modeling (PLS-SEM) to estimate the relationships between performance expectancy, effort expectancy, social influence, study value, habit, facilitating conditions, and hedonic motivation in predicting the use of GenAI. The findings reveal that habit, social influence, and study value significantly impact students' adoption of GenAI tools. At the same time, performance expectancy, effort expectancy, facilitating conditions, and hedonic motivation do not show statistically significant effects. These results suggest a behavioral-intention gap, where positive perceptions of GenAI do not consistently translate into usage. The study highlights the importance of fostering habitual engagement and peer-driven norms to encourage meaningful integration of GenAI in academic settings. By offering empirical insights into student behavior, this study contributes to the discourse on digital transformation in higher education. It provides actionable recommendations for educators and policymakers to support the ethical, practical, and student-centered adoption of GenAI, aligning with the conference's mission to advance innovation and quality in higher education studies.
Public Affairs, Public Policy and Public Administration | Organization Development
The Implementation and Effects of PRIME-HRM at the Conrado F. Estrella Regional and Medical and Trauma Center
This study examined the implementation and effects of the Program to Institutionalize Meritocracy and Excellence in Human Resource Management (PRIME-HRM) at the Conrado F. Estrella Regional Medical and Trauma Center, focusing on its role in strengthening public healthcare human resource systems. Using a descriptive-evaluative design, the research assessed four HR systemsâRecruitment, Selection and Placement (RSP); Performance Management (PM); Learning and Development (L&D); and Rewards and Recognition (RR)âin terms of implementation level, organizational impact, and challenges. Results showed that L&D was highly implemented, while RSP, PM, and RR were moderately implemented, indicating institutional progress alongside areas needing improvement, particularly in merit-based practices and performance alignment. PRIME-HRM enhanced HR efficiency, employee engagement, and organizational performance. However, implementation was moderately constrained by limited program awareness, inadequate training, resource constraints, and policy misalignment. The study concludes that sustained PRIME-HRM success depends on institutional readiness, strategic leadership, and systems-based interventions. A comprehensive action plan involving capacity building, policy standardization, technology integration, and strengthened monitoring is recommended to institutionalize a transparent, inclusive, and performance-driven HR system, reinforcing professionalism and accountability in public healthcare management.
Political Science
Access to Legal Information and Refugee Empowerment: Experimental Evidence from Greece
Marine Casalis, Dominik Hangartner, Alexandra Hartman, Rodrigo Sanchez
Can legal empowerment support forcibly displaced people facing high levels of violence and limited incentives to report? We study engagement with legal information and its downstream impact using a randomized encouragement design with 1,707 refugees and asylum seekers in Greece. At baseline, nearly half of participants were unaware of where to seek help after experiencing violence. We randomly encouraged access to either generic legal information via a website, personalized legal information delivered through WhatsApp, or a control condition. Take-up was higher for generic than personalized information. Relative to the control group, personalized information significantly improved knowledge of exploitation and confidence in responding to violence three months later, whereas effects of generic information were smaller and statistically insignificant. We find no detectable effects on more distant outcomes, including mental health and integration. Online trace data suggests that personalized conversations provide tailored guidance and referrals, highlighting a trade-off between scalability and effectiveness.
Other Social and Behavioral Sciences | Anthropology | Linguistics
Global language diversification is linked to socio-ecology and threat status
Remco Bouckaert, David Redding, Artur Trebski, Oliver Sheehan, Russell Gray, Kate E Jones, Quentin Atkinson
Global linguistic diversity reflects the gradual gain and loss of languages over millennia, yet half of the worldâs ~6-7000 languages are threatened with extinction by the end of this century. Attempts to identify factors that promote or reduce linguistic diversity have focused largely on the correlates of current language richness (languages per unit area) and threat status. However, much less work has examined how linguistic diversity is shaped by evolutionary history and the processes of lineage diversification and extinction that underlie it. Here, we use Bayesian phylogenetic inference techniques to generate a supertree of extant human languages (n=6635) that integrates prior knowledge and uncertainty about linguistic diversification around the globe. Our posterior treeset, which represents more than 10 million years of language change, reveals net diversification rates are higher in regions of moderate population density and landscape traversability, for languages spoken over a larger area and further from cities, and for cultures that are reliant on agriculture and maintain political links beyond the local community. By combining our global tree with data on language threat status we also show that evolutionary distinctness (how distantly related a language is to its closest relatives) is positively related to endangerment, and generate a ranking and map of the worldâs most evolutionarily distinct, globally endangered (EDGE) languages. Our findings provide insight into the forces shaping linguistic diversity, indicate more of the evolutionary history of languages is at risk than expected under a random threat distribution, reinforce the need to act now to document and protect this diversity, and pave the way for further refinement of the global tree of human languages.
Public Affairs, Public Policy and Public Administration | Science and Technology Studies | Sociology
Policy-driven innovation: The science-policy nexus in artificial intelligence research in Germany
This study reconstructs and characterises the science-policy nexus in the field of artificial intelligence research in Germany, examining the alignment between normative policy goals and empirical research outcomes. Adopting a narrative policy framework, the research investigates transition dynamics across policy, scholarly, and innovation levels, tracing the interconnectedness in stages of patents, papers, and publicly funded projects. The research employs a two-pronged empirical approach: 1) identifying German contributions to AI research through patent citations and bibliometric data, and 2) linking these outputs to the policy instances that funded and enabled them. This methodology reveals the complex pathways through which policy intentions translate into research outcomes, highlighting the mostly indirect nature of this relationship. Key findings emphasise significant challenges in data quality and availability, particularly in linking research outputs to higher-level policy dimensions. While the study successfully identifies German-affiliated papers through patent and bibliometric datasets, it uncovers fundamental disconnections between stated policy objectives and actual research trajectories. These dimensions are compounded by administrative bottlenecks, asynchronous implementation settings, and entangled funding periods. The study concludes that AI development is heavily influenced by geopolitical and strategic decisions extending beyond academia, and that academic research into AI is part of a larger narrative of policy and political design. The study offers a framework for assessing the nuances of science-policy pathways while acknowledging the limitations of fully characterising this nexus. The systematisation presented serves as a foundation for future research, emphasising the need for comprehensive and coherent data sources to evaluate the phases and connections within scholarly and policy narratives.
Economics
Disruption or Augmentation? The Changing Demand for AI Skills in the Age of Generative AI
We study how the introduction of generative AI (GPT-3) has impacted the demand for AI-related skills in the European labour market. Using a novel large-scale collection of online job advertisements in in twenty two European Union countries and the United Kingdom, we develop a detailed classification of AI skills and tasks, and we exploit the release of GPT-3 in November 2022 as a natural experiment and apply a difference-in-differences estimation to assess the shifts in the demand for AI skills for occupations that are exposed to ChatGPT relative to not-exposed occupations. We find that GPT-3 had a negative and statistically significant impact on the share of AI job ads for occupations in the treated group relative to the control group, so that the availability of generative AI decreased the demand for occupations whose most frequent core task is automatable through ChatGPT. To the best of our knowledge, this is the first paper that proposes a detailed classification framework and robust identification strategy to study the impact of generative AI on labour demand.
Science and Technology Law | Computer Law | Law and Politics | Law and Philosophy | Internet Law | European Law | Communications Law | Political Science | Communication
Regulating Authenticity in Artificial Times: Synthetic interactions, democratic risks, and the limitations of the AI Actâs transparency obligations.
The AI Act wants to mitigate the democratic risks that arise when people can no longer reliably distinguish synthetic from human-generated and authentic content. This manuscript critically examines the regulatory function the AI Act assigns to the notion of âauthenticityâ in addressing these risks. An ambiguous and contested notion, authenticity broadly captures the correspondence between what a particular thing or object is and what it claims to be. This paper first examines how (perceptions of) authenticity are constructed (What does authenticity entail? Section 2) and second how these perceptions may inform peopleâs (1) assessment of journalistic content, (2) evaluation of political communication, and (3) capacity for self-expression and identity formation (Why does authenticity matter from a democratic perspective? Section 3). We then analyse how the use of Generative AI can affect (both positively and negatively) perceptions of authenticity in these three domains (How does AI affect authenticity? Section 4). In a final step, we use this framework as a critical lens to reappraise the protection Article 50 of the AI Act affords, and its transparency and disclosure obligations (Does Article 50 AI Act effectively protect people against unwarranted authenticity-distortions? Section 5). Our analysis demonstrates why the Article 50 AI Act fails to empower citizens against the democratic risks synthetic media pose. At a foundational level, the AI Act conflates artificiality with inauthenticity and untrustworthiness, thereby undermining its intended ambition of safeguarding the democratic integrity and foundations of the information society. At an operational level, the lawâs disclosure obligations lack sufficient granularity to enable citizens to engage with and critically assess the outputs of generative systems. Transparency strategies that relay information about why AI was used and for what purposes, the data underpinning content generation, and the (professional) values of the actor responsible for the content could be more empowering. At the same time, we should remain cautious: people might rely on the anonymity that AI affords to express themselves or spread political messages. In these cases, far-reaching disclosure obligations could be counterproductive.
Economics
Norm heterogeneity and the emergence of cooperation A spatial agent-based model of conditional cooperation
Daniel MartĂnez-Felip, Steven G.M. Schilizzi, Chi Nguyen, David Pannell
The resolution of collective-action problems often depends on social norms and pressure to conform to group behaviour, yet individuals typically differ in how strongly they perceive and internalise these norms. While existing models of norm change and social tipping often assume homogeneous and static normative expectations, recent evidence suggests substantial heterogeneity in the perceived norm strength. We study how different compositions of such heterogeneity within a community shape the emergence and internalisation of cooperative behaviour. We develop a spatial agent-based model in which agents follow a conditional-cooperation norm but differ in norm strength, characterised as either tight or loose. Agents interact locally and update their cooperation thresholds endogenously through a combination of payoff-driven learning and social learning from experiencing group behaviour. Our results show that introducing a moderate share of loose-norm individuals into otherwise tight-dominated communities can facilitate the emergence of cooperative tipping points by enabling cooperation to seed and spread locally, even when agents place zero weight on social-relative-to-financial learning. However, whether cooperation becomes internalised and persists depends critically on the relative weight given to social and financial learning. A higher weight on social learning amplifies local behavioural feedbacks, sharpens tipping-point dynamics, and allows agents with tight social norms to internalise cooperation such that it can be sustained with fewer cooperating group members. Once cooperation spreads, conformity pressure stabilises cooperative behaviour among loose-social-norm agents. Taken together, our findings highlight the importance of community composition and norm-strength heterogeneity for collective-action dynamics, and show how heterogeneity in perceived norm strength can generate abrupt and persistent transitions in cooperative behaviour.
Legal Writing and Research | Science and Technology Law | Legal Ethics and Professional Responsibility | Other Law | Law and Philosophy | Internet Law | Legal Studies | Science and Technology Studies
Legal interpretation and AI: From expert systems to argumentation and LLMs
AI and Law research has encountered legal interpretation in different ways, in the context of its evolving approaches and methodologies. Research on expert system has focused on legal knowledge engineering, with the goal of ensuring that human-generated interpretations can be precisely transferred into knowledge-bases, to be consistently applied. Research on argumentation has aimed at representing the structure of interpretive arguments, as well as their dialectical interactions, to assess of the acceptability of interpretive claims within argumentation frameworks. Research on machine learning has focused on the automated generation of interpretive suggestions and arguments, through general and specialised GenAI tools, now being increasingly deployed in legal practice.
Science and Technology Studies | Sociology
Eco-Digital Posthumanism: Eco-Digital Co-Responsible Agency, Genealogy and Research Agenda
Eco-Digital Posthumanism is a sociological-philosophical theory that redefines subject formation and civic responsibility at the intersection of ecological systems and digital infrastructures. While posthumanist thought has powerfully decentred the human subject, and critical data studies have examined the material conditions of digital architectures, their co-constitution remains undertheorized. This article addresses that gap. It does so through three theoretical moves. Drawing on Barad's intra-action (Barad, 2007), it rejects the presumption that entities precede relations. Haraway's notion of sympoiesis (Haraway, 2016) situates subjectivity within multispecies processes of co-becoming, resisting the reduction of ecology to measurable footprint. Braidotti's relational ethics (Braidotti, 2013) reframes the posthuman subject as embodied, embedded, and fundamentally non-autonomous. Their approaches diverge in emphasis yet converge in destabilizing the fiction of the self-standing individual. From this convergence, the theory derives its central construct: eco-digital co-responsible agency, namely the proposition that if agency is distributed across humans, non-humans, and digital infrastructures, responsibility cannot be individualized but must be shared ecologically and technologically. This onto-epistemological claim, following Barad's inseparability of ethics and ontology (Barad, 2007), grounds the theory's normative implications rather than reducing them to design prescriptions. At the centre of the theory lies an unresolved tension. Ecological re-embedding (grounded in place, embodied attentiveness and material co-presence) confronts the dis-embedding logic of algorithmic platforms, curated self-performance, and data colonialism (Couldry & Mejias, 2019). The theory does not seek to dissolve this contradiction. It treats it as analytically generative. Its implications extend to education, AI ethics, media studies, and civic ecology, demanding a reconfiguration of institutional and technological arrangements that currently amplify algorithmic mass individualism.
Political Science | Communication | Sociology
Testing Content Analysis through Different Large Language Models: Towards a Gold Standard Protocol
This paper proposes a comprehensive assessment of content analysis performed by different Large Language Models (LLMs), in order to develop a gold standard protocol for using LLMs in content analysis research. The study relies on 1,500 cases sampled from a dataset of approximately 4,000 Facebook posts from political leaders in six countries (Italy, Spain, France, Greece, Germany, and the Netherlands), which have been human-coded for 17 variables related to populism content and communication style. The same corpus of Facebook posts and the identical codebook used by human codersâcontaining variable descriptions and instructionsâwere applied to four distinct LLMs (six versions): ChatGPT (3.5 and 4o), Gemini 1.5 (flash and pro), Llama 3 (70B), and Mistral Large. The coding has been compared among the LLMs, as well as between the LLMs and human coders. To assess the performance of the LLMs, the consistency between LLMs and human coders was quantified using inter-coder reliability measures. In cases of discrepancies between human and LLM coding, the research team implemented a supervised assessment procedure to identify the correct response, simultaneously verifying the reliability of both human and LLM content analysis. The significance of this research lies in its potential to evaluate the capabilities of various LLMs, particularly in non-English languages, and to establish a standardized protocol for utilizing LLMs in content analysis within political and communication studies. This study aims to advance our understanding of LLMsâ efficacy in replicating human coding processes and their application in multilingual contexts, ultimately contributing to the methodological rigor in the field of computational content analysis.
Understanding contraceptive and hormonal medication decision-making for pregnancy prevention and management of gynaecological symptoms: A systematic review of UK evidence
NIHR Policy Research Unit in Reproductive Health, Elena Proffitt, Disha Dhar, Lois Harvey-Pescott, Ellie Brown, Abigail McNiven, Ammaarah Felix, Egrada De Lima, Yasmin Rahman, Julia V Bailey
Background There has been a decline in the number of contraceptive appointments and prescriptions in the UK. Existing evidence explores the impact of access, barriers and awareness on contraception use. However, less is known about the nuance of how individuals make these decisions. This review aimed to synthesise recent UK evidence on those assigned female at birthâs attitudes, experiences and decision-making around contraception and hormonal medication for pregnancy prevention and/or gynaecological reasons. Methods Five academic databases and six online sources were systematically searched. Included studies were published in English from 2015 onwards and contained primary data on contraceptive decision-making for pregnancy prevention and/or gynaecological treatment in the UK. Studies were critically appraised for methodological reliability and usefulness. Data were coded deductively, inductively grouped conceptually, and mapped onto a conceptual framework. Results 21 studies met the inclusion criteria. The majority were qualitative and focused on pregnancy prevention. The synthesis demonstrates that decision-making is shaped by how methods felt in relation to the body; trading off positive and adverse effects; experiences navigating different information sources; balancing clinical and cultural pressures against bodily autonomy; and personal perceptions of risk and fulfilling intimate desires. Conclusion Contraceptive and hormonal medication decision-making is a dynamic process shaped by complex trade-off balances, trial-and-error processes, evolving needs, and individual contexts. Individuals often want to involve and trust others by sharing the decision-making process. Person-centred healthcare consultations must recognise the complexity of choice, use, and to support contraceptive and hormonal medication decision-making across the life course.
Public Affairs, Public Policy and Public Administration | Sociology
Algorithmic Accountability in Public Administration: A Systematic Review and Conceptual Framework for Responsible AI Governance
(This manuscript is a preprint and has not been peer reviewed.) The increasing use of artificial intelligence (AI) in government decision-making has raised important questions about accountability in public administration. While AI technologies offer opportunities to improve efficiency, data analysis, and public service delivery, the integration of algorithmic systems into administrative processes also introduces new governance challenges related to transparency, responsibility, and democratic oversight. This study examines how algorithmic accountability is addressed in the existing literature on artificial intelligence in the public sector. Using a systematic literature review guided by the PRISMA framework, the study analyzes 45 peer-reviewed publications drawn from major academic databases. The findings identify five key governance dimensions discussed in the literature: transparency in algorithmic decision-making, explainability of AI systems, human oversight and administrative responsibility, ethical governance of artificial intelligence, and public trust in digital government. Based on these findings, the study proposes a conceptual framework that explains how these governance mechanisms interact to support accountable algorithmic decision systems in public administration. The framework extends traditional public administration theories of accountability to the emerging governance challenges created by algorithmic decision systems.
Other Social and Behavioral Sciences | Anthropology
Politicizing menopausal flesh: Collective bodies and affective endurance in graphic narrative
Menopause is often stigmatized and viewed as a private health issue, contributing to the marginalization of aging female bodies. Despite the rise of medical humanities, menopause is rarely examined as a site of bodily regulation politics. This paper addresses this gap by examining Menopause: A Comic Treatment (2020), edited by MK Czerwiec, as a graphic narrative that reframes menopause as a collective, politically significant embodied experience, and argues how the collective graphic storytelling challenges the medical and cultural isolation of menopausal bodies. The anthologyâs collective format and rejection of singular authorship function as a political strategy that resists the isolation imposed on menopausal femininity. Methodologically, this paper employs close visual-textual analysis of four selected narratives from the anthology by MK Czerwiec, Mimi Pond, Ajuan Mance, and Susan Squier and Shelley Wall, read as strategic components of a unified formal intervention. Drawing on feminist medical humanities (Emily Martin, Margaret Lock), biopolitical theory (Michael Foucault), and graphic medicine scholarship (Susan Squier, Ian Williams), the analysis shows how graphic form through humor, visual metaphor, fragmentation, and multimodality render menopausal experiences visible while exposing the institutional, cultural, and biomedical forces shaping aging femininity. Rather than treating comics as supplements to medical knowledge, this paper explores graphic narrative as an epistemological mode that generates embodied understanding. It argues that the politics of flesh shapes how institutional regulation of menopausal bodies reshapes affective life and endurance, foregrounding lived aging experience without reinforcing mind-body dualism. By framing the narrative representation of menopause as a political practice rather than a pathological condition, the paper contributes to interdisciplinary discussions of embodiment, narrative resistance, and the critical potential of graphic literature to challenge dominant stereotypes of gendered aging.
Other Social and Behavioral Sciences
A meta-analysis of stable isotope data from early Pacific Island colonisation to complex chiefdoms
Ashleigh Rogers, S. Anna Florin, Alison Crowther, Natasha Lyall, Carlo Cocozza, Ricardo Fernandes
The Pacific Islands offer a singular setting to examine how human populations adapted to conditions of extreme isolation and ecological variability over millennia. Yet key questions persist about the pace of initial colonization, the development of social inequalities, and the varying roles of marine and terrestrial resources in these processes. Stable isotope analysis of human remains provides a direct means to investigate subsistence, mobility, and social differentiation, complementing archaeological proxies that may be absent or ambiguous. Here we present the first large-scale meta-analysis of human collagen ÎŽ13C and ÎŽ15N values across the Pacific, synthesized from the newly compiled Oceanian Archaeological and Palaeontological Isotope Database (OAPID). Results reveal regionally distinct isotopic signatures shaped by insularity and biogeography, heavy marine reliance during early colonisation, and increasingly pronounced biological sex-based dietary differentiation through time. Geographic and methodological biases, coupled with limited baseline data, continue to challenge inter-regional comparison. Despite these constraints, expanding isotopic coverage is transforming understandings of Pacific lifeways across the vast and remote region. This synthesis highlights the growing potential of isotopic research to address fundamental questions about the timing of colonisation, the development of social differentiation, and human adaptation to complex island ecosystems and social landscapes.
Modeling Interest Change Using a 22-Year N=1 Lifelog: Connecting Ultra-Long-Term Personal Data with Population Survey Data
This study proposes an exploratory framework for linking N=1 lifelog data with N=ALL administrative survey data in order to examine long-term changes in citizensâ interests in an aging society. It introduces a methodological approach to connecting micro-level âinternal interestâ records with macro-level survey data under a shared conceptual frame, and explores an âinterest contraction hypothesis,â which suggests that the diversity and overall volume of civic interest may decline as populations age. The empirical setting combines a rare 22-year lifelog of the author (15.5 million Japanese characters; N=1) with a 19-year municipal citizen survey (27,720 respondents; N=ALL) and demographic projections from the same city. Using shared interest categories, both datasets are converted into standardized interest scores and analyzed through an Age-Period (AP) modeling framework to provide scenario-based, exploratory extrapolations rather than definitive forecasts. For N=ALL, the model provides exploratory estimates of a very small decline in the mean standardized interest score (â0.7 points by 2050), along with a redistribution of interest from civic and participatory domains toward everyday and later-life concerns. For N=1, the projected decline is somewhat larger (â1.3 points). However, this single case does not aim at statistical generalization; rather, it serves as a methodological testbed for clarifying applicability conditions and limitations of the proposed linkage, including sensitivity to initial values. In addition, the N=1 setting enables log-based traceability, allowing score fluctuations to be traced back to daily textual context and supporting a more contextual interpretation of life-course changes in interest. Overall, the study presents an exploratory methodological framework for connecting N=1 and N=ALL evidence, explicitly articulates its constraints, and offers a foundation for future research on data-informed intervention design. Note: The author declares that this study represents independent research and does not reflect the official views of the Kawasaki City Government. Note: This English version is a translated preprint of the Japanese manuscript.
Environmental Studies | Economics | Public Affairs, Public Policy and Public Administration | Sociology
Health Consequences of Large Data Centers: Air Pollution, Noise, Water Use, and Environmental Justice
The global expansion of large, energy-intensive data centers, accelerated by cloud computing, cryptocurrency, and artificial intelligence (AI), has created growing concern about implications for human health. Emerging scholarship highlights multiple health-relevant pathways: increased emissions of criteria air pollutants from power plants and onsite diesel backup generators, chronic environmental noise from cooling infrastructure, intensive water withdrawals that strain public supplies, and land-use changes that intersect with social determinants of health. Direct epidemiologic evidence on communities living near data centers remains sparse, with most work to date relying on lifecycle emissions modeling and indirect analogy with established air and noise pollution literatures. Nevertheless, modeling studies consistently project that by the late 2020s, U.S. data centers could be responsible for roughly 1,300 premature deaths and up to 600,000 asthma symptom cases annually, with an associated public health burden approaching $20 billion per year. Case studies reviewed document risks related to air pollution, water stress, and noise that fall disproportionately on vulnerable communities, with per-household health cost burdens estimated to reach multiple times the national average in some disadvantaged counties. Drawing on environmental health, noise science, water security, and environmental justice literatures, this article synthesizes current evidence, proposes a conceptual framework organizing four principal exposure pathways, identifies critical research gaps, and outlines policy and planning priorities to ensure that digital infrastructure development is compatible with public health protection and equity.
Outdoor Education | Science and Mathematics Education | Other Social and Behavioral Sciences | Animal Studies
The ethical use of animals in education tool (EUAET): Systematically considering harms, benefits, & unintended consequences
Animals can be highly engaging in educational contexts, yet our use of them is increasingly morally fraught due to decreased access to free living wildlife, enhanced technology for mediated encounters, and advancements in our understanding of animal sentience. As most people are not formally taught how to make difficult moral decisions, educators and organizations can more carefully consider the morality of their animal programs with the Ethical Use of Animals in Education Tool (EUAET, pronounced you-et), a practical ethics-based guide for systematically considering harms, benefits, justifications, and unintended consequences. This article describes the development of the EUAET through conceptual analysis and iterative feedback from education professionals, and walks through the ten steps. Modeling the use of the EUAET on a species or issue people are passionate about can showcase the benefits of more careful moral consideration for students who may otherwise get very little structured practice at it.
Other Social and Behavioral Sciences
Epistemic Parallax: A Theory of Structural Cognitive Misalignment and Its Implications for AI in Neurodivergent Mental Health
The Flatland thought experiment, drawn from Abbott's 1884 novella and developed by Carl Sagan, has been increasingly applied to neurodiversity discourse and artificial intelligence ethics as a metaphor for constrained perception. The standard reading positions neurotypical cognition as the three-dimensional Sphere â the more complete, higher-dimensional observer â and neurodivergent cognition as the two-dimensional Square, generating a cross-section interpreted as disorder rather than difference. This article argues that this reading encodes the deficit model it was designed to challenge and introduces Epistemic Parallax as a novel theoretical construct to correct it. Epistemic Parallax is defined as the systematic displacement in meaning, classification, and judgment that arises when a cognitive system, institutional framework, or artificial intelligence observes neurodivergent experience from a non-parallel normative frame â producing distortions that are a geometric property of the observational relationship rather than a feature of the observed. The construct is distinguished from the Double Empathy Problem, institutional ableism, and algorithmic bias by its specification of mechanism over outcome and its applicability to non-adaptive systems that cannot self-correct through reciprocal interaction. Grounded in the Double Empathy Problem's empirical record, the full dimensional progression from point to tesseract, Intense World Theory, monotropism, and multidimensional sensory processing research, Epistemic Parallax is applied to AI in digital mental health to identify the deployment of neurotypically-trained systems as clinical arbiters of neurodivergent experience as a form of structural hermeneutical injustice in Fricker's precise sense. The Dimensional Parity Standard is proposed as the operational correction, comprising six criteria â bidirectional validation, cross-plane transparency, co-authorship of ground truth, relational deployment, dimensional humility, and a sixth principle extending the Feynman honesty framework developed in the companion article. Implications for regulatory policy, system design, and a three-priority research agenda are identified.
How does early-stage digital connectivity relate to how people distribute trust across social targets? Using nationally representative World Values Survey (Wave 5) data from Egypt in 2008 (N=3,051), we test whether personal computer use (a proxy for early digital capability) is associated with higher trust in socially distant out-groups (people of another religion and people of another nationality) and lower trust in close local ties (neighbors). We estimate logistic regression models with governorate-clustered standard errors and report average marginal effects (percentage-point differences in the probability of reporting "trust completely" or "trust somewhat"), adjusting for demographic and socioeconomic factors, urban residence, employment, religiosity, and political engagement. Compared with respondents who never used a computer, occasional and frequent users are more likely to trust out-groups (+7 to +11 percentage points) and less likely to report high trust in neighbors (-2 to -8 percentage points). A within-respondent trust-gap index (neighbor trust minus mean out-group trust on the 4-point scale) is lower among computer users, consistent with reduced parochialism. Results are similar when we use the full four-point trust scale and when we estimate weighted linear probability models using the WVS sex-correcting weights. Because the data are cross-sectional, the findings are descriptive associations consistent with "trust reallocation," but they cannot separate exposure effects from selection into early computer use.
Computer Sciences
Narrative-Integrated Thematic Analysis (NITA): How can LLMs support theme generation without coding?
Large language models (LLMs) have sparked debate about shifting away from the coding paradigm; yet many applications have focused on replacing human coding rather than facilitating transitions to alternative methods. This article introduces Narrative-Integrated Thematic Analysis (NITA) that allows qualitative researchers to design, train, and guide an LLM in conducting thematic analysis. As a nonpositivist, pragmatist approach, NITA positions researchersâ reflexivity, intellect, and judgment at the center of the analysis process. This approach combines a reflexive, iterative monitoring, evaluation, and learning procedure (PERFECT) with a conversational method for interacting with LLMs. We experimented with the LLM through six stages: planning an initial PERFECT procedure, preparation, generating candidate themes, constructing individual narratives, constructing meta-narrative, and writing up. Our findings reveal the transformative potential of LLMs to support researcher-led, noncoding data analysis while maintaining interpretative agency. We argue that GenAI enables researchers to develop an alternative mode of thinking in qualitative data analysis.
Psychology
A Developmental Perspective on the Racial Socialization of White Children: Linguistic and Social-Cognitive Considerations
Grace Reid, Selim Ygit, Ariana Orvell, Emily Foster-Hanson, Ryan F. Lei
While there is growing consensus that it is important to talk about race and racism with children (a process called racial socialization)âparticularly with White childrenâwhat to say when having these discussions is less clear. Here we argue that how parents have these discussions (in addition to what they say) is important to consider, because children might interpret messages differently depending on specific linguistic features. Specifically, we highlight the potential role of abstraction, generic language, and modality as three features of language both researchers and White parents might consider when thinking of racial socialization. We also highlight developmental shifts in how these linguistic features might be interpreted. Finally, we suggest some future directions for racial socialization researchers.
Educational Methods | Social Statistics | Sociology
MultiSpline: Nonlinear Multilevel Spline Modeling Across R, Python, and Stata
We introduce MultiSpline, a cross-platform software suite for nonlinear multilevel spline modeling implemented in R, Python, and Stata. Nonlinear relationships between continuous predictors and outcomes are common in clustered and longitudinal data from education, health, and economics research. Existing tools in each language provide the building blocks for such analyses but typically require researchers to manually combine spline basis construction, mixed-effects estimation, intraclass correlation coefficient (ICC) computation, prediction, and visualization across multiple packages and steps. MultiSpline unifies this workflow into a single interface in each language, enabling researchers to fit, summarize, predict from, and visualize nonlinear multilevel models in only a few lines of code. All implementations are freely available under the MIT license via CRAN (R, under review), PyPI (Python), and SSC (Stata), with source code on GitHub.
International and Area Studies | Economics | Public Affairs, Public Policy and Public Administration | Social Statistics | Sociology
POPULATION GROWTH, INFRASTRUCTURE DEMAND, AND CONSTRUCTION TRADE: SOCIOECONOMIC IMPLICATIONS FOR BANGLADESH
Bangladeshâs population growth and urbanization have heightened demand for construction materials, leading to heavy import reliance amid domestic supply constraints. This study tests whether mature population expansion (aged 18+, proxied by total population and instrumented with an 18-year lag) causally drives these imports and produces an import-amplifying (inverse) home-market effect in a developing economy. An augmented gravity model is estimated on bilateral construction material imports to Bangladesh (1995â2021) using BACI (CEPII), World Bank, and CEPII data. OLS yields counterintuitive negative coefficients on domestic population and construction intensity, likely due to endogeneity. Two-stage least squares, instrumenting construction demand with lagged population, reveals a positive and significant effect in the preferred specification without year fixed effects (fitted coefficient 3.37, p < 0.05), confirming demographic pressure significantly increases imports. The results extend new trade theory by evidencing an inverse home-market effect in intermediate goods trade under supply constraints (Krugman, 1980; Anderson & van Wincoop, 2003). They underscore persistent structural import dependence and the need for accelerated domestic capacity-building, backward linkages, and resilient supply chains to support sustainable infrastructure-led growth. The analysis offers rigorous evidence to inform Bangladeshâs industrial and trade policy.
Other Social and Behavioral Sciences | Psychology | Communication
âIn Real Life, Everything Feels so Differentâ: Autistic, Embodied Perspectives on Online Sociality
Background: Autistic adults often report heightened bodily vulnerability in face-to-face interactions, shaped by factors such as social expectations and sensory demands. With the increasing centrality of online communication, it is important to understand how digital environments can shape embodied experiences and social participation for different autistic people. Methods: This qualitative study used phenomenological interviews with 11 autistic adults living in North America and Europe. We interviewed participants, all of whom were habituated users of online spaces, in their preferred modality (text, audio, or video). Thematic analysis, informed by phenomenological attention to embodiment, identified how participants described bodily attention, agency, and connection across online and offline settings. Results: Participants consistently reported offline interactions requiring extensive bodily monitoring, associated with feelings of scrutiny and exhaustion. Online environments, in contrast, often afforded greater bodily ease, enabling shifts in attention away from self-monitoring toward communication. Participants emphasized novel forms of agency afforded in certain online contexts, helpful in fostering a sense of control. They furthermore described online communication as variably limiting or enriching, but frequently as supporting authentic and comfortable forms of self-expression and connection. Discussion: The findings suggest that online spaces can provide distinctive forms of embodied relief and inclusion for some autistic adults, challenging assumptions that in-person interaction is inherently preferable or superior for everyone. Consideration of autistic embodiment can be crucial for understanding accessible, inclusive platforms and for rethinking normative expectations of communication in both online and offline settings.
Political Science
Party youth wings as forces of renovation: A study of young women membersâ efficacy and ambition
Sofia Ammassari, Duncan McDonnell, Niklas Bolin, Annika Werner, Marco Valbruzzi, Carsten Wegscheider, Reinhard Heinisch, Ann-Cathrine Jungar
Party youth wings are a vital pipeline to power in parliamentary democracies, but have been overlooked by gender scholars. We investigate the political socialization that youth wings offer their women members, focusing on gendered trends as regards two key political attitudes. We ask: Do women and men in youth wings differ in their acquisition of personal efficacy and electoral ambition? Using original survey data from over 3,100 youth wing members in Australia, Austria, Germany, Italy, Spain and Sweden, we find that women are more likely than men to report increased desire to influence party policy and stand as candidates â the latter especially in center-right youth wings. In addition, the more exposed members are to the youth wing, the larger the gender gaps in the acquisition of efficacy and ambition. Our results suggest that, insofar as womenâs political socialization is concerned, youth wings can be forces of renovation within their parties.
Other Social and Behavioral Sciences | Economics | Public Affairs, Public Policy and Public Administration | Science and Technology Studies | Organization Development
Digitale SouverÀnitÀt in der Data Governance Schweizer Unternehmen
As a result of growing international tensions, digital sovereignty has become a topic of increasing relevance for European and Swiss stakeholders. Beyond the significance of digital sovereignty to states and citizens, companies also start to make up their minds about how to control their data and technology. In this paper, we examine how digital sovereignty is perceived in the context of corporate data governance. To this end, we conducted 16 qualitative interviews with politicians, business associations, experts, and representatives of large and small companies from Switzerland. Our results show that knowledge about digital sovereignty is still in its infancy and that many companies have not yet developed specific strategies to address the issue. Nevertheless, many Swiss companies express their willingness to expand efforts on dealing with issues affected by digital sovereignty. Especially smaller companies expressed their interest in reinforcing digital sovereignty and promoting Swiss IT solutions. It also became apparent that the costs of sovereignty-enhancing measures did not play a decisive role for many companies, as digital sovereignty was frequently perceived as a basic component of security. From our findings, we derive detailed recommendations on actions companies should take to develop a so-called sovereignty-centered data governance strategy. Digitale SouverĂ€nitĂ€t ist ein Thema, das aufgrund zunehmender internationaler Krisen und Konflikte im europĂ€ischen und Schweizer Diskurs zunehmend an Bedeutung gewinnt. Hierbei spielt diese nicht nur fĂŒr Staaten und BĂŒrger eine wichtige Rolle, sondern zunehmend auch fĂŒr Unternehmen. Wir untersuchen in unserer Arbeit, wie die digitale SouverĂ€nitĂ€t im Kontext der Data Governance von Unternehmen wahrgenommen und bewertet wird. HierfĂŒr haben wir 16 qualitative Interviews mit Politikern, UnternehmensverbĂ€nden, Experten und Vertretern von grossen und kleineren Unternehmen durchgefĂŒhrt. Unsere Ergebnisse zeigen, dass das Wissen ĂŒber digitale SouverĂ€nitĂ€t noch rudimentĂ€r ist und viele Unternehmen keine speziellen Strategien in ihrer Data Governance zum Umgang mit dem Thema gefunden haben. Dennoch drĂŒcken viele Unternehmen aus, mehr fĂŒr digitale SouverĂ€nitĂ€t tun zu wollen. Besonders kleinere Unternehmen sind an Schweizer IT-Lösungen interessiert. Es zeigte sich auch, dass Kosten von souverĂ€nitĂ€tssteigernden Massnahmen fĂŒr viele Unternehmen keine massgebende Rolle spielten, da digitale SouverĂ€nitĂ€t oft als elementarer Bestandteil einer Sicherheitsstrategie wahrgenommen wurde. Aus unseren Ergebnissen leiten wir konkrete Handlungsempfehlungen fĂŒr Unternehmen in einem souverĂ€nitĂ€tszentrierten Data Governance Framework ab.
Counseling | Sociology
Psychotherapy in Unsettled Times: How Therapists Mediate Between Collective Crises and Personal Distress
Psychotherapy has long been critiqued for turning individuals inward and away from civic life. Drawing on 40 interviews with therapists in the San Francisco Bay Area, this article revisits this debate in the context of converging societal crisesâincluding global political unrest, climate-related disasters, and public health emergenciesâto examine how large-scale crises surface in therapy. I argue that therapists, themselves living through the same crises, navigate their role as mediators between collective crises and personal distress by moving clients immobilized by crisis toward restored functioning and, in some cases, more active engagement with the social world through four key phases of the therapeutic process: (1) validating crisis-related distress as a reasonable response; (2) stabilizing clients through co-regulation, coping, and containment strategies; (3) reorienting clients by linking distress to broader social conditions and clarifying values; and (4) mobilizing clients toward restored functioning or values-aligned social engagement, depending on their proximity to threat. The findings illuminate how mental health care is adapting under conditions of contemporary macro-level crises. More broadly, they challenge critiques of psychotherapyâs individualism by showing how therapists actively bridge the personal and the political in clinical practice.
Other Social and Behavioral Sciences | Political Science | Sociology
Pre-Framework Sustainability Governance: A Historical Analysis of Sheikh Zayed bin Sultan Al Nahyan's Sustainability Legacy, 1946â2004
The global sustainability narrative is structured around Western institutional milestones beginning in 1972, with recognition accruing to the architects of policy vocabulary rather than to pre-framework practitioners. This chronology has obscured governance traditions outside Western institutional settings. In this study, we examine the environmental, social, and economic governance of Sheikh Zayed bin Sultan Al Nahyan (1918â2004), founding father of the United Arab Emirates (UAE), through a retrospective sustainability analysis spanning 1946 to 2004. Employing a structured historical methodology, the study maps 58 years of documented policy actions to the 17 United Nations Sustainable Development Goals (SDGs), finding alignment with all 17 goals, beginning 41 years before the 1987 Brundtland Commission report first defined "sustainable development." The analysis introduces a critical distinction between "sustainability" as an intergenerational stewardship practice, originating with Carlowitz's 1713 forestry treatise, and "sustainable development" as an institutional policy framework established by the Brundtland Commission in 1987. The findings indicate that Sheikh Zayed's governance record, validated externally by three independent United Nations system awards, represents the earliest, largest-scale, and longest-duration integrated sustainability practice documented for a single head of state.
Environmental Studies | Science and Technology Studies
SCOPE: A Decision Framework for Evaluating the Sustainability and Ethics of AI Adoption
Evaluation tools for AI rarely address both ethical and environmental dimensions. This paper introduces SCOPE, a decision framework for assessing AI projects across five integrated dimensions: Sufficiency (Is AI necessary?), Carbon (What is the full environmental footprint?), Outcomes (Who benefits and who bears costs?), Power (Who controls the system?), and Endurance (Is the solution sustainable long-term?). A review of existing frameworks, spanning regulatory instruments, international standards, corporate tools, and academic proposals, reveals a structural divide: most address either ethics or environmental sustainability, but rarely both. The question of whether an AI system should be built at all (sufficiency) remains the most neglected dimension across the field. SCOPE integrates sustainability science and AI ethics into a single instrument, positions sufficiency as the foundational question, and requires explicit net impact assessment. The framework is designed for decision-makers evaluating AI adoption in organizational contexts, applicable before implementation decisions are made. This paper presents the framework's theoretical foundations, details each dimension with reference to current literature, compares SCOPE with existing frameworks, and discusses implications for research and practice.
South and Southeast Asian Languages and Societies | Linguistics
Preservation of regional languages continues to be carried out by local government, the use of the Balinese language is required to make everyone must to using Balinese Language. Not all Balinese people are able to use the excellent and correct Balinese language. Some words have a variety of meanings. The meaning studied in this study is the verb âminumâ, which has a context meaning carried by each lexicon. The data source of this study is the Balinese-Indonesian dictionary published by the Balai Bahasa Denpasar. Observation methods and note-taking techniques were used to collect data. The descriptive-qualitative method was used to analyse the data, and the informal method was used to present the data analysis results. This study uses the theory of Natural Semantic Metalanguage by Wierzbicka (1996). There are fifteen verbs with the meaning of âminumâ in Balinese which have a prototype of action with the default meaning of doing: towards and moving. The semantic structure of the verb meaning drink in Balinese has a syntactic pattern. Natural Semantic Metalanguage X does something to Y and something happens to Y.
Other Social and Behavioral Sciences | Sociology
Now as Then: The Construction of Structural Barriers to 'Right to Abode' for Racialised Commonwealth Migrants in Britain â A Rapid Review of Contemporary Oppositional Voices
This rapid review synthesises 17 sources from legal scholars, historians, and advocacy organisations to archive opposition to the legislative dismantling of the "right to abode" for racialised Commonwealth migrants in Britain. Tracing policy from 1948 universal subjecthood to the 2026 "earned settlement" reforms, the review documents a bipartisan project of exclusion through racially encoded mechanisms: partiality clauses, tiered citizenship, extended qualifying periods (now reaching 20 years), prohibitive costs (ÂŁ13,000+ per adult), and mandatory digital eVisas creating a "politics of exhaustion." Stated justifications mask actual drivers: electoral pressures, geopolitical realignment, and racialised public sentiment. The cumulative effect is "permanent temporariness" and "two-tier citizenship," with 1.35 million people facing retroactively applied rules.
Sociology
âThe Indicator of CCTV Success is Winning Electionsâ: Insights from the Implementation of an Algorithmic Video Surveillance System in Poland
This article explores the emergence and dynamics of institutional collaboration surrounding the implementation of an algorithmic video surveillance system (AVS) in a Polish city, utilizing the Advocacy Coalition Framework (ACF) as a theoretical lens. The study identifies two primary coalitions: the âSafe City,â focused on public safety and crime prevention, and the âSmart City,â which emphasizes technological innovation and city branding. Through qualitative case study method, including in-depth interviews, the research provides an empirical analysis of how cooperation unfolded among actors who are typically reluctant to work together. The paper argues that the systemâs success is owed to the convergent belief systems of the coalitionâs members. The findings also highlight the role of individual policy entrepreneurs, local authorities, law enforcement, and private contractors in engaging citizens in financing the CCTV system and reducing any opposing voices. Ultimately, the study contributes to understanding the interplay between politics and policy in the context of urban surveillance technology, while calling for further research on the implications of such systems for core components of the âright to the smart cityâ like privacy and democratic engagement.
Other Social and Behavioral Sciences | Psychology | Anthropology | Linguistics | Communication
The Wall Teaches the Rooms: Transduction, Equivalence, and the Cost of Cross-Interface Coordination
How do agents with radically different experiential repertoires achieve communicative coordination? This paper introduces a minimal analytical framework organized around two parameters and two protocol concepts: \textit{transductive equivalence} (TE), the degree of structural correspondence between configurations across distinct interfaces; \textit{transductive coupling cost} (TC), the informational burden required to achieve coordination across a mediating boundary; the \textit{transductive protocol} ($\Pi_{\text{trans}}$), the collectively maintained pattern of equivalences that channels coordination; and the \textit{exchange protocol} ($\Pi_{\text{ex}}$), the filtering properties of the mediating boundary itself. The framework is developed through a thought experiment---the Drywall Rooms---in which two agents, each confined to a soundproofed room, must communicate exclusively via vibrations transmitted through a shared drywall partition. The objects available in each room differ, yielding distinct vibratory profiles; communication thus requires establishing functional equivalences among materially dissimilar events. The paper's central claim is that different constraints produce different kinds of meaning, not less meaning: the mediating wall is not what stands between agents and communication but what makes communication a transductive achievement constituted by the boundary, not a co-perception degraded by it. Because transductive protocols require continuous enactment to persist, the TC/TE framework decouples shareability from stability, dissolving a persistent conflation in theories of meaning. The resulting analytical toolkit is applicable to sign language linguistics, bilingualism, translation, education, and the structural mechanisms through which asymmetric coordination costs are sustained at the institutional scale.
Economics | Organization Development
Beyond the Discount War: Strategy and Survival in Indiaâs Food Delivery Duopoly
Indiaâs online food delivery market has consolidated into a stable duopoly following the exits of Uber Eats and Amazon Food. Standard Bertrand competition predicts that such a market structure should result in aggressive price discounting and persistent margin erosion. However, the observed trajectory of Zomato and Swiggy diverges from this prediction. This paper argues that the Indian food delivery duopoly is better understood through the framework of Nash equilibrium and repeated game theory rather than static price competition. Drawing on financial disclosures, regulatory developments and strategic investments across adjacent verticals, the analysis shows that both firms have shifted capital allocation toward quick commerce and dining and entertainment services. These investments reduce direct confrontation in the core food delivery segment and function as a structural analogue to mixed strategy behavior. Instead of committing exclusively to price based competition, each firm distributes resources across multiple business lines, generating strategic unpredictability and limiting profitable unilateral deviation. The stability of this equilibrium is reinforced by public market discipline that constrains explicit coordination while allowing tacit adjustment. The paper contributes to the understanding of platform competition in emerging digital markets by demonstrating how vertical differentiation can stabilize outcomes in environments where pure price rivalry would otherwise destroy value.
Library and Information Science
Adaptive Infophilia: The Ethics of Information Power
This paper integrates Chris Bronk's information power framework with adaptive infophilia theory to explain how our evolutionary drive for information both empowers us and endangers us in the context of digital content and geopolitics. Using an interdisciplinary framework spanning physical, biological, and political dimensions, we supply the missing layers in Bronk's analysis and propose information weaponization as the central violation. We advance technical, educational, and ethical strategies to build resilience and empower wellbeing and flourishing. By combining political science insights with information behaviors and ethics, this paper advances a new principle for computing professionals: information shall not be weaponized.
Hypotheses on Baseball Decline Among Youth in Japan
Youth well-being has become an increasing concern in Japan in recent years. This study considers sports as a potential factor impacting the lives and psychology of young people and examines the long-standing and widely cherished sport of baseball in Japan. The study focuses on high school baseball, given that it has consistently attracted public attention across the nation. By analyzing publicly available data from the Japan High School Baseball Federation, this study examines trends such as declines in club membership, formation of combined teams due to a lack of players, and the overall decline of baseball among youth in Japan. Furthermore, it hypothesizes two potential causes for this decline: 1) increased diversity in sports and entertainment, and 2) the negative image associated with baseball. Therefore, this study contributes to the literature on youth well-being by documenting the current decline in baseball participation among young people and proposing hypotheses regarding its underlying causes.
Psychology
Validation of the Mandarin Chinese Version of the Detachment, Internalizing, and Somatoform Spectra of the Hierarchical Taxonomy of Psychopathology Self-Report (HiTOP-SR)
Wenqi Zhang, Peiyi Wang, Ran Liu, Chuansheng Chen, Zhaoxia Yu, Emily Baum, Michelle Chan, Y. Anthony Chen, Tannei Hong, Tianjiao Kong
The Hierarchical Taxonomy of Psychopathology (HiTOP) is a dimensional approach to understanding mental health, addressing limitations of categorical systems such as the Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD). This study aimed to validate a Mandarin version of the HiTOP Self-Report (HiTOP-SR), with a focus on the Internalizing, Detachment, and Somatoform spectra among a Chinese population. A translation and back-translation process was followed by collaborative item refinement from a team of bilingual and monolingual scholars to ensure both linguistic equivalence and cultural relevance. The final 213-item scale was administered to 1,999 undergraduate students across four Chinese universities, with follow-up assessments conducted five weeks later. The Mandarin HiTOP-SR demonstrated strong psychometric properties, including high internal consistency (α > .70 for 45 scales/subscales), good test-retest reliability (r > .70 for 32 scales/subscales), adequate model fit for 45 scales/subscales, and acceptable discriminant validity (only 13 pairs showed a latent correlation of > .90). Convergent validity was supported by strong correlations with corresponding DSM-5-TR symptom domains. These findings confirm the structural and conceptual alignment of the Mandarin HiTOP-SR with the HiTOP framework. This culturally informed adaptation advances the development of evidence-based, dimensional assessment tools in Chinese contexts and contributes to the global applicability of transdiagnostic models of psychopathology.
Psychology
The Role of Media Exposure in Youth Radicalization: A Multilevel Meta-Analysis
Jessica I. den Elzen, Jessica J. Asscher, Kyle M. Lang, Hanne Duindam
This preprint corresponds to an article that has now been published in a peer-reviewed journal and is available as open access. Please refer to and cite the final published version: den Elzen, J. I., Asscher, J. J., Lang, K. M., & Duindam, H. M. (2026). The association between media exposure and violent radicalization of young people: A multilevel meta-analysis. Aggression and Violent Behavior, 88, 102141. https://doi.org/10.1016/j.avb.2026.102141 Youth radicalization poses considerable risks to society, with notable concerns about the role that media exposure might play in this process. Despite adolescentsâ susceptibility to radicalization and their frequent online media use, previous reviews on media and radicalization have focused mostly on adults. To increase understanding of the association between media use and radicalization in youth (< 26 years old), a multilevel meta-analysis was conducted. In total, 26 studies were included, reporting on 25 independent samples (N = 49,552) yielding 141 effect sizes. A small overall effect of r = 0.13, indicated that media exposure is positively associated with radicalization in youth. The effect was stronger for vignettes/behavioral assessment methods of media exposure, online media exposure, and exposure to extremist content. These findings highlight the relevance of media exposure as a possible facilitator of radicalization processes in youth.
COVID-19 and the paradox effect of age in risk perception
In the rapidly growing research on risk perception in the context of the COVID-19 pandemic, little attention is paid so far to a frequently reported finding: older people estimate the risk of infection with the virus to be lower than younger people, while they are exposed to a greater health threat in the event of an infection at the same time. Our study aims to shed more light on this paradox effect of age in risk perception, both theoretically and empirically. Referring to the theory of cognitive dissonance, we argue that, taking the already early communicated age-dependency of the danger of COVID-19 into account, cognitive dissonance may emerge especially among the elderly. The easiest way to reduce this dissonance is to trivialize the dissonant cognitions by the devaluation of the risk of infection itself. This devaluation should increase with increasing dissonance, and thus with increasing age. We test our assumptions using the GESIS Panel Special Survey on the Coronavirus SARS-CoV-2 Outbreak in Germany, a rapid-response study on the effect of the pandemic on individualsâ daily life. Age is measured as metric variable, so that non-linear relations can be examined. We use stepwise linear regression models and control the effect of age on the perceived risk of infection according to pre-existing diseases, adapted behavioral measures, perceived threat, and sociodemographic characteristics. The results reveal an exponential, inverted U-shaped effect of age on the perceived risk of contracting the coronavirus, as theoretically expected. This effect is quite robust and indicates exponential trivialization due to exponentially growing dissonance with increasing age.
Political Science
Infrastructural Repression in Practice: the Politics of Electricity Cuts in post-2013 Egypt
Authoritarian regimes rely on the provision of services and infrastructure not only to secure legitimacy and co-optation, but also in order to manipulate them as a tool of coercion. This paper introduces the concept of infrastructural repression: the strategic disruption of essential services to raise the costs of mobilization. I fo?cus on one formâpunitive withdrawal, the short-term suspension of services following dissentâand develop the argument in post-2013 Egypt under Abdel Fattah al-Sisi. Linking a day district panel of protest events with satellite nightlight data capturing power outages, I show that anti-regime, politically framed protests are systematic?ally followed by localized electricity cuts, whereas routine protests over economic grievances are not. These effects are concentrated in Muslim Brotherhood-leaning districts, consistent with a strategy of targeting politically threatening constituencies. To identify these dynamics, I combine a within event study design, and stacked difference-in differences, with matching frontier and instrumental-variable approaches. Results consistently support the hypotheses. The findings show that infrastructures conventionally viewed as pillars of authoritarian legitimacy and co-optation can also act as tools of repression.
Development and validation of the Circular Behaviours Scale: A measure of householder behaviours for a circular economy
Kathryn Colley, Graciela MartĂnez SĂĄnchez, Jianyu CHEN, Phoebe Somervail, Alice Hague, Tami Wooldridge, Altea Lorenzo-Arribas, Tony Craig
Moving towards a circular economy will require substantial behavioural change on the part of members of the public, as well as in business models. However, robust tools for measuring individual-level behaviours contributing to the CE are lacking. This paper details the development and validation of the Circular Behaviours Scale (CBS), a self-report instrument designed to assess individualsâ propensity to engage in a broad range of circular behaviours, involving three separate studies. Study 1 reports a process of item generation, content validity assessment, initial item reduction and user testing. Study 2 applied Classical Test Theory and Item Response Theory to identify a 9-factor subscale structure and further reduce the number of items. Study 3 validated the final 34-item scale, confirming the factor structure and demonstrating convergent, discriminant, and known-group validity, with low social desirability bias. The CBS captures circular behaviours across a wide range of âRâ principles (e.g. refuse, reduce, repair, reuse, recycle) pertaining to the circular economy, and spanning all stages of consumption (from acquisition, to use, and disposal), offering a more comprehensive measure than existing instruments. It provides a valuable tool for researchers seeking to develop empirical and conceptual understanding of waste- and consumption-related behaviours, and for policymakers aiming to assess and encourage behaviour change as part of circular economy policy.
Science and Technology Studies
Bringing Citizen Science into Deliberative Democracy: Insights from Climate Citizensâ Assemblies
Julian Vicens, Ferran Bertomeu, Kyriaki Maria Fameli, Anna Maria Kotrikla, Amalia Polydoropoulou, Nil Alvarez, David Laniado
This paper explores the integration of citizen science into climate citizensâ assemblies as a pathway to democratise not only decision-making but also knowledge production. While citizens' assemblies enable citizens to deliberate on policy, they typically rely on expert-defined evidence, limiting participantsâ epistemic agency. Conversely, citizen science empowers lay publics to generate and interpret data but often lacks deliberative structures for collective reflection. We present the co-creation and testing of a Citizen Science Toolkit for Climate Assemblies, developed through participatory workshops in Living Labs and field deployments across two European climate citizens' assemblies, in Riga and Edermunde. Using mixed methods, including surveys, focus groups, and qualitative coding, we analyse participantsâ and organisersâ perspective. Results from those two assemblies show that integrating citizen science fosters knowledge uptake, citizen empowerment, and trust in the process, but also increases organisational demands. We argue that structurally embedding citizen science within deliberative formats expands the epistemic legitimacy of democratic innovation. The paper concludes with design principles for future citizens' assemblies and outlines a framework for citizen science as a climate adaptation governance tool.
Urban Studies and Planning | Economics | Public Affairs, Public Policy and Public Administration
Trade Associations and Lobbying for Roads: Funding, Strategies, and Discourses
Orly Linovski, Nicholas Klein, Amy Lee, Kelcie Ralph
The need for spending on roads and highways is largely unquestioned because the benefits of economic growth, reduced congestion, and increased jobs seem both self-evident and politically neutral. Yet, as we document in this report, this narrative benefits from the support of hundreds of lobbyists, millions of dollars in spending, and a collection of extensive and diverse strategies. This report focuses on one group involved in the road lobby â the trade associations and business organizations that stand to directly benefit from increased investment in road building, including contractors, building material and aggregate producers, and engineering companies. We find that trade associations spend heavily on lobbying and political campaigns, and they are often among the top spenders in their industry category. This results in hundreds of lobbyists working for trade associations, many with government experience, and millions of dollars donated to political campaigns and political action committees (PACs). The strategies used are diverse and extensive, including direct engagement with elected officials, mobilizing association members and grassroots advocacy, establishing expertise through âinformational lobbyingâ and research institutes, and funding programs to support lobbying at other levels. These resources are used to frame road building as critical to economic growth and job creation, worthy of support through increased spending and dedicated user fees as well as regulatory reform.
Political Science | Legal Studies | Sociology
Using digital trace data to study public sentiment toward the police. A demonstration case on the George Floyd killing.
In this paper, we assess a measurement approach to study sentiment toward the police using large-scale digital trace data and natural language processing (NLP). Existing research on the consequences of high-profile cases of police violence relies almost exclusively on surveys, which are often constrained by fieldwork timing, selective nonresponse, and limited temporal resolution. We test an alternative, easy-to apply, fully observational measurement strategy that uses YouTube Data Tools to collect millions of unsolicited public comments and applies a refined dictionary-based sentiment algorithm incorporating valence shifters to estimate attitudes expressed in police-related discourse. Using the killing of George Floyd as a demonstration case, we show how this approach yields high-frequency attitudinal indicators that closely mirror known temporal patterns from survey-based studies, including the immediate but temporary downturn in sentiment toward the police. Our analysis suggests that process-generated text from YouTube video comments can meaningfully broaden the methodological toolkit available to policing and criminology researchers. However, we stress that survey items and NLP-based sentiment scores capture fundamentally different constructs, and while the latter may be useful in some cases (e.g., facilitating rapid assessments of attitudinal dynamics), they are not a substitute for survey data.
Urban Studies and Planning
Beyond single destination access: a tour based analysis of proximity based planning in Melbourne
Proximity based planning has become an influential idea in urban policy, centred on the goal of meeting daily needs within short walking and cycling distances of home. However, most studies still assess access to single destinations, even though daily travel often involves linked tours rather than isolated trips. This paper develops a tour based perspective on proximity based planning and examines how daily activity patterns differ across Greater Melbourne. Using data from the Melbourne travel survey, we construct home based tours from full day travel diaries, classify them by destination structure, and estimate separate latent class models for weekdays and weekends. The results show that outer Melbourne is much more car dependent than inner Melbourne, while the overall structure of weekday and weekend tour patterns is more similar across the city. Car dominated tours increase from 49.5% in the inner ring to 79.9% in the outer ring, while walk dominated tours fall from 27.4% to 12.2%. The latent class analysis shows that similar weekday and weekend tour archetypes are found across inner, middle, and outer Melbourne, but are realised through different modes. Within the same classes, walking and public transport are more common in the inner ring, while car use is highest in the outer ring. These findings suggest that proximity based planning should not be assessed only by whether destinations are nearby, but by whether neighbourhoods allow people to combine daily activities without needing a car.
Legal Profession | Legal Studies
Inefficiency and Inequity of the Law Review Submission System
Where a legal scholar works shapes publication outcomes nearly as much as what they write. In the law review submission system---the primary publication market for legal scholarship in the United States---student editors face thousands of submissions for a handful of slots and rely heavily on institutional prestige as a proxy for article quality. We build a calibrated agent-based simulation of this market and benchmark it against deferred acceptance, a centralized matching algorithm used in markets like medical residencies. The simulation predicts severe misallocation: more than 60\% of top-tier placements differ from what centralized signal-based matching would produce, and the rank correlation between article quality and journal prestige is 0.45 versus 0.79 under centralized matching. Which system produces better placements overall depends on how many authors are competing for how many slots. As competition intensifies---a trend already underway---the current system's disadvantage grows, with the model predicting up to 13.4\% loss in match quality. Partial reforms like extending deadlines have negligible effects; in the simulation, the primary source of inefficiency is the decentralized structure of the market itself. The simulation also reveals that credential dependence produces inequity that persists even among articles of comparable quality: authors from prestigious institutions receive markedly better placements regardless of the matching mechanism. Centralized matching fixes the sorting problem but not this equity problem---prestige bias is embedded in editorial signals and would require changes to how articles are evaluated, not just how they are assigned.
Environmental Studies | Public Affairs, Public Policy and Public Administration
Imagining Decarbonised Futures: A Novel Integrative Methodological Framework
Net-zero commitments have become the dominant instrument of climate and energy governance. Hence, energy transitions are increasingly shaped by state-authored visions that project, stabilise, and legitimise visions of the future. Energy social science has developed rich discursive approaches to study conflicts around energy systems, infrastructures, and projects. However, it has paid comparatively less attention to two elements. The first is studying how comprehensive net-zero policy visions are constructed upstream â that is, before implementation and contestation unfold. The second is to combine different qualitative methods to address a single phenomenon. This paper addresses both gaps. It analyses net-zero governance as a formative site of political and symbolic work, where ecological limits, economic priorities, and technological assumptions are assembled into a coherent vision of transformation. The paper introduces an integrative qualitative framework for energy research. It combines discourse analysis, rhetorical analysis, and LLM-assisted interpretation. It shows its applicability using the Spanish governmentâs net zero policy commitments and their parliamentary contestations as a case study. The analysis shows that Spainâs net-zero governance operates through a politics of managed consensus, in which layered discourses and rhetorical performances absorb contestation while deferring to the future the more radical implications of ecological limits. The paper also responds to calls for methodological pluralism in energy research by demonstrating it in practice. Beyond the case study, the findings help explain why net-zero governance in Europe, while designed to build consensus, may itself generate the conditions for backlash.
Political Science | Public Affairs, Public Policy and Public Administration
Distinguishing Ecological Modernization and Ecomodernism. Environmental Policy Implications
Ecological modernization and ecomodernism assume that liberal democracies can address their ecological challenges. However, scholars seem to overlook that each rests on distinct theoretical assumptions and political programs. This paper compares the two approaches and analyzes their practical implications. Ecological modernization and ecomodernism embrace rationalist and reformist environmental politics to achieve absolute decoupling through Green New Deals. Ecological modernization calls for market-led precautionary innovation regulated by governments and supported by green consumerism. In contrast, ecomodernists advocate for state-driven proactionary and comprehensive innovation and are dismissive of demand-side policies. These differences point to three policy implications. First, the precautionary principle might need careful reconsideration to reconcile economic and environmental performance. Second, eco-innovation may require a stronger commitment from nation states to implement effective supply-side policies. Third, accelerated absolute decoupling requires promoting and setting rational consumption targets. Together, these implications involve dilemmas of technological and social innovation that liberal democracies should navigate to meet sustainability goals.
Political Science
Bounding Knowledge Decay From Agnostic Temporal Generalization
Causal generalization is essential to contemporary political science practice. We argue that recent methodological advances in causal generalization pay insufficient attention to issues which arise from generalization over time. For assumptions of varying degrees of strictness, we derive novel statistical bounds of the growing uncertainty of a given causal estimate into the future. We derive these bounds using the Wasserstein divergence which allows us to weaken assumptions of positivity which are not typically met in practice. In an empirical example, we demonstrate that actual variation in treatment effects over time tends to dominate reported statistical uncertainty. Once implicit and untenable assumptions about covariate distribution and conditional treatment effects are made explicit and relaxed, descriptive and causal knowledge are both essential for temporal causal generalization.
Political Science | Communication | Sociology
Using GitHub Actions for Computational Communication Research
Communication researchers increasingly use computational methods to collect and analyze large datasets. Part of the promise of these methods is their ability to increase the reproducibility and transparency of workflows. Taking up calls for more reproducible workflows and better recognition of the tools used in communication research, this paper introduces GitHub Actions for automated data collection. I describe the components required to set up and run a GitHub Actions workflow and illustrate its utility by discussing how I collected Bluesky posts tagged with "#CdnPoli" during the 2025 Canadian federal election. I conclude by offering best practices for other researchers, contributing to the development and documentation of reproducible workflows for computational communication research.
Armed conflict accelerates degradation while enabling passive regeneration in forests, land and rivers of Nigeria's Lake Chad territory
Environmental degradation in armed conflict zones is extensively documented worldwide. Yet gaps persist in disentangling the specific mechanisms of degradation from evidence of regeneration during active violence, particularly across forest-land-water resources. This knowledge is critical for distinguishing conflict actors' direct impacts from affected populations' survival responses, and for understanding the challenges and opportunities of ecological regeneration arising from depopulated conflict zones. Here, I focus on the Nigeria's Lake Chad territory, examining armed conflictâs transformations of forests, land and rivers from 2009-2025; the mechanisms linking combatants, security forces and displaced groups to these changes; and the extent to which displacement enables ecological recovery. I employ a multi-methods approach. First, I review newspaper reports, peer-reviewed literature and grey literature to develop a heuristic analytical framework linking armed conflict and environmental outcomes. This framework guides primary and secondary data collection: I gather primary data through focus group discussions, key informant interviews, and field observations during guided transect walks, while secondary data comprise event-level conflict records from the Armed Conflict Location and Event Data Project and high-resolution satellite imagery from Google Earth Pro. The results reveal (i) dual degradation mechanisms via direct militarisation by conflict actors and indirect insecurity-induced civilian extraction of natural resources amid disrupted environmental governance, and (ii) ecological regeneration in depopulated conflict zones where military cordons, abandoned farmlands and human absence enable fish stock recovery, fallow expansion and secondary bush regrowth. These findings advance conflict ecology by separating military destruction from civilian survival pressures while documenting regeneration amid ongoing violence â a potential peace dividend that is vulnerable to rapid reversal upon repopulation. Strategic action is therefore essential on two fronts: curbing degradation through targeted capacity-building in environmental governance; and harnessing regeneration by monitoring recovery trajectories in no-go zones around fishing, pastoral and farming areas showing signs of regeneration, and designating such zones as temporary protected reserves prior to reopening to secure short-term gains in fish stocks, fallow lands and bush regrowth against repopulation pressures.
Agentic Framework for Political Biography Extraction
Producing large-scale political datasets demands extracting structured facts from unstructured sources, traditionally relying on expensive human experts and resisting at-scale automation. This paper develops and evaluates large language model (LLM)-based solutions to this bottleneck, focusing on elite biographies, one consequential class of political facts. We propose a two-stage ``Synthesis--Coding'' framework: LLM agents first search, filter, and curate evidence from heterogeneous web sources, then map curated inputs into structured records. We validate the framework across Chinese, American, and OECD political elites, benchmarking performance against human baselines using multiple state-of-the-art LLMs. We find that LLM coders match or exceed human experts when given curated inputs, and that agentic synthesis substantially outperforms human collective curation (Wikipedia) in open-web environments. We further identify a systematic bias: directly coding from long, multilingual corpora degrades extraction quality, and demonstrate that the synthesis stage mitigates this bias by compressing evidence into signal-dense representations.
Bright but Poor. Undermatching in Post-Secondary Education
Florencia Torche, Alejandra Mizala, Alejandra Abufhele, Luis Herskovic
Educational undermatching identifies high school graduates who do not attend selective colleges even if they have high academic performance. To date, the study of undermatching is restricted to access to selective colleges and to the United States and the United Kingdom. We expand this concept to identify students who, having high academic performance, do not undertake five critical educational transitions: graduating from high school, enrolling in higher education, taking the college-entry exam, enrolling in university, and enrolling in a selective university. Using the case of Chile and a novel population-level panel dataset combining administrative and survey data, we find that undermatching is prevalent, highly stratified by SES, and stronger among disadvantaged boys than girls. A Gelbach decomposition analysis suggests that inequality in undermatching is largely accounted for by the studentsâ sorting across schools. We discuss the implications of undermatching for countries around the world.
We use an example to show that a distribution is asymmetric generally, suggesting that normal distribution is the simplest distribution without momentum. We define a distribution with momentum as a blended normal distributionâas if the underlying normal distribution is disfigured by, or blended with, momentum. We suggest that a variableâs movement over a period follows a distribution longitudinally, whereas the literature usually examines a variableâs population that follows a normal distribution cross-sectionally. Thus, we use the distribution of current observations to predict the likelihood that the variable falls within a specific range at a specific time. This study questions the fundamentals of statistics and econometrics.
Other Social and Behavioral Sciences | Psychology | Economics
Effects of engagement in arts and creative activities on internalising symptoms and life satisfaction in adolescence: Results of a causal analysis in the #BeeWell study
Samuel Hugh-Jones, Jessica Bone, Anna Wilding, Matt Sutton, Prof. Neil Humphrey, Luke Munford
Background: There is growing evidence of links between arts and creative activities and mental health, particularly in adolescents. However, methodologically stronger evidence is needed. Using causal inference methods, this study examined whether day-to-day arts engagement can improve adolescent mental health and wellbeing. Methods: The sample included N=13,058 (42.6% girls, 12-15y) individuals from the #BeeWell study, a longitudinal study of adolescents in Greater Manchester (UK). Inverse probability weighting with regression adjustment was used to assess the effect of engagement with six different arts and creative activities on subsequent internalising symptoms and life satisfaction, conditioning on baseline outcomes and covariates. Results: Engaging in any arts or creative activity several times or more a year led to increased life satisfaction. Going to the cinema or theatre (but not other activities) resulted in decreased subsequent internalising symptoms. Effects on both outcomes did not differ by the number of different activities young people engaged in or the frequency of engagement. No significant differences were observed across socio-economic status, gender, or ethnicity. Conclusions: Regular engagement with arts and creative activities can improve adolescent life satisfaction. Specific activities can reduce internalising symptoms. The absence of moderation effects across subgroups indicates these activities could confer universal benefit. Increasing opportunities to engage in arts and creative activities is an effective way to improve adolescent mental health and wellbeing without widening inequalities.
Political Science
A Natural Lab for Issue Voting: Calibrated Multi-Party Vote Prediction from Large-Scale German VAA Issue Batteries
Vote Advice Applications (VAAs) generate vast traces of political attitude data but only a subset of users self-annotate their intended vote, limiting downstream analysis. Using a large German VAA dataset with 31 issue items, I evaluate whether attitudes alone can predict party choice and produce calibrated probabilities suitable for auto-labeling unannotated VAA records as well as other survey style datasets. I compare multiple modelling techniques including a model evaluation and a gated approach (left-wing/right-wing prediction before party prediction) to maximize their predictive power under a stratified 60/10/30 split. Models are tuned on macro-F1 and calibrated on the validation set (isotonic). LightGBM attains the best test performance and excellent probability calibration, enabling aggregation of probabilities to user-base vote shares. Error structure aligns with known cleavages and wrong predictions mostly deviate towards politically close parties. Furthermore, the gated approach has a slight advantage in its predictive power yet yields worse predicted probabilities. Methodologically, I show that calibrated gradient boosting over attitude items alone yields reliable multiclass vote probabilities.
Political Science | Economics
Initial Dividend and Institutional Cycles: A Unified Analytical Framework for Institutional Replacement
Why do institutional replacements historically exhibit structurally similar patterns of rise and decline? This article proposes the concept of the "Initial Dividend" as the core driving mechanism of institutional cycles and constructs a four-stage cyclical model dividend release, distributive ossification, dividend exhaustion, and legitimation crisis leading to substitution-to universally explain institutional replacement across differing historical contexts. This article argues that whenever a new institution replaces an old one, the structural transformation releases a one-time surplus of resources or efficiency gains, defined here as the "Initial Dividend." The temporal nature of this dividend is the fundamental cause of institutional cycles: when the dividend is exhausted and the vested interest structures surrounding it obstruct adaptive reform, the institution enters a legitimation crisis, creating conditions for the next round of replacement. Through four sets of comparative historical cases- -Chinese dynastic cycles, the European transition from feudalism to constitutionalism, post-war decolonization state-building, and the neoliberal turn since the 1980s-this article empirically tests the theoretical framework and clearly defines its scope, boundary conditions, and falsifiable propositions.
Higher Education | Education Economics | Public Affairs, Public Policy and Public Administration
A Monte Carlo Simulation Framework for University Enrollment Strategy Under Marketing Uncertainty
Universities operate in increasingly uncertain financial and enrollment environments, yet evidence-based recruitment investment planning remains difficult because campaign-level data are often proprietary or unavailable. This study develops a decision-analytic framework for university enrollment strategy under uncertainty, integrating Monte Carlo simulation, econometric analysis, nonlinear optimization, and policy stress testing. The Enrollment Strategy Simulation (ESS) framework evaluates how alternative recruitment budget allocation ratios affect financial performanceâincluding return on investment (ROI), net present value (NPV), enrollment yield, and downside riskâacross a four-year discounted tuition revenue horizon. Using 10,000 replications per scenario, the analysis compares 5%, 10%, and 15% allocation ratios under stochastic variation in cost per lead (CPL), conversion rate (CR), and institutional costs. Expected ROI rises from â0.476 at 5% to 0.325 at 15%, with mean NPV turning positive at the 15% threshold. Regression results confirm that conversion rate is strongly positively and cost per lead strongly negatively associated with ROI. A risk-adjusted optimization procedure identifies approximately 19.3% as the optimal mean-variance allocation. Policy stress tests show that advertising cost inflation produces the largest deterioration in expected outcomes. The ESS framework provides a transparent and reproducible decision-support tool for enrollment investment planning when empirical institutional data are unavailable. All simulations were implemented in R, with replication code archived via GitHub and Zenodo. Keywords: Monte Carlo simulation, enrollment strategy, decision analytics, higher education finance, university budgeting, risk-adjusted optimization
Leisure Studies | Sociology
Holding Labor to Ac(count): Quiet Quitting and the Limits of the Anti-Work Imaginary
This article addresses debates over the emancipatory potential of counter-accounting by asking whether the co-optation of oppositional accounts signifies success or failure. It charts the interplay between official accounts and counter-accounts through a historical analysis of four waves of anti-work struggle, showing how activists alternately challenged â and failed to challenge â the dominant work ethic. It is found that partisans of antiwork consistently drew on problematic accounts, leaving them vulnerable to recuperation, reintegration, and, eventually, defeat. By adopting the official accounting apparatus of dominant institutions, these counter-accounts inherited the ideological biases of the truth regimes they sought to dismantle. Counter-accounts cohere and become intelligible only by indexing themselves to the prevailing order. Accounting practices that repurpose existing data for alternative ends will likely bear the imprint of the truth regimes that created them, leaving them open to co-optation. The analysis concludes by invoking the contemporary phenomenon of quiet quitting, highlighting both its resonances with earlier phases of struggle and its departures from past precedent. By withholding voice and withdrawing from the productivist mandate, quiet quitting points toward a latent strategy of refusal that resists the imperative to be made legible to the accounting gaze, thereby offering a potential path beyond the traps of counter-accounting.
Environmental Studies | Sociology
Climate Variability Shapes Miscarriage, Stillbirth, and Abortion
Exposure to climate variability is associated with pregnancy termination, yet no prior study has distinguished between induced and spontaneous termination. This study links reproductive calendar data to high-resolution temperature and precipitation records (N = 308,035 pregnancies) to provide a novel, trimester-specific assessment of climate effects on miscarriage, stillbirth, and abortion in South Asia. I find that temperatures during conception and early gestation increase the likelihood of miscarriage and abortion, while dry conditions elevate miscarriage risk. These effects are comparable in magnitude to established sociodemographic predictors of adverse pregnancy outcomes. Once social stratification is considered, however, divergent patterns emerge. Increased years of schooling protect women from spontaneous termination associated with heat and drought, and abortion responses to precipitation shocks are concentrated among the most highly educated women. Together, these findings demonstrate that climate variability operates within existing social hierarchies, shaping both physiological vulnerability and unequal reproductive agency, and reinforcing stratified patterns of fertility and pregnancy loss.
Full report: Scoping the feasibility of a new longitudinal birth cohort study of children at risk of poor outcomes across the UK
Lucy Griffiths, Grace Bailey, Rowena Bailey, Katie Harron, Richard J. Silverwood, Alissa Goodman, Alyce Raybould, Karen Dennison, Orla McBride, Jonathan Scourfield
This project explored the feasibility of establishing a new UK-wide longitudinal birth cohort study focused on children at risk of poor outcomes, particularly those likely to become involved with early interventions or childrenâs social care services. The project found a strong policy appetite and clear research need for a new longitudinal birth cohort study, capturing lifelong experiences of children at risk. Although challenging, the findings lead to three main study designs: enhanced recruitment of mothers (including those living in disadvantaged circumstances) whose children may be at greater risk, as part of a population-wide study; recruitment based on maternal health records to recruit mothers with recorded adversities within a defined period pre-birth; or a targeted study capturing children already involved in childrenâs social care. We detail sample size estimations and cost considerations. We also outline an alternative or complementary strategy through linkage to administrative records. This report includes findings in full - including methodology, all data tables, and discussion. A summary report is also available [CLS website link to be inserted].
Summary report: Scoping the feasibility of a new longitudinal birth cohort study of children at risk of poor outcomes across the UK
Lucy Griffiths, Grace Bailey, Rowena Bailey, Katie Harron, Richard J. Silverwood, Alissa Goodman, Alyce Raybould, Karen Dennison, Orla McBride, Jonathan Scourfield
This project explored the feasibility of establishing a new UK-wide longitudinal birth cohort study focused on enhanced recruitment and retention of vulnerable children at risk of poor outcomes, particularly those likely to become involved with early interventions or childrenâs social care services. The project found a strong policy appetite and clear research need for a new longitudinal birth cohort study, capturing lifelong experiences of children at risk. Although challenging (with the requirement for further governance and ethical considerations), the findings lead to three main study designs (recommendations): enhanced recruitment of mothers (including those living in disadvantaged circumstances) whose children may be at greater risk, as part of a population wide study; recruitment based on maternal health records to recruit mothers with recorded adversities within a defined period pre-birth; or a targeted study capturing observations and outcomes of children already involved in childrenâs social care. We also outline an alternative or complementary strategy through linkage to administrative records. This report provides a brief, accessible overview of the main findings. Readers are encouraged to consult the main report [CLS website link to be inserted] for the f indings in full including methodology, all data tables, and discussion. The project was funded by the Economic and Social Research Council (ESRC) under the Transforming Data Collections Infrastructure for Social Science initiative (Grant No. UKRI109). It brought together an interdisciplinary UK-wide team from Swansea University, University College London, Ulster University, Cardiff University and the National Centre for Social Research, supported by the Nuffield Family Justice Observatory.
Intergenerational Educational Mobility in Scandinavia and the United States
Jens-Peter Thomsen, Stefan B. Andrade, Florian R. Hertel, Max Thaning, Ăyvind N. Wiborg
Intergenerational educational mobility reflects a welfare state's ability to provide citizens with opportunities to climb the social ladder. Representing two distinct welfare state types, studies have contrasted mobility patterns in Scandinavia and the United States but have provided no consistent answer as to who achieves the highest level of intergenerational educational mobility. We conduct a meticulous examination of intergenerational educational mobility in Denmark, Norway, Sweden, and the United States for cohorts born between 1958 and 1987 using comparable operationalizations and methods and the best available data (administrative data in Scandinavia and eight surveys in the United States). We focus on methods that capture relative mobility. Across models, we find that inequality in Scandinavia is 20 percent to 30 percent lower than in the United States. A multiverse analysis, which can run a large number of models within a single framework, shows that our results are robust to alternative variable specifications.
Wigglers and the Willing: A Within-Subject Analysis of Inequality Concerns
Mariana Blanco, Francesco Bogliacino, Salvatore Nunnari, Pietro Ortoleva
People make pro-social choices, yet researchers still lack tools to quantify how much moral wiggle room individuals exploit or how strongly they trade off money against normative principles. We introduce a within-subject design that measures both. We employ three variants of the Modified Dictator Game: a Self-Other allocation, an Other-Other allocation, and a Plausible Deniability allocation. Each variant elicits a switching point x, where higher values signal greater self-interest. Comparing switching points across variants yields the extensive and intensive margins of moral wiggle room, the money-principle trade-off, and a choice-based taxonomy of types requiring no assumptions about utility functions. We run the experiment in Colombia (N=376) and the US (N=274), with conceptual replications in both countries (N=288 and N=353). A sizable share of participants exploit plausible deniability, though not a majority. The intensive margin remains small in dollar terms, especially in the US. The money-principle trade-off is economically meaningful, yet over 40% of subjects keep their allocation unchanged between the Self-Other and Other-Other settings. Our taxonomy classifies between 60 and 90% of subjects into four robust types. The ordering $x(PD)>x(SO)>x(OO) that would characterize our representative agent represents only 8% of subjects. Roughly one-third exhibit x(PD)=x(SO)=x(OO), a deontological pattern that survives the inclusion of filler tasks. The remaining two types split between genuine social preferences and subjects who posture as deontological.
Geography | Environmental Studies | Public Affairs, Public Policy and Public Administration
Displacement and Transport-induced Gentrification: What about informal settlements benefiting from accessibility improvements?
Transport-induced gentrification has been increasingly studied. Residential displacement is the primary concern underlying this. More recently, scholars have begun to explore this debate in informal settlements, as they have long been a housing solution for working-class people in the Global South. This paper further advances this debate by addressing a twofold objective. First, we wonder if gentrification can unfold in Latin American slums through the entry of slightly more affluent households. Second, we investigate whether the relocation of long-term residents can be considered market-driven displacements. To this end, we undertook a two-step approach that combined the comparison of Google Street View (GSV) images from different dates with a participatory workshop in a community impacted by a Light Rail Transit system (Fortaleza, Brazil). Our findings reinforce scholarly arguments that gentrification and displacement are two different and independent phenomena. This is because, despite finding no evidence of market-driven displacement, we find a few cases of low-income gentrifiers. For the Latin American theorization, this challenges the framing of gentrification as a conflict between antagonistic classes over space. Another contribution of our study concerns the spatial extent of transport-induced gentrification, as changes within the community were closely linked to regional restructuring processes.
Sociology
Visual Constructions of Attractiveness as Cultural Indicators in Online Dating: Differentiation Across Locations, Gender, and Sexual Orientation
This article examines patterned distributions of visual self-presentation in online dating across location, gender, as well asexuality, and asks whether interpretively reconstructed visual constructions of attractiveness can be used as scalable indicators for comparative cultural analysis. Grounded in the praxeological sociology of knowledge and a practice-theoretical understanding of habitus, Tinder images are treated as documents of tacit and conjunctively shared orientations through which attractiveness is anticipated and expressed in patterned visual practices under field-specific constraints. Based on abductive reconstruction and computational analysis of 73,206 images from 13,000 Tinder profiles across thirteen metropolitan locations, stratified by gender and sexuality, the study applies a typology of ten Constructions of Attractiveness (COA) and their patterned combinations as Repertoires of Attractiveness (ROA). Using correlation-derived distances, hierarchical clustering, and multidimensional scaling, the analysis reconstructs how ROA similarity relations are organised across geo-cultural location, gender, and sexuality. Results show that geo-cultural proximity is the dominant structuring dimension of self-presentation in online dating, while gender constitutes a strong global axis of differentiation whose configuration varies systematically across locations. Sexuality primarily modulates similarity within locations but to a lesser extent than gender. To assess their analytic viability as cultural indicators, the ROA-based similarity space is compared with the InglehartâWelzel cultural value dimensions as an established reference for cross-cultural ordering and shows strong structural correspondence, supporting their comparative adequacy for analysing cultural differentiation. The alignment is read as structural correspondence rather than validation, bringing reconstructive visual analysis into dialogue with established value-based approaches to cross-cultural comparison.
Economics | Communication
Strategic Recovery and Institutional Resilience in Digital Asset Exchanges: The Indodax Case Study and the S3-Resilience Model
This study examines institutional resilience and strategic recovery dynamics of Indodax following a cyber security incident in September 2024. The research aims to evaluate the effectiveness of the recovery process using the S3-Resilience Model framework, focusing on the interplay between operational speed, financial solvency, and public sentiment. This study employs a descriptive-analytical mixed-method case study approach, integrating both qualitative and quantitative data. Data were gathered from reconstructed market events, publicly accessible blockchain records, and official institutional disclosures. The analysis was conducted by applying the S3-Resilience Model conceptual framework, integrating three main pillars: Speed, Solvency, and Sentiment. Quantitative metrics such as the Crisis Shock Coverage Ratio (CSCR) and V-Shaped Recovery patterns in trading activity were used to validate the resilience indicators. The findings reveal a high degree of systemic resilience, evidenced by service restoration within 80 hours, significantly below the industry average. Transparency was maintained through the publication of Proof of Reserve amounting to Rp11.5 trillion with a CSCR of 34x. Market response remained positive, indicated by net positive fund inflows and a swift return to normal trading volumes. The Indodax case demonstrates that institutional resilience in digital asset exchanges depends on a balanced integration of technical readiness and transparent financial accountability. The study concludes that the S3-Resilience Model is a viable framework for managing systemic risks and maintaining market trust during high-impact cyber crises.
Family Law | Public Affairs, Public Policy and Public Administration
Title IV-D Performance Incentives and Shared Parenting Outcomes: A Policy Analysis
Title IV-D of the Social Security Act (1975) funds state child support enforcement through federal matching of administrative costs and performance incentives allocated from a capped national pool tied to five metrics. The program has been effective in increasing paternity establishment rates above 90% and generating more than $30 billion in annual collections. However, the structure of the incentive system could create financial pressures affecting custody policy and child support guideline design. The review considers the historical development of Title IV-D, the structure of its performance incentives, data from variations across states, and procedural critiques from legal scholarship. I assess policy options, considering their feasibility and potential impact on shared parenting arrangements. Recalibrating incentives and strengthening proportional support guidelines may better align program objectives with contemporary family structures. Keywords: Title IV-D, child support enforcement, family policy, shared parenting, performance incentives
Urban Studies and Planning | Economics
A review of Circular Economy and the Construction Sector in Ireland: Barriers and Enablers for Circular Economy Adoption
Fergal Stapleton, Lucia VĂĄzquez Mendoza, Edgar GalvĂĄn
Without immediate intervention, global warming will have devastating consequences on the environment for future generations; as such, there is an urgent need to adopt more sustainable economic practices like the Circular Economy (CE). Although several policies and regulations support this goal, such as the European Green Deal, Ireland consistently ranks among the poorer-performing countries in CE adoption. One of the Irish sectors that contributes the most to this is the construction sector, where the built environment constitutes 30-40% of Greenhouse Gas (GHG) emissions. With this in mind, a comprehensive synthesis of the diverse range of barriers and enablers to CE adoption is crucial for developing targeted strategies to improve Irelandâs CE performance and contribute effectively to the sustainability goals. This study comprehensively analyses CE and the built environment in Ireland, drawing from impactful articles, white papers, and reports. This study reveals that key barriers to CE adoption in Irelandâs built environment include pervasive issues in material and waste management, leading to a high material footprint, low Circular Material Use Rate (CMUR), and inadequate recycling of Construction and Demolition Waste (CDW). Critical policy and regulatory shortcomings were identified, particularly the insufficient focus on Whole Life Carbon (WLC) assessment and practical support for Design for Disassembly (DfD). Furthermore, the digitalisation necessary to underpin CE is significantly hampered by a lack of integrated data frameworks, skills gaps, and clear standards. Crucial enablers identified involve strategic policy reforms to stimulate secondary material markets and mandate WLC, the advancement of digital tools such as Building Information Modelling (BIM) for CE and shared material databases, and fostering widespread adoption of DfD principles alongside targeted decarbonisation strategies appropriate for the Irish context.
Pathbreak: A Biodiversity-Food-Governance Game as a laboratory for re-imagining biodiversity governance
Ilkhom Soliev, MichaĆ PajÄ k, Maryna Bykova, Marco Janssen
Biodiversity loss is fundamentally driven by collective-action dilemmas, yet tools making these complex trade-offs tangible remain scarce. We introduce Pathbreak: A BiodiversityâFoodâGovernance Game, an experiential laboratory for re-imagining biodiversity governance, developed drawing on over a decade of experience. Moving beyond stylized models, Pathbreak integrates first-order dilemmasâagricultural yields versus ecosystem resilienceâwith second-order challenges such as political legitimacy, trust, and intersectionality. Through qualitative analysis of debriefings from five pilot studies involving participants with a range of knowledge about biodiversity (n=50), we demonstrate the efficacy of the game as a proof-of-concept boundary object. The study shows that participants engage with economic trade-offs alongside deeper dynamics of power and policy time-lags. Despite tensions between playability and ecological realism, Pathbreak acts as a catalyst for transformative, transdisciplinary learning. This framework effectively bridges the gap between biodiversity science and the societal transformations required to reverse ecological decline.
Psychology | Sociology
Dynamics of Social Cohesion in Diverse Groups: A Wave-Interference Model of Social Processes
This study develops a continuous structural model of group cohesion based on an interference framework. Whereas many influential approaches in diversity research focus on categorical subgroup distinctions, the present approach represents heterogeneity as dispersion of cohesion-relevant orientations within a shared interaction space. Simulation results reveal robust structural regularities across parameter ranges. Increasing diversity reduces the amplitude of cohesion dynamics without altering their functional form, and the optimal group size remains largely invariant. Structural adjustments such as resizing provide only partial compensation for dispersion-related attenuation. Most notably, the required regulatory scaling exhibits nonlinear threshold dynamics: intervention demand increases discontinuously and displays plateau regions that remain stable across group sizes. These patterns emerge endogenously from the interference structure of the model and highlight nonlinear scaling relationships that remain implicit in categorical accounts.
Environmental Studies | Leisure Studies | Organization Development
ENACTING CLIMATE ACTION IN DESTINATION GOVERNANCE: Effectual reasoning, intrapreneurial work, and enabling conditions
We examine how sustainability managers in destinations enact climate action. Drawing on data from European destination managers, we analyse the interaction between effectual decision-making, intrapreneurship, and enabling contextual conditions. Managers use effectual reasoning to make progress under uncertainty and translate this into intrapreneurial practices that mobilise others, reshape priorities, and coordinate action across fragmented destination systems. Whether these efforts can be sustained and scaled depends on institutional, relational, and culturalâcognitive embeddedness, which provide legitimacy, access to partners and expertise, and shared understandings that normalise collaboration and climate responsibility. By integrating effectuation and intrapreneurship into tourism governance, this study offers a process-oriented explanation of how destination organisations move beyond symbolic commitments toward more substantive climate action under conditions of constraint.
The time course of local coherence effects in German: Evidence from self-paced reading times and event-related potentials
In sentences like âThe coach smiled at the player tossed a frisbee,â the string âthe player tossed a frisbeeâ cannot be an active subject-verb-object (SVO) clause given the preceding context; yet, comprehenders seem to entertain this incorrect parse, at least momentarily. Behaviorally, this momentary mis-parse is expressed as greater difficulty when the SVO chunk is read. This phenomenon, called local coherence effect, has important implications for sentence processing theories that treat grammar as a strict filter during incremental sentence processing: Under such a strict filter, local coherence effects should never occur. Although several studies report the existence of local coherence effects, one question remains unanswered: at what moment are local coherence effects triggered, and how quickly â if at all â does grammar override the mis-parse? We investigate the time course of local coherence effects through two experiments in German (self-paced reading and EEG). Our data suggest that the local coherence effect, indexed by longer reading times and a more positive P600, was triggered as soon as the locally coherent chunk was read. However, the locally coherent parse did not linger; it did not continue to cause processing difficulty. The model that our results are most compatible with is self-organized parsing. Our results are compatible with self-organized parsing and versions of good-enough processing. Our results do not support accounts in which local coherence effects are caused by uncertainty about previous input or by a complete breakdown of algorithmic parsing. A broader implication of our findings is that although grammar is not a strict a-priori filter, it can step in rapidly to correct incremental structure building.
Dodo bird verdict: Verbal modeling, counterconditioning, and operant conditioning are effective in nocebo hyperalgesia attenuation
Pain Research Group, Daryna Rubanets, Izabela Ćaska, Joanna KĆosowska, PrzemysĆaw BÄ bel, ElĆŒbieta A. Bajcar
Nocebo hyperalgesia, the increased pain following inert interventions, is frequently observed in clinical practice. The limited research has focused on methods of attenuating this effect. The current study investigates whether nocebo hyperalgesia can be reduced through counterconditioning, verbal modeling, and operant conditioning. Healthy volunteers (N=168) were randomly allocated to three experimental and two control groups. In the experimental groups, nocebo hyperalgesia was induced via classical conditioning by applying high-intensity pain stimuli with a placebo and low-intensity pain stimuli without a placebo. In the control groups, sham conditioning was implemented (the relation between pain intensity and placebo was non-contingent). Nocebo hyperalgesia was then attenuated by 1) counterconditioning (low-intensity pain stimuli with a placebo, and high-intensity pain stimuli without a placebo); 2) verbal modeling (moderate pain stimuli with and without a placebo, with pain ratings provided by others suggesting less pain with placebo); 3) operant conditioning (moderate pain stimuli with and without a placebo, and participants were rewarded when experiencing less pain with placebo). In one control group, sham conditioning was continued; the other group received no manipulation. Classical conditioning induced nocebo hyperalgesia. All three learning procedures effectively attenuated the nocebo effect with no difference in their effectiveness. Expectancies changed similarly to pain ratings. The induction of nocebo hyperalgesia was fully mediated by expectancies. The current study demonstrates that nocebo hyperalgesia can be attenuated by verbal modeling, counterconditioning, and operant conditioning. Our findings suggest that healthcare workers may have flexibility in selecting nocebo-attenuating procedures when considering the treatment context or patient preferences.
Communication
Beyond the Laboratory: Introducing High-Throughput Communication Science
To examine causal mechanisms specified by theory, communication researchers draw on a diverse methodological toolkit (e.g., surveys, experiments, computational methods). These tools, however, are often implemented in isolation and yield results that are difficult to integrate. Here we propose high-throughput communication science, an integrative agenda that combines rich, temporally sensitive, and ecologically valid multimodal data streams with Marr's tri-level framework to reveal multilevel and reciprocal causal dynamics inherent to communication theories. Accordingly, we offer a roadmap for empirically implementing high-throughput communication science and highlight the broad utility of this approach across multiple communication subfields. In doing so, we map a path forward that better captures the complex, multilevel, and reciprocal causal mechanisms inherent to human communication.
Psychiatry and Psychology
Sexual Harassment, Sexual Violence, and Mental Health Outcomes: Causal Inference with Ambiguous Exposures
Social exposures and their impact on mental health has proven hard to capture, partly owing to the complex and multifaceted nature of the social reality. Sexual harassment and sexual violence (SHV) are no exceptions. SHV can be conceptualized as a continuum of negative sexual experiences whose severity varies depending on multiple determinants (type of SHV, frequency, power relations, etc.). Further, exposure to SHV may be conceptualized either as discrete exposures (i.e., experiences of specific SHV events) or as exposure to a sexually hostile environment, often represented by a latent variable reflected by patters of SHV events. With any of these conceptualizations, SHV constitutes a broad construct containing many kinds of negative experiences. The ambiguity of SHV pose a challenge when attempting to determine its mental health consequences, as different forms of SHV may vary in terms of their mental health impact. In this article we use the potential outcomes framework to discuss the conceptualization of SHV in relation to mental health outcomes, focusing on the consistency condition. We discuss limitations and possible interpretations of estimates of the causal effect of SHV on mental health, both when SHV are conceptualized as discrete exposures and when conceptualized as one or several latent variables. We present the recently developed multiple versions of treatment theory and show how it can provide a formal interpretation of causal estimates under ambiguous exposures. Lastly, we provide suggestions on how the increase the clarity and interpretability of estimates of the effects of SHV on mental health, by increasing the precision of the causal questions and the use of more specific definitions of SHV exposures.
Sociology
Cultural Capital as a Fundamental Health Resource: Evidence from a Life-Course Analysis
Socioeconomic health inequalities persist across the life course, yet research on their determinants has largely focused on material resources and conventional indicators of socioeconomic status. Drawing on Bourdieuâs theory of cultural capital and the sociology of health, this study examines whether cultural resources acquired in childhood constitute an overlooked mechanism in the intergenerational transmission of health inequalities. Using data from the U.S. Health and Retirement Study (1992â2020) combined with the Life History Mail Survey (N = 14,905), the analysis employs structural equation modeling to assess how childhood cultural capital shapes health outcomes in later life. The model integrates childhood socioeconomic status, childhood health, educational attainment, adult socioeconomic position, and adult health trajectories within a life-course framework. Results indicate that childhood cultural capital is significantly associated with better health in older age, even after accounting for childhood conditions, education, wealth, occupational status, and prior health. The total association operates through both indirect pathways, primarily via education and subsequent socioeconomic attainment, and a substantial direct pathway not fully explained by these mediators. Although childhood health remains the strongest predictor of later-life health, the findings suggest that cultural resources acquired during early socialization represent an independent and enduring influence on health trajectories. These results highlight the importance of incorporating cultural capital into life-course models of health inequality.
The Bildung Climate School: eco-anxiety outcomes of an inclusive sustainability educational program
This study examines the eco-anxiety impact of the Bildung Climate School (BCS), a twelve- week environmental education program in the Netherlands that integrates students from vocational (MBO), applied sciences (HBO), and research university (WO) education. Using mixed-methods education action research, we evaluated eco-anxiety outcomes among 22 participants in the program's second pilot iteration through pre- and post-program surveys, and pre- and post-qualitative interviews analyzed through deductive thematic analysis. The aggregated quantitative results showed non-significant trends toward increased eco- anxiety. However, disaggregating the analysis showed divergent patterns: university students' eco-anxiety increased significantly, while for vocational students the patterns were non-significant. The qualitative results suggest that the increase in eco-anxiety likely followed from increasing university studentsâ sustainability knowledge while decreasing their (techno)-optimism about the future. Though their eco-anxiety increased, most felt engaged or empowered to take action by the end of the BCS. MBO students consistently demonstrated greater baseline empowerment and action-oriented resilience, challenging the deficit framing of vocational education in the Netherlands. Our study aligns with literature framing eco-anxiety as a rational response to a real threat, offering avenues to increase student resilience through a vocational understanding of the âheads, hands, heartsâ framework in environmental education. We close on insights into the contributions of vocational education to environmental education research, aligned with the Bildung tradition, while suggesting potential mitigating strategies for the negative consequences of developing experimental interventions that could increase student eco- anxiety.
Political Science | Agricultural and Resource Economics | Environmental Studies | Social Statistics
Disasters and Discourse: How Newspaper Framing Shapes the Political Salience of Climate Change
How do newspapers frame extreme weather events (EWEs), and does framing differ systematically by event type? Extreme weather attribution is a rapidly growing field of climate science, yet media coverage often diverges from scientific understanding, shaping public perceptions of whether EWEs are human-induced crises or naturally occurring phenomena. This paper presents a corpus-based computational text analysis of approximately 18,000 articles published in The Guardian between 1997 and 2022, covering hurricanes (n â 10,000) and droughts (n â 8,000). We test the null hypothesis that there is no difference in narrative framing of different extreme weather events in relation to climate change. Using a six-category theory-driven keyword occurrence matrix covering climate change attribution, severity and damage, social inequality, policy response, emotional and psychological responses, and knowledge discourse derived from IPCC attribution research, we compare framing patterns across the two corpora. We find strong grounds to reject the null hypothesis: drought articles are more frequently framed in terms of climate change attribution and human causation, while hurricane coverage is more strongly associated with economic damage framing. These asymmetries have significant implications for the political economy of climate information, public risk perception, and the governance of climate adaptation.
Social Statistics | Sociology
Survival Loops: Refugee Coping Strategies in Protracted Crises
Melati Nungsari, Kirstine Rahma Stroeh Varming, Shre Maha Manohar
Refugees living in contexts of protracted displacement face overlapping and recurring crises that extend beyond the initial experience of forced migration. This article examines how refugees in Malaysia navigate such crises while living under conditions of legal precarity, economic marginalization, and social exclusion. Drawing on longitudinal qualitative interviews with refugee community leaders conducted across four rounds between 2020 and 2022, the study identifies 32 distinct coping mechanisms employed in response to external shocks and everyday structural constraints. These mechanisms are grouped into five categories inspired by Lazarus and Folkmanâs stress-coping framework: problem-focused, emotion-focused, meaning-focused, social-support-based, and maladaptive coping. The analysis shows that while many coping strategies provide temporary relief and demonstrate considerable agency within refugee communities, structural barriers significantly limit their long-term effectiveness. Legal exclusion, restricted access to formal employment, and social marginalization shape the range of coping strategies available and often prevent adaptive responses from translating into sustained improvements in wellbeing. To capture this dynamic, the article introduces the concept of a âsurvival loop,â a cycle in which crises trigger coping responses that alleviate immediate pressures but ultimately reproduce vulnerability over time. By situating coping strategies within the broader structural conditions of protracted displacement, the study contributes to crisis and refugee studies by highlighting the limits of resilience-focused approaches and emphasizing the importance of structural interventions in shaping long-term wellbeing.
Geography | Sociology
Turnover in changing urban landscapes: a demographic perspective of diversity at the submunicipal level
In recent decades, migration has played an increasingly central role in population change amid very low fertility and mortality, accelerating population turnover resulting in an unequal increase of diversity across territories and generations, accelerating demographic metabolism, the generational succession driving social change. Residentsâ perceptions of these fast changes have been instrumentalized by longstanding conspiracy theories, crystallizing in what is known as the âGreat Replacementâ. This paper counters such narratives by analysing these demographic processes through the case study of three Spanish Mediterranean cities. We measure these demographic dynamics at sub-municipal levels and across cohorts, assessing diversity not merely as the accumulation of origins but as the relative balance between groups. Results show that in a context of rising inequality and job insecurity for both natives and migrants, fast demographic changes, rather than ethnic replacement, reflect complex population dynamics shaped by cohort structures, local socioeconomic conditions, and urban migration histories. Replacement theories capitalize on negative perceptions of demographic change, attributing it as the cause of public discontent over rising inequality. Exposure to diversity is highest in younger âemptyâ cohorts and economically vulnerable areas: neighbourhoods shaped by twentieth-century internal migration and central areas undergoing gentrification.
Bad Health, Bad Jobs, But for Whom? Health Status, Gender, and Sorting Into Precarious Work
Extensive research has documented the adverse health consequences of precarious work schedules. Far less attention has been paid, however, to whetherâand for whomâhealth status may sort workers into precarious work. Using panel data from the National Longitudinal Survey of Youth 1997 and cross-lagged panel models with individual fixed effects, this study examines the bidirectional relationship between schedule precarity and health, along with potential gender differences. Our findings challenge the prevailing view that precarious work primarily causes poor health. While we observe some evidence of deteriorating health following exposure to precarious schedules, our longitudinal analyses accounting for temporal ordering point more strongly to health-based selection: individuals in poorer health are disproportionately sorted into precarious work, likely due to employer perceptions of diminished reliability and lower entitlement to schedule autonomy. The feedback loop in which poor health increases exposure to precarious work, thereby compounding health risks, is disproportionately concentrated among women, who already face structural disadvantages in employment. To account for this gendered health penalty, we extend sociological queuing models by theorizing a matching process, where workersâ preferences for stable, autonomous schedules (job queue) intersect with employersâ preferences for âideal workersâ (labor queue); the interaction of gender and health signals within the labor queue positions women in poor health at the bottomâperceived as less reliable and less deserving of schedule flexibility and autonomy. By uncovering a bidirectional, gendered dynamic between health and work precarity, this study highlights an important yet underrecognized mechanism through which labor market inequalities are (re)produced.
Science and Technology Studies
Strengthening Croatian-UK Research Ties through Network, Collaborations and Initiatives for Scientific Diaspora
This study examines the motivations, experiences, and collaborative engagements of Croatian researchers in the United Kingdom with their counterparts in Croatia. Utilizing a questionnaire answered by 40 Croatian scientists in the UK, the study investigates motivations for relocating, the nature and extent of their scientific collaborations, and their perceptions of research environments in both countries. Results indicate a strong desire for increased collaboration despite significant challenges such as a lack of institutional support, a clear information gap, and networking opportunities. The majority of researchers left Croatia before they managed to form connections with potential collaborators, thus infrastructure and opportunities for forming such networks are needed. The study also discusses the impact of the "Map of Croatian Scientists" project, highlighting its potential to foster networking and improve collaborative ties. Moreover, ideas and recommendations coming from researchers themselves are listed and include increasing awareness of research opportunities and funding, as well as facilitating better connectivity within the Croatian scientific diaspora through networking events. Through these insights, the paper contributes to understanding how transnational scientific networks can be more effectively nurtured to benefit both the researchers, scientific progress and innovation.
Psychology
Influence of Stepped Support on Older Adultsâ Internet Insomnia Intervention Engagement and Outcomes
Kelly Shaffer, Katharine E Daniel, Philip Chow, Karen Ingersoll, Lee M. Ritterband
Background: While delivering care by the Internet holds substantial potential to increase access to behavioral insomnia treatment, sustaining user engagement is considered a challenge. Minimal human support may enhance intervention engagement and efficacy, and older adults may particularly benefit from additional support for otherwise self-directed Internet interventions. Objectives: Test whether a human-delivered stepped support protocol improves engagement and outcomes using a fully-automated cognitive-behavioral therapy for insomnia program tailored for older adults (Sleep Healthy Using the Internet-Older Adult Sufferers of Insomnia and Sleeplessness [SHUTi-OASIS]). Methods: Adults aged 55 and older with insomnia (N=207) were randomized to receive SHUTi-OASIS alone or with stepped support (SHUTi-OASIS+SS). SS could be activated at intervention Core 1 or Core 2 (of six total Cores) if a participant had not completed the Core within two weeks of it becoming available. Engagement metrics were tracked by the Internet intervention platform. Participants self-reported insomnia outcomes by survey and prospective online sleep diaries at baseline, post-9 week intervention period, post 6-months, and post 12-months. Results: There was minimal activation of stepped support (14 of 102 SHUTi-OASIS+SS participants). There were no consistent differences in engagement or insomnia outcomes found when comparing SHUTi-OASIS versus SHUTi-OASIS+SS participants, nor when comparing only low-engaging participants across each condition (n=15 SHUTi-OASIS versus n=14 SHUTi-OASIS+SS). Conclusions: In this trial, most older adults engaged with the Internet intervention as instructed without the need for human support. Findings highlight the utility of highly-engaging Internet interventions for addressing older adultsâ healthcare needs.
Linguistics
Gender Bias in Nepali-English Machine Translation: A Comparison of LLMs and Existing MT Systems
Bias in Nepali NLP is rarely addressed, as the language is classified as low-resource, which leads to the perpetuation of biases in downstream systems. Our research focuses on gender bias in Nepali-English machine translation, an area that has seen little exploration. With the emergence of Large Language Models(LLM), there is a unique opportunity to mitigate these biases. In this study, we quantify and evaluate gender bias by constructing an occupation corpus and adapting three gender-bias challenge sets for Nepali. Our findings reveal that gender bias is prevalent in existing translation systems, with translations often reinforcing stereotypes and misrepresenting gender-specific roles. However, LLMs perform significantly better in both gender-neutral and gender-specific contexts, demonstrating less bias compared to traditional machine translation systems. Despite some quirks, LLMs offer a promising alternative for culture-rich, low-resource languages like Nepali. We also explore how LLMs can improve gender accuracy and mitigate biases in occupational terms, providing a more equitable translation experience. Our work contributes to the growing effort to reduce biases in machine translation and highlights the potential of LLMs to address bias in low-resource languages, paving the way for more inclusive and accurate translation systems.
Political Science
Do Municipal Voters Punish Partisan Candidates? Evidence from a Newly Partisan Municipal Election
Jack Lucas, R. Michael McGregor, Feodor Snagovsky, Jared Wesley
While political parties structure competition in national elections, many municipal systems operate without party cues, often reflecting widespread public opposition to local partisanship. It is unclear, however, whether municipal voters would actually punish candidates for affiliating with political parties if given the opportunity. We study this question using Calgaryâs 2025 municipal election â the first held after provincial legislation imposed formal parties on a historically nonpartisan system. Drawing on two large surveys fielded before and during the election, each embedding an identical conjoint experiment, we combine causal forest estimation of heterogeneous treatment effects with observational vote choice models to trace the party affiliation penalty from experimental estimates through to real electoral behavior. We find that voters impose a meaningful penalty on partisan candidates that grows rather than fades over time. This penalty is highly uneven: it is concentrated among citizens with strong anti-partisan attitudes and those who hold negative views of the provincial governing party that introduced the reform, suggesting that reactions to municipal parties reflect a mix of sincere anti-partisan commitments â the stronger channel â and conditional responses to the government responsible for the change. Experimentally estimated propensities to punish partisan candidates predict actual vote choice, confirming that anti-partisan sentiment shaped real electoral outcomes. These findings indicate that opposition to municipal parties reflects genuine normative commitments to independent local governance â commitments strong enough to resist accommodation under real electoral conditions â and help explain why nonpartisan equilibria prove so difficult to dislodge.
Political Science | Economics | Sociology
Miten saada osaavia maahanmuuttajia Suomeen?
Maria Vaalavuo, Ohto Kanninen, Hannu Karhunen, Timo Kauppinen, Jeremias Nieminen, Hanna Pesola
Tutkittuun tietoon perustuva maahanmuuttopolitiikka vahvistaa suomalaisen yhteiskunnan taloudellista ja sosiaalista kestÀvyyttÀ: pÀÀtöksiÀ voidaan tehdÀ arvioimalla eri politiikkavaihtoehtojen vaikutuksia luotettavan tiedon, ei mielikuvien, pohjalta. TÀssÀ policy briefissÀ pohdimme, kuinka maahanmuuttopolitiikkaa voitaisiin ohjata suuntaan, joka hyödyttÀisi suomalaista yhteiskuntaa ja maahanmuuttaneita parhaalla mahdollisella tavalla. Keskitymme siihen, kuinka Suomeen voidaan saada osaavaa työvoimaa. Uutta tietoa toimivista politiikkatoimista tarvitaan jatkossakin, joten hahmottelemme idean kokeiluksi.
The Relationship Between Indoor Environmental Conditions and Personnel Well-Being in Healthcare Facilities: A Narrative Review and Practical Recommendations
Indoor Environmental Quality (IEQ) in healthcare facilities influences personnel well-being, yet staff are frequently exposed to environmental conditions that are less than optimal. This narrative review synthesizes current evidence on three key IEQ factors â noise, thermal comfort, and lighting â and their psychological and physiological impact on healthcare workers. Hospital noise levels often exceed recommended limits and are associated with annoyance, stress, and cardiovascular activation. Thermal conditions are frequently perceived as too warm for staff, although both heat and cold can elicit stress responses. Adequate and appropriate lighting supports circadian regulation, alertness, and performance, particularly for shift workers. For each domain, the review outlines practical recommendations for sensor-based measurement in healthcare facilities. Together, these insights underscore the importance of integrating environmental monitoring into strategies aimed at improving the well-being of healthcare personnel.
Political Science | Public Affairs, Public Policy and Public Administration
The Death of Policy Process Theories? Agenda-Setting in the Age of Machines
The Multiple Streams Framework, Punctuated Equilibrium Theory, the Advocacy Coalition Framework, and the Narrative Policy Framework rest on five tacit premises about political information so self-evident when the theories were formulated that they were never explicitly stated: that political information is human-produced, filtered by identifiable gatekeepers, reflective of authentic public opinion, distinguishable from noise, and anchored in verifiable events. However, a radical transformation of the informational ecosystem completely upends these premises: machines â AI and LLMs â now produce political information indistinguishable from that produced by humans. As a consequence, this article argues that the canonical theories are, in the Kuhnian sense, dying. Through agenda-setting, where the four theories converge, it shows that their core mechanisms lose the substrate on which they were built to operate. It proposes a new Epistemic Policy Process (EPP) theory based on three dimensions to circumscribe the conditions under which the classical theories can still hold, and maybe stay alive.
Communication
Connected for Change: Insights into the in-group communication of the German Climate Movement on Telegram
In-group communication is crucial to the success of social movements. Effective communication among the in-group via social media enhances information dissemination, facilitates protest organization, and fosters internal cohesion as well as a strong sense of identity within the movement. While previous research has examined various platforms, Telegram has recently attracted attention due to its emphasis on privacy and its versatile communication capabilities. Notably, scholarly interest in Telegram has primarily centered around far-right and fringe groups. However, it is also widely used by diverse social movements, including the climate movement. This study aims to extend research by exploring in-group communication within the German climate movement on Telegram. To this end, I gathered data from the five most prominent groups resulting in a data set of 464,699 messages stemming from 277 publicly accessible Telegram channels and groups. I use LLM-based automated content analysis and social network analysis to investigate both the communication content and structure among climate movement actors. Results show that the German climate movement maintains a robust communication structure which interconnects the individual groups into a common network. Messages strongly focus on three primary activities: sharing information, sharing identity, and promoting action. Furthermore, the network reveals pronounced small-world characteristics, indicating that information can circulate efficiently.
Sociology
Disaggregating the relationship between precarious employment and delayed marriage in Japan: Incorporating non-cohabiting partnerships
Precarious employment is argued to have led to delayed marriage and increased cohabitation in place of marriage. However, delayed marriage entry has also occurred in countries without an accompanying increase in cohabitation, suggesting that precarious employment may hinder the preceding stages of union formation. This study examines the influence of nonstandard employment and unemployment on later marriage entry for men and women in Japan by analyzing two distinct processes: entry into non-cohabiting partnerships and entry into marriage from non-cohabiting partnerships. The results show that nonstandard employment and unemployment are negatively associated with non-cohabiting partnership entry, in addition to marriage entry from non-cohabiting partnerships. While the negative association between unemployment and marriage entry is stronger for men than for women, there are no significant gender differences in the association between employment and non-cohabiting partnerships entry. The results suggest that the influence of precarious employment appears at earlier stages of union formation.
Anthropology
Top of the world: a global cross-cultural review of spinning tops
Roope Oskari Kaaronen, Marlena Billings, Isobel Wisher, Rebecca Schwendler, Charles P. Egeland, Marc Malmdorf Andersen, Felix Riede
The spinning top is one of the most globally ubiquitous forms of traditional object play, with an archaeological record that spans over five millennia. Yet the top has never been subjected to a systematic cross-cultural analysis. Here, we present a global study covering 1391 spinning tops from 347 past and contemporary societies. Using a geographically explicit dataset, we measure whether different top types exhibit spatial clustering indicative of cultural transmission, or random distributions suggestive of independent convergent evolution. We find that mechanically simpler designs, such as twirlers and whip-tops, are distributed near-randomly worldwide, suggesting frequent independent reinvention. In contrast, the mechanically opaque peg-top is clustered across South and Southeast Asia, reflecting regional cultural transmission. Furthermore, we discuss how tops appear in other social contexts, such as competitive games, agricultural rituals, and spiritual practices. Drawing on ethnographic and archaeological data, we argue that spinning tops likely represent a much deeper, potentially Late Pleistocene, behavioural ancestry than is currently recognised.
Anthropology
Cranial Morphometrics and Postcranial Affinities of Sahelanthropus tchadensis: A Multivariate Re-evaluation of Phylogenetic Position, Genetic Drift and Hominin Congruity in Miocene-Pliocene Chronology
The Late Miocene hominid Sahelanthropus tchadensis occupies a pivotal yet contentious position in early hominin evolution. Since its discovery in 2001, debates have persisted regarding its phylogenetic placement. Current research places S. tchadensis ostensibly as a stem hominin, a basal hominid, with some research positioning the taxon as an early member of the Gorillini lineage. Recent craniometric analyses have reinforced hominin affinities, particularly in basicranial and dental metrics, while postcranial studies have generated conflicting interpretations regarding locomotor behavior. In this paper we present a comprehensive multivariate re-evaluation integrating (1) three-dimensional geometric morphometric analysis of cranial landmarks from the virtual reconstruction of TM 266-01-60-1, (2) comparative dental metrics across extant apes and Plio-Pleistocene hominins, and (3) quantitative reassessment of femoral and ulnar morphology incorporating newly available data from TM 266-01-063, TM 266-01-050, and TM 266-01-358. Whereas principal analysis of the cranial features including the vertically oriented upper face, the reduced subnasal prognathism, and an anteriorly positioned basicranium, places S. tchadensis within the hominin morphospace intermediately between African apes and australopiths. It is the detailed dental metrics that align the species unequivocally with Plio-Pleistocene hominins rather than extant apes, and in the supplementary re-analysis of femoral neck-shaft angle, diaphyseal cortical thickness distribution, and cross-sectional geometry a substantial overlap with both early hominins and extant hominids is uncovered. The additional presence of an obturator externus groove and femoral tubercle also further suggests some capacity for extended hip posture comparable to Ardipithecus ramidus, but without the full suite of australopith locomotor adaptations challenging claims of habitual bipedality. We interpret these findings through the lens of population-genetic models incorporating Late Miocene effective population sizes, rates of genetic drift, and incomplete lineage sorting. We propose that S. tchadensis represents a stem hominin exhibiting mosaic evolution, with cranial and dental derived characters emerging under strong directional selection for dietary and social functions, while postcranial morphologies persisted due to weaker selective pressures on locomotion in wooded habitats. This re-evaluation supports a defined hominin status for Sahelanthropus while cautioning against over-interpretation of individual anatomical systems in isolation, emphasizing the need for integrative phylogenetic frameworks that accommodate clearly delineated classification in a case of heterogeneous trait evolution during the chimpanzeeâhuman divergence.
Other Social and Behavioral Sciences | Sociology
Infant mortality decline in urban Senegal: The case of colonial Saint-Louis, 1880â1921
Our study utilises vital registers from Saint-Louis, Senegal, between 1880 and 1921 to track trends in infant mortality and to investigate individual-level determinants of neonatal and post-neonatal mortality. We find evidence of sizeable declines in infant mortality rates, begin-ning in the late 1890s. For the individual-level analysis, we sampled five birth cohorts (N = 4,728) to examine how socioeconomic factorsâparticularly occupational class, French litera-cy, and neighbourhoodâwere associated with infant mortality risk. Literacy was associated with significantly lower neonatal mortality, but not in the post-neonatal stage, likely reflecting how proximity to colonial health structures shaped reproductive health and infant care. Using interactions, we examined how the effects of socioeconomic factors on mortality may have changed over time. Our analysis suggests that infants from lower socioeconomic backgrounds, as captured by paternal occupation or neighbourhood of birth, faced increasingly higher rela-tive mortality risks compared to those from more advantageous socioeconomic backgrounds.
Enfoques de precauciĂłn en salud pĂșblica: La necesidad de respuestas oportunas en contextos de alta incertidumbre
Artificial Intelligence (AI) promises to transform urban planning research, practice, and education, yet few curricula address âUrban AIâ. This paper presents the pedagogical design of a pilot Urban AI course and argues for three meta learning goals: applying AI effectively and appropriately in urban challenges, addressing its social, environmental, and governance impacts, and developing normative judgements and professional identities around AI. Pilot teaching produced a knowledge graph connecting essential skills to these goals and a critical framework for AI use and reflection, grounded in analysis of 235 student reflection journals, alongside course evaluations, syllabus materials, and student projects (https://www.xiaofanliang.com/teaching/).
Social Statistics
AI for Survey Design: Generating and Evaluating Survey Questions with Large Language Models
Designing survey questions is easy; however designing good survey questions is a complex task. Large language models (LLMs) have the potential to support this task by automating parts of the item-generation process, but their suitability for survey research has not yet been systematically evaluated. Published research in this area remains sparse, and little is known about the quality and characteristics of survey items generated by LLMs or the factors influencing their performance. This work provides the first in-depth analysis of LLM-based survey item generation and systematically evaluates how different design choices affect item quality. Five LLMs, namely GPT-4o, GPT-4o-mini, GPT-oss-20B, LLaMA 3.1 8B, and LLaMA 3.1 70B, were used to generate survey items on four substantive domains: work, living conditions, national politics, and recent politics. We additionally evaluate three prompting strategies: zero-shot, role, and chain-of-thought prompting. To assess the quality of the generated survey items, we use the Survey Quality Predictor (SQP), a tool for estimating the quality of attitudinal survey items based on codings of their formal and linguistic characteristics. To code these characteristics, we used an LLM-assisted procedure. The findings show striking differences in survey item characteristics across the different models and prompting techniques. Both the choice of model and the prompting technique employed influence the quality of LLM-generated survey items. Closed-source GPT models generally produce more consistent items than open-source LLaMA models. Overall, chain-of-thought prompting achieved the best results. GPT-4o, GPT-4o-mini, and LLaMA 3.1 70B achieved similar item quality, while the LLaMA model showed greater variability.
International and Area Studies | Economics | Public Affairs, Public Policy and Public Administration
Measuring the Power Gap: A Comprehensive National Power Index Assessment of India and China (2024â25)
This paper constructs a seven-pillar Comprehensive National Power (CNP) Index to provide a transparent, replicable benchmark of the relative power positions of India and China within a ten-country reference group comprising the United States, China, India, Russia, Japan, Germany, the United Kingdom, France, Brazil, and the Republic of Korea. Drawing on twenty-one publicly available indicators sourced from the IMF World Economic Outlook (2024), SIPRI (2025), WIPO Global Innovation Index (2024), Stanford HAI Global AI Vibrancy Tool (2024), UNDP Human Development Report (2025), Brand Finance Global Soft Power Index (2025), the Fund for Peace Fragile States Index (2024), the World Bank World Governance Indicators (2023), and the UN E-Government Development Index (2024), each indicator is subjected to minâmax normalisation before being aggregated into pillar scores and a weighted composite index. The results show that Chinaâs CNP score of 62.35 leads Indiaâs 33.83 by 28.5 index pointsâa gap driven primarily by Chinaâs dominance in the Economic (pillar score: 78.2 vs. 16.9), Technological (57.8 vs. 18.8), and Diplomatic (64.7 vs. 23.6) dimensions. India records superior scores in Human Capital (62.5 vs. 55.5) and Soft Power (68.7 vs. 61.8), suggesting latent assets whose conversion into strategic capability remains the central policy challenge. The paper situates these quantitative findings within the broader theoretical literature on power transition, argues that the gap is structurally significant but not irreversible, and derives policy implications for Indiaâs long-run strategic posture.
Environmental Studies | Social Statistics
The COVID-19 Pandemic and Carbon Emissions: A Sectoral Analysis of India and Global Trends Against the Paris Agreement Targets
The COVID-19 pandemic triggered an unprecedented contraction in global economic activity, producing a rare natural experiment for observing the relationship between human activity and carbon emissions. This paper examines sector-wise variation in CO2 emissions in India and globally during the pandemic year of 2020, using daily near-real-time data from the Carbon Monitor, and benchmarks observed changes against the 7.6% annual reduction target required under the Paris Climate Agreement to limit global warming to 1.5 degrees C. We find a global CO2 decline of 4.57% in 2020 relative to the 2019 baseline, substantially below the Paris-required threshold, and achieved only through the severe disruption of most economic activity. India's overall decline was steeper at 8.33%, driven disproportionately by the industrial sector (-13.92%) and domestic aviation (-45.71%), reflecting the comparative stringency of India's lockdown measures. Critically, emissions in most sectors had substantially recovered to pre-pandemic levels by the second half of 2020, while ground transportation and aviation showed sustained decline through year-end. The findings suggest that pandemic-induced emission reductions represent a temporary and structurally shallow disruption rather than a meaningful contribution to long-term decarbonization, and that achieving Paris targets will require sustained structural transformation across all major emitting sectors.
Other Social and Behavioral Sciences | Psychology | Sociology
Micro-Interaction Collapse: Automation and the Decline of Everyday Social Encounters in Digitally Mediated Societies
This paper introduces the concept of micro-interaction collapse to explain how technological systems reshape everyday social encounters in contemporary societies. Sociological theory has long emphasized the role of routine interactions in sustaining social order, everyday trust, and public civility. However, the increasing use of automated services, digital platforms, and convenience-oriented systems is transforming the environments in which these interactions occur. Drawing on classical and contemporary sociological theory, this study develops a conceptual framework explaining how technological infrastructures may reduce opportunities for brief face-to-face encounters among strangers during routine activities. The analysis identifies automation, digital platforms, and convenience-oriented systems as key structural drivers of this transformation. The concept of micro-interaction collapse highlights how technological change alters interaction opportunities in everyday environments and proposes directions for future empirical research on the social consequences of digitally mediated societies.
Other Social and Behavioral Sciences | Social Work | Public Affairs, Public Policy and Public Administration | Science and Technology Studies | Communication | Sociology
Meinungsmonitor KĂŒnstliche Intelligenz. Die KI-Nutzung unter ErwerbstĂ€tigen â Unterschiede zwischen Erwerbsklassen, Nutzungsprofilen und Folgenwahrnehmungen von KI am Arbeitsplatz
Der Kurzbericht prĂ€sentiert zentrale Ergebnisse einer Segmentierungsstudie des Projekts Meinungsmonitor KĂŒnstliche Intelligenz 3.0 (MeMo:KI 3.0), die im Juni 2025 durchgefĂŒhrt wurde. Analysiert wird die NutzungshĂ€ufigkeit von KĂŒnstlicher Intelligenz (KI) unter 1.987 ErwerbstĂ€tigen in Deutschland sowie deren Zusammenhang mit Erwerbsklassen, soziodemografischen Merkmalen und arbeitsbezogenen Einstellungen. Die Ergebnisse zeigen deutliche Unterschiede zwischen Erwerbsklassen auf Grundlage der Oesch-Klassifikation. Höher qualifizierte Gruppen mit technischer oder soziokultureller Arbeitslogik â etwa technische Experten oder selbststĂ€ndige FachkrĂ€fte â berichten deutlich hĂ€ufiger von regelmĂ€Ăiger KI-Nutzung. Niedrigere Nutzungsraten finden sich dagegen in Erwerbsklassen mit geringerer formaler Qualifikation oder stĂ€rker standardisierten TĂ€tigkeitsprofilen, etwa bei qualifizierten Arbeitern, FachkrĂ€ften im Dienstleistungsbereich oder kaufmĂ€nnischen Angestellten. Insgesamt zeigt sich, dass ein erheblicher Teil der ErwerbstĂ€tigen bislang nur selten oder gar nicht mit KI arbeitet. HĂ€ufigere KI-Nutzung geht zugleich mit höherer subjektiver KI-Kompetenz und positiveren affektiven Einstellungen zu KI am Arbeitsplatz einher. Vielnutzende bewerten zudem die erwarteten Auswirkungen von KI auf Arbeitsbedingungen deutlich positiver und berichten geringere negative affektive und verhaltensbezogene Reaktionen auf die KI-EinfĂŒhrung am Arbeitsplatz. Insgesamt weisen die Befunde auf eine digitale Spaltung der KI-Nutzung entlang von Alter, Bildung und beruflicher Position hin.
Other Social and Behavioral Sciences | Economics | Social Work | Public Affairs, Public Policy and Public Administration | Science and Technology Studies | Communication | Sociology
Meinungsmonitor KĂŒnstliche Intelligenz. Nutzung und Bewertung von KI am Arbeitsplatz â eine Frage der Erwerbsklasse: Kurzbericht einer Segmentierungsstudie
Marco LĂŒnich, Birte Keller, Florian Golo FlaĂhoff, Frank Marcinkowski
Der Kurzbericht prĂ€sentiert zentrale Ergebnisse einer Segmentierungsstudie des Projekts Meinungsmonitor KĂŒnstliche Intelligenz 3.0, die im Juni 2025 durchgefĂŒhrt wurde. Analysiert werden Einstellungen, Bewertungen und Reaktionen von 1.987 ErwerbstĂ€tigen in Deutschland gegenĂŒber dem Einsatz von KĂŒnstlicher Intelligenz (KI) am Arbeitsplatz, differenziert nach Erwerbsklassen auf Grundlage der Oesch-Klassifikation. Die Ergebnisse zeigen ausgeprĂ€gte Unterschiede zwischen Erwerbsklassen. Höher qualifizierte und technisch orientierte Gruppen bewerten KI affektiv positiver, sehen gröĂere berufliche Nutzenpotenziale und berichten von geringeren Belastungs- und Substitutionssorgen. Erwerbsklassen mit organisationaler oder interpersoneller Arbeitslogik sowie niedrigeren Qualifikationsniveaus reagieren hingegen ambivalenter und Ă€uĂern hĂ€ufiger Sorgen, insbesondere hinsichtlich des Datenschutzes, sozialer Kontakte und der allgemeinen Ersetzbarkeit menschlicher Arbeit. Ăber alle Erwerbsklassen hinweg werden Entlastungspotenziale durch KI in Hinblick auf die Arbeitsbelastung und den Gesundheitsschutz wahrgenommen, wĂ€hrend Widerstands- und Protestneigungen insgesamt moderat bleiben. Insgesamt verdeutlichen die Befunde, dass Wahrnehmungen von KI am Arbeitsplatz stark von beruflicher Position, Arbeitslogik und Qualifikation geprĂ€gt sind.
Decomposing Behavioral Variability in Email Communication: Self-Excitation, Latent State-Switching, and Their Interaction in the Enron Corpus
Human email communication exhibits substantial temporal variability that resists simple characterization. We treat individual email activity as a stochastic system and ask how much behavioral variability is explained by each of three generative mechanisms: circadian and weekly periodicity, self-excitation from incoming messages, and latent workârest state-switching. Using the Enron email corpus (58 users, 101,299 sent emails, 1998â2002), we fit a hierarchy of five modelsâinhomogeneous Poisson, lognormal renewal, Hawkes process, Poisson hidden Markov model (HMM), and a hybrid HMM-on-Hawkes-residualsâevaluated via strict 70/30 temporal train/test splits. All three pre-registered hypotheses pass: 83% of users exhibit significant self-excitation (α > 0; mean branching ratio 0.15), 84.5% show greater than 10% log-likelihood improvement under state-switching, and 62% retain residual state-switching structure after Hawkes filtering. Latent state-switching provides the largest predictive gains, while self-excitation is real but modest, and the two mechanisms capture complementary sources of variability. All code and derived data (timestamps and anonymized identifiers only) are publicly available for full reproducibility.
Geography | Environmental Studies | Sociology
Deltaic Compression in the Sundarbans: Migration, Ecology & the Politics of Cascading Calamities
Climate change discourse frequently portrays the Sundarbans as a landscape approaching displacement or ecological collapse. Such narratives foreground sea level projections and cyclone intensification but often overlook how livelihoods persist within inhabited delta environments despite mounting ecological stress. Drawing on field research conducted across four administrative blocks of the Indian Sundarbans, namely Sagar, Namkhana, Kakdwip and Basanti, this study examines how agrarian instability, forest dependency, seasonal migration and institutional mediation interact within a single political ecology of adaptation. The paper advances the concept of deltaic compression to describe the cumulative narrowing of livelihood elasticity under conditions of repeated environmental disruption and partial institutional buffering. Rather than producing immediate displacement, climatic exposure intersects with social stratification, debt circulation and infrastructural fragility to intensify labour across agriculture, forest extraction and migration simultaneously. Economic diversification expands, yet income mobility remains limited and recovery intervals contract under recurrent storm exposure and salinity intrusion. Integrating field data with scholarship on vulnerability, resilience and environmental governance, the analysis demonstrates how risk in the Sundarbans emerges through the interaction of ecological change and historically mediated structures of belonging. Migration circulates labour without dissolving settlement continuity, while forest engagement and public welfare systems operate as stabilizing yet incomplete buffers. The framework of compression therefore redirects analytical attention away from imminent climate displacement toward the gradual tightening of livelihood margins within densely inhabited delta landscapes. Recognizing compression as a structural condition highlights the limits of policy frameworks oriented primarily toward episodic disaster response. Addressing ecological vulnerability in the Sundarbans requires long term infrastructural reinforcement, soil regeneration strategies and financial mechanisms capable of reducing dependence on informal debt while supporting adaptive livelihoods under intensifying climatic volatility.