This paper examines the reciprocal associations between specific internalizing (e.g., depression and anxiety) and externalizing (e.g., Attention Deficit/Hyperactivity Disorder, Conduct Disorder, and Oppositional Defiant Disorder) disorder symptoms and cannabis use during early adolescence with age differences. We analyzed youth-reported cannabis use, depression, anxiety, Attention Deficit/Hyperactivity Disorder (ADHD), Conduct Disorder (CD), and Oppositional Defiant Disorder (ODD) symptoms in 9- to 15-year-old adolescents enrolled in the longitudinal Adolescent Brain Cognitive Development (ABCD) Study (N=11,868) using data from the baseline visit through the 4-year follow-up. Multilevel regression models, parsing between- and within-youth effects were fit to examine the association between cannabis use and five different mental health disorders prospectively. Moderation by age was tested. In the main analyses, all between-youth reciprocal associations between mental health disorder symptoms (i.e., internalizing and externalizing) and cannabis use were significant, except anxiety. Anxiety was unidirectionally related to cannabis use, where increased anxiety symptoms predicated more cannabis use one year later (β = 0.0810, p = .006) but not vice versa. Strongest between- and within-youth reciprocal associations emerged for depression and conduct disorder symptoms with cannabis use prospectively, with age moderating the associations. In a nationwide sample of adolescents ages 9 to 15 years-old, we found depression and conduct disorder symptoms were most strongly and reciprocally associated with cannabis use prospectively. Further research is necessary to validate and confirm our findings and extend to greater cannabis use frequency and motives for use in the context of increased acceptance of cannabis use as treatment for mental health issues.

The expansion of research systems in low- and middle-income countries has shifted science to a more diverse geographical structure. Using a global dataset of 40 million authors in Science, Technology, Engineering, Mathematics and Medical fields (STEMM), we investigate whether this shift has made it easier or more difficult for newcomers residing in the Global South to rise to prominence in their disciplines. We tracked yearly cohorts of authors who began their publication careers between 2000 and 2014, finding that the South-North gap in the likelihood of joining the ‘citation elite’ (the top 5% of most cited authors per cohort) has increased by approximately 23%. Southern Asia and South-Eastern Asia outperform Eastern Asia and Latin America and the Caribbean in terms of changing regional shares in the citation elite. South-North gaps in citation elite membership also appear to be larger and increasing in the life sciences, and smaller and shrinking in some engineering-related subfields. Using decomposition approaches, we attribute most of the widening South-North gap in citation elite membership to diverging trends in attrition rates, publication outputs and journal selection, with changes in team sizes and regional migration playing only a minor role. These findings highlight the enduring dominance of wealthier nations in the production and distribution of scientific knowledge. While the scientific workforce has diversified globally and opportunities for Global South individuals to pursue successful science careers in the Global North have expanded, regional disparities persist with scientists based in the Global South now less likely to achieve scientific prominence relative to their Global North counterparts than previously.

Studying visual consciousness in animals has provided important insights into its neural mechanisms, due to the availability of precise neural recording and perturbation techniques. On one hand, animals can serve as models to understand the neural underpinnings of visual consciousness and its disorders in humans. On the other hand, investigating the presence of consciousness and comparing perceptual experiences across various species are fascinating in their own right. In this chapter, we review experimental approaches and key findings regarding each topic. We argue that to understand the neural mechanisms of visual consciousness, we first need to establish perceptual report and no-report paradigms in humans that accurately reflect their subjective experiences. Then, we need to transfer these paradigms to animals and combine them with high-throughput electrophysiology and cell- or pathway-specific perturbations. As we review several experimental approaches including visual illusions, visual masking, bistable perception paradigms, and other behavioral metrics to investigate conscious perception in different animals, we argue that the combined evidence from these approaches would give the most refined picture of how they subjectively experience the visual world. Finally, we present results from non-human primate studies concerning the neural circuitry underlying visual consciousness disorders such as blindsight and spatial neglect.

Negative campaigning (NC) has become a prevalent campaign strategy in recent years, especially in interactive media such as Facebook, Twitter/X or Instagram where politicians can communicate without any mediation by gatekeepers like journalists. Even though the identification of NC is a crucial precondition for understanding modern election campaigns, the automated identification of NC is still in its infancy, even with state-of-the-art text analysis methods. Especially when researchers want to identify NC across elections and different levels of a polity, they need to develop and validate specific classifiers. As actor constellations and topics vary considerably across different elections, applying automated measures to lower-level elections requires a thorough validation of how well trained models generalize across contexts. Using several federal and state level elections as a test case, this paper investigates the generalizability of transformer models for text classification in the complex German multilevel and multiparty system. Based on over 40,000 social media posts of candidates in eight state and federal elections between 2013 and 2021 that were annotated by human coders, the classifier can identify negative campaigning across space and time. A leave-one-out classification shows that the model can accurately predict data even for unknown elections with moderately sized training data. We demonstrate how a classifier for a demanding theoretical concept can be trained and validated in multidimensional contexts and provide orientation for similar projects.

Climate change mitigation technologies (CCMTs) play a key role in decarbonisation efforts, but may also create new opportunities for crime and security risks that have remained under-explored. This study presents an expert-informed assessment of crime threats and countermeasures associated with CCMTs, involving 28 experts from government, law enforcement, industry, academia, and civil society. Through structured idea generation, thematic analysis, and forecasting surveys, the participants evaluated 35 distinct crime threats and 36 countermeasures, of which 13 threats and 18 countermeasures were uniquely identified by them. The identified risks were found to be concentrated in CCMT supply chains and resource extraction, with high-priority threats relating to environmental harms, illegal mining, and human rights abuse, alongside cyber-enabled and financial crimes. Promising countermeasures include CCMT-specific regulation, risk assessment, data sharing, physical security, and targeted education. The findings show that the green transition reshapes rather than removes crime risks, underscoring the need for proactive governance to ensure a secure and sustainable low-carbon transition.

Anger is provoked by frustrated expectations and triggers a punishment response. When expectations reflect social identities, punishment may vary accordingly. We design an online experiment on an Italian sample (N=597 trustor-dictators) where subjects play a trust game followed by an allocation game with punishment options, a sequence designed to elicit genuine emotional reactions upon learning whether their counterpart defected. We elicit beliefs under incentive compatibility and measure emotional responses using the PANAS scale. We apply the belief-dependent model of anger by Battigalli et al. (2019b) to derive our predictions. In our data, defection triggers a strongly negative emotional reaction, with anger being the dominant response. Anger correlates with elicited beliefs about trustworthiness among subjects who best respond to their expectations, and anger in turn predicts punishment. Female trustors hold higher trustworthiness expectations toward female trustees than toward male ones, while no analogous pattern emerges for male trustors. Defection by a female trustee triggers a stronger anger response in female trustors, in line with the larger expectation gap. Punishment follows a cross-gender pattern, consistent with in-group bias. Overall, our results suggest that gender bias in punitive behavior emerges both from expectation-driven frustration and from residual preference-based differences.

Artificial intelligence is rapidly advancing the capabilities of social robots. Positioned as one key solution to issues related to ageing societies, these socially interactive, physically moving robots will likely be used in many public and private contexts. Emerging technologies like these are known to be prone to criminal exploitation before regulatory and governance frameworks adapt. To support anticipatory governance, this study uses expert elicitation to identify and assess plausible future crime and security risks associated with large-scale social robot deployment, alongside potential countermeasures. Over two days, 21 expert stakeholders identified and prioritised 21 distinct crime threats and 17 countermeasures according to anticipated risk severity and implementation potential. The highest-risk threats concerned the exploitation of social robots’ social features for fraud and social engineering, using them to spread hate, extremism, or disinformation, and their facilitation of harassment, stalking, or coercive control. The most promising countermeasures included robot registration or identity markers, anticipatory risk assessment practices, and cybersecurity measures. The findings contribute to futures-oriented debates on human–robot relations and inform research and policy agendas aimed at pre-empting harmful social robot–enabled outcomes.

Brazil’s rapid digital transition promised broader civic participation but instead deepened polarization, disinformation, and democratic erosion. This article examines how these dynamics produced a distinctive model of digital regulation, shaped not by legislatures or bureaucracies but by judicial activism. Interpreted through the framework of digital constitutionalism, Brazil’s regulatory trajectory reveals an attempt to reassert rights, trust, and institutional balance in the face of platform power and algorithmic manipulation. By analyzing the Marco Civil da Internet, the General Law on the Protection of Personal Data (LGPD), the failed “Fake News Bill” (PL 2630), the “AI Bill,” the interventions of the Superior Electoral Court, and ongoing debates on AI legislation, the article shows how crisis-driven governance reshaped the country’s digital governance. The analysis is based on a five-pillar framework that is used to explain the Brazilian digital regulatory model. This model indicates that Brazil has developed its own traits of “digital constitutionalism” provided that the country’s regulations are reliant on a strong judicial activism that not only guarantees rights, but help to preserve democratic values, and maintain national sovereignty in the face of Big Techs. However, this experience illustrates both the risks of judicial overreach and the potential of constitutional principles to guide democratic resilience in the digital age. The article contributes to comparative debates by positioning Brazil as a Global South test case for rights-based digital governance.

Purpose: Social robots are set to permeate every area of our lives from childhood, well into our old age—from education, policing, and entertainment, to healthcare. Ensuring that their deployment happens in a safe and secure way requires a firm understanding of the broad scope of crime and security threats that social robots may facilitate. Methods: We conducted a scoping literature review to provide an overview of the crime and security threats related to social robots, and potential countermeasures. Results: We identified 18 distinct crime threats and 17 possible countermeasures described across 388 academic and non-academic articles from any discipline. The crime threats ranged from fraud and trespassing, to espionage and abuse towards robots. Countermeasure themes included establishing social robot rights and many technological adaptations. Conclusions: Stakeholders in the social robotics domain are encouraged to use these findings to pre-empt future crime risks related to social robots.

Humans are a social species, relying on a complex network of long-term relationships and cooperation to tackle ecological problems such as obtaining resources, safety and procreation. This rich sociality is as demanding as it is rewarding; while affiliation and status are intrinsically valuable, securing these benefits requires significant cognitive effort, material investment, compromise, and vigilance. Common views of cultural evolution and innovations often frame social interactions either as a vehicle to transmit knowledge across generations, or as a cooperation problem to be solved. I propose that culture evolves to directly address the challenges and costs inherent in social relationships. Cultural innovations help facilitate social interactions by making them more predictable and regular, and promoting independence and flexibility. Predictability can be achieved through centralized social events and experiences, such as rituals and stories, and through institutions and norms. Independence is promoted by technologies that enable individuals to carry out tasks on their own, and by substituting some of the benefits associated with social relationships. In all cases cultural innovations success can be evaluated by the way they meet the needs and offset the costs of social interactions. This view can explain the adaptive interactions between cultural innovations and social relationships.

Understanding causal relations for sustainability scientists means studying phenomena that involve complex causality, e.g. multiple and heterogeneous relations and entities, context-sensitivity, and multi-scalar phenomena. To cope with this, sustainability scientists have borrowed concepts from neighboring disciplines, used causal expressions that have confusing meaning, or abstained from using causal language altogether. We argue for using causal language as it is useful for prediction, manipulation, explanatory understanding and responsibility attribution. However, traditional views on causality have limitations dealing with causal complexity. We spell out the challenge of formulating useful concepts. We argue that it is important to recognize the role of everyday causal cognition and its limitations, to distinguish the different ways in which sustainability scholars talk about complexity and to clarify the causal meaning of complexity concepts, like non-linearity, adaptive capacity, and feedback. Finally, we propose the concept of causal configuration to make explicit the causal meaning of complexity-related concepts.

Childfreeness has often been examined through the lens of decision-making in early adulthood or as a potential source of regret in later life. Less attention has been paid to how childfreeness is experienced and lived in midlife, particularly among women who often remain biologically fertile but increasingly encounter social assumptions of finality. This qualitative study explores how women over forty make sense of childfreeness as a lived identity. Using interpretative phenomenological analysis, in-depth interviews were conducted with twelve childfree women aged 40-55 years old. Three group experiential themes were constructed that captured a development shift in which childfreeness becomes settled and no longer subject to internal negotiation. Participants described childfreeness as grounded in values of freedom, responsibility and ethical self-knowledge, alongside a conscious refusal of motherhood understood as irreversible responsibility. Rather than rejecting care or generativity, women articulated alternative forms of care and future-oriented planning that challenged pronatalist assumptions equating womanhood, care and generativity with motherhood. The findings highlight midlife as a critical yet under-researched period in life trajectories of childfree adults, offering important insights into gendered ageing, moral responsibility and the plurality of meaningful adult life trajectories beyond parenthood.

Migration is a defining phenomenon of our time, around which heightened political rhetoric creates the impression of unprecedented political conflict. In the UK, this perception coincides with major political developments, such as the Brexit referendum and the rise of anti-immigration politics in recent decades. We apply quantitative text analysis techniques to the Hansard collection of spoken contributions in the House of Commons to examine how political elites have discussed immigration over the past century. We find that the Labour Party has consistently expressed more positive sentiment towards immigration compared to the Conservative party since the early 1960s, and that these positions further diverged in the early 1980s. The last 15 years have seen more negative rhetoric across all major parties, with immigration discussed among Conservative and Reform UK MPs in the most negative terms since 1923. We discuss possible future research avenues, supported by suggestive findings on the increasing moralization of the immigration debate and growing negativity towards asylum.

As financial decision‐making increasingly shifts toward algorithmic co‐pilot models, the psychological dynamics of human–algorithm collaboration remain insufficiently understood. This study examines defensive attribution mechanisms in financial trading, focusing on how individuals assign responsibility and experience regret under varying outcomes. A custom‐built trading simulator was used (N = 88; 1,320 incentivized trials), and behavior was analyzed using linear mixed‐effects models. The results reveal a robust self‐serving bias expressed through two distinct processes. Responsibility attribution was high for gains but declined sharply after losses, while perceived algorithm influence increased following failures, indicating retrospective inflation of the algorithm’s role. Regret exhibited a structural asymmetry: loss‐related regret was strongly dispositional, whereas gain‐related regret was situational. These patterns suggest that negative outcomes activate stable self‐evaluative tendencies, while positive outcomes elicit more context‐dependent responses. Crucially, restoring decision autonomy significantly reduced emotional distress after losses. Participants who chose to ignore the algorithm experienced lower regret, indicating that agency serves as a psychological buffer that protects self‐image more effectively than compliance with external advice. The findings imply that financial interfaces should avoid full automation and instead prioritize meaningful user engagement to preserve psychological ownership of decisions.

This report presents findings from the fifth wave of the PROPA online survey, conducted between 10 and 27 October 2025 among Russian citizens aged 18 and older (N = 2,676). The survey examines economic perceptions, political attitudes, views on the war in Ukraine, experiences with crime, social networks, and media consumption. Key findings • Economic perceptions remain stable but pessimistic. Across waves, respondents’ self-assessments of their personal economic situation show little change, and average satisfaction remains low. Concern about rising prices remains consistently high across social groups. • Attitudes toward the war in Ukraine remain polarized, and support coexists with negotiation preferences.Nearly half of respondents express support for the war, while a comparable share favors initiating peace negotiations. Notably, a substantial minority of those who declare support for the war also support starting negotiations. • Personal exposure to the war is widespread and politically consequential. Many respondents report personal connections to the war through participation or losses among close contacts. Such exposure is strongly associated with both support for continued military action and expectations about the war’s duration. • Fraud is the most common crime reported, trust in law enforcement remains moderate. Most respondents report no direct experience of crime in recent years. Among those who have, fraud is the most common form of crime. However, reporting varies by age, gender, region. Willingness to seek police assistance depends strongly on prior experience with law enforcement. • Media consumption continues to shift toward Telegram amid declining trust in news. Reliance on several traditional and online news sources has declined, while Telegram has continued to grow as a key source of political information. Across platforms, respondents report declining trust in news and political information. Taken together, the results of Wave 5 portray a society characterized by persistent economic anxiety, polarized war-related attitudes, evolving information habits, and complex patterns of vulnerability and social interaction.

During free play, children decide with which peers they want to spend their time. The distribution of time and social effort amongst their peers can be indicative for the inclusivity of the group. In this appraisal paper, we explore a recently introduced measure to estimate social mixing in groups, called social fluidity. We estimate social fluidity for 27 data sets of children's face-to-face interaction networks collected during playtime breaks and discuss how this measure can be used by field experts to characterize group behavior as well as individual behavior. We therefore draft a step-by-step plan to analyze proximity data based on the behavioral model and the social fluidity measure introduced by Colman et al.

This exploratory study compares the remote work experiences of employees with and without disabilities in New Zealand, revealing key differences in preferences and barriers. While both groups perceive remote work as beneficial to workplace culture, employees with disabilities report a more pronounced impact alongside distinct challenges. The study emphasizes the need for inclusive remote work policies to ensure equitable opportunities for all.

For the last two decades, a widely adopted commitment by soybean traders to avoid sourcing from farms in the Brazilian Amazon with recent deforestation has contributed to reducing deforestation across the biome. Recently, legal and political challenges to this commitment have led to its likely demise. We review the evolution of the Amazon Soy Moratorium (ASM) policy context and present estimates of the area of forest at risk with the end of the policy. Ending the ASM will lead to increased deforestation in the Amazon and could discourage the adoption of policies against deforestation by other private sector actors more broadly.

Measuring media ideology is essential for researching media bias, media effects, and various important topics in political science, communication, and other social sciences. However, given journalistic norms of objectivity and the complexity of ideology, measuring media ideology accurately is uniquely challenging. Large language models (LLMs) have become valuable tools in this endeavor. Based on media communication theories, I argue that media ideology is expressed via different cues -- the topic, argument, framing, criticism, and sources of the media content -- and that LLMs often miss these. Standard methods of LLM classification also offer little control, flexibility, and data granularity to researchers. Drawing on insights about computational and quantitative measurement methodologies, I introduce the "Multi-Cue Classification" (MQ-Class) approach. With MQ-Class, an LLM classifies the different ideological cues separately and researchers then apply pre-specified weights and thresholds to combine them into one label per text. I compare standard LLM and MQ-Class methods using two example tasks -- classifying the economic and cultural ideologies of a novel sample of online media articles. Across multiple tests, MQ-Class is more accurate and puts researchers "back in the driver's seat." I conclude by discussing how MQ-Class could be implemented for other classification tasks and data.

Purpose - With worldwide consideration towards in succeeding business sustainability, the necessity of prioritizing the concept of CSR was emerged. Since the phenomenon of CSR captures broader scope organizations frequently strive to gain more understandability of this concept while providing benefits of CSR to their stakeholders. The purpose of this paper is to examine how Corporate Social Responsibility (CSR) awareness and perceived CSR value affect customer loyalty of two dominant supermarket players in a high-density urban commercial hub in Sri Lanka. Social exchange theory is implemented as the theoretical framework of this study. Design/methodology/approach – Adopting an explanatory research design, cross-sectional data from 108 respondents were collected in 2019 using multi-stage non-probability sampling method incorporating purposive sampling followed by quota sampling. Responses were gathered using a self-administered survey questionnaire. To test the formulated hypotheses based on independent and dependent variables, multiple linear regression analysis was performed with the aid of SPSS 25.0 version. Findings – The findings reveal that the level of CSR awareness has a positive, yet modest and significant impact on supermarket customer loyalty. Whereas, perceived value of CSR indicates a positive, stronger and significant effect on customer loyalty in the supermarket sector. Consequently, perceived value of CSR exerts a stronger positive influence on supermarket customer loyalty rather than CSR awareness. Implications - This study contributes to the literature by deconstructing the CSR-loyalty nexus. Consequently, the conclusions made from the results will be helpful to managers and employees in modern retail stores to determine the effectiveness of currently implemented CSR projects towards customers and what components should be prioritized in their CSR efforts to make customers loyal. Further it will provide useful insights to the managers in supermarkets in developing effective CSR strategy as enhancing customer loyalty. Keywords: Corporate social responsibility (CSR), CSR awareness, Customer loyalty, Perceived value, Supermarkets

The transactions involving most of the digital assets do not require financial intermediaries and cannot be regulated. Further, the volatility of digital asset and risk exposure affects the growth of financial market. Hence, the regulatory authorities also regularly monitor and incorporate the necessary transformation and transmission of the respective monetary policies. The impact of Digital Asset, either Private or Public, on the money flow is to be examined. Considering the above, this paper intends to examine the on monetary policy implications for digital assets in general and CBDCs in particular.

This study examined the effect of credit risk management practices on the financial performance of registered Deposit-Taking SACCOs in the Coastal Region of Kenya. The objectives of the study were to determine the effects of credit appraisal methods, credit risk identification, credit risk mitigation practices, and credit risk monitoring on SACCO financial performance. The study focused on SACCOs operating in the Coastal Region, including those headquartered elsewhere but with branches in the region. The theoretical framework was guided by Asymmetric Information Theory, Transaction Costs Theory, the 5 C’s Model for Client Assessment, and Credit Liquidity Theory. A non-experimental correlational research design was adopted, targeting 30 participants from 10 SACCOs using a census sampling approach. Primary data were collected through structured questionnaires, with validity and reliability ensured through expert review and a pilot study. Data were analyzed using SPSS, and inferential statistics were performed using a multiple linear regression model. The findings revealed that credit risk identification (ρ < 0.001, β= 0.312) and credit risk mitigation practices (ρ < 0.001, β = 0.511) had a statistically significant positive effect on financial performance, while client appraisal methods (ρ = 0.084, β = 0.142) and credit risk monitoring (ρ = 0.221, β = 0.119) were not statistically significant. Based on these results, the study recommends that SACCOs strengthen credit risk identification and mitigation strategies, adopt effective client appraisal methods, and enhance monitoring practices to the extent feasible. The study contributes valuable insights for SACCO managers, policymakers, investors, and researchers seeking to improve financial performance through effective credit risk management.

In the era of the Quantified Self, continuous self-measurement has become routine, enabling individuals to track genetic data, metabolism, sleep, and circadian rhythms with unprecedented precision. Yet the structure and quality of people's social connections, the Exogenous Social Connectome, remain largely ignored, despite decades of evidence showing that social integration predicts mortality as reliably as smoking, and often more strongly than hypertension or obesity. Social health is still assessed primarily through surveys and self-report rather than objective measurement. To fill this gap, we introduce the Social Connectivity Value (SCV), a composite digital biomarker that quantifies how social network structure biologically influences mental health, physiological regulation, and longevity. SCV builds on sociometric mapping, network topology, evolutionary weighting of relationships, and complex-systems dynamics to capture how social structure affects stress biology, immune function, and aging. Within this framework, social structure is treated not as passive exposure but as a modifiable biological system that can be measured, tracked, and deliberately designed. Despite extensive evidence linking social ties to health, existing approaches fail to specify which structural features matter, which configurations are fragile, and where change has leverage. SCV provides this framework through a standardized protocol for mapping social connections over time, from first dates to lifelong partnerships. In a Social Geroscience framework, SCV metrics operate alongside and shape established longevity biomarkers such as heart rate variability, sleep quality, and metabolic control. By making social structure visible and quantifiable, SCV enables the deliberate design of personal social networks that reshape dating trajectories, pair-bonding outcomes, and long-term healthspan.

This paper develops a theoretical model explaining why evaluators may deliberately avoid relying on observable performance metrics in selection contexts characterized by long-term developmental horizons. While conventional frameworks treat measurable credentials—such as degrees or certifications—as monotonic indicators of ability, real-world selection often displays a paradox: highly credentialed candidates may be systematically discounted. The model distinguishes between observable qualifications and latent foundational capacity, defined as the underlying potential for adaptation and long-term learning. Under developmental uncertainty, evaluators interpret credentials not only as signals of past performance but also as indirect indicators of how individuals have allocated finite developmental resources. Extensive investment in measurable achievements may therefore signal a relative neglect of unstructured capacity essential for long-term adaptability. We formalize this mechanism as horizon-dependent metric avoidance, showing how a non-monotonic relationship emerges between observable qualifications and evaluation outcomes. The resulting Reverse Credential Effect provides a structural explanation for overqualification penalties and the strategic discounting of metrics in high-uncertainty, long-horizon selection environments. More broadly, the model highlights how the temporal structure of evaluation fundamentally shapes the informational value of performance signals. By introducing evaluation horizon as a structural parameter, the model extends standard signaling frameworks to long-term developmental selection contexts.

This thesis reconceptualizes American metropolitan areas as dissipative thermodynamic structures governed by non-equilibrium dynamics. Drawing on process philosophy, non-equilibrium thermodynamics, and information geometry, I analyze 386 MSAs using publicly US Census data from 2006–2024 (2020 excluded due to data disruption). Among 102 major US MSAs, 9 (8.5%) meet all criteria for confirmed dissipative structures, with 46.2% operating in the dissipative regime; 340 MSAs (88%) exhibit predominantly geodesic demographic trajectories with a mean geodesic efficiency η of 72.6%. Furthermore, only one manifold tearing event was found to have occurred (2008 Financial Crisis), creating societal transformative changes; But 95.6% of MSAs showed adiabatic (resilient) responses to the 2008 crisis and 91.3% to COVID-19, with zero non-adiabatic classifications. Validation confirms non-equilibrium dynamics (p=0.023). The findings challenge equilibrium-based urban planning, suggesting policy should focus on managing flows and enabling adaptive capacity rather than optimizing fixed forms. A surprising result was the universal adiabatic response of all major MSAs surveyed, suggest great resilience in medium to large American cities while refuting the “urban doom” thesis following the COVID-19 pandemic. All source codes are available at: http://github.com/rogerwzeng/dissipative-urbanism Keywords: dissipative structures, non-equilibrium thermodynamics, information geometry, urban complexity, process philosophy, metropolitan dynamics, demographic flows

Transgender and gender diverse (TGD) individuals in China navigate a distinctive socio-cultural stress ecosystem shaped by collectivist values and conservative public discourse. While minority stress theory is well-established, the specific processes of identity negotiation under Chinese familial, institutional, and societal pressures remain underexplored. This qualitative study conducted in-depth, semi-structured interviews with ten TGD individuals in China. Data was analyzed using grounded theory, progressing through open, axial, and selective coding, informed by social role theory and labeling theory. Analysis revealed four dynamically interconnected social roles: the “Mentally Ill Patient” (characterized by pathologization and internalized stigma), the “Marginal Person” (experiencing systemic and familial exclusion), the “Pretender” (employing concealment as a survival strategy), and the “Helper” (fostering community mutual aid and resilience). These roles are not static but fluid, illustrating how external labeling and role expectations are internalized, negotiated, or resisted. Mental health challenges among TGD individuals in China must be understood as a dynamic process of negotiating identity and stigma within a collectivist structural context. The findings extend minority stress theory beyond Western paradigms, highlighting the urgent need for affirming, community-informed support systems that move beyond pathologization to empower resilience and agency. This manuscript is currently under review at Sex Roles (Springer Nature).

The approximate number system allows humans and other species to quickly estimate the numerosity of a set of objects. Much research has focused on its possible role as a basis for mathematics achievement and learning difficulties, relying importantly on the numerosity comparison task. In contrast, less research has focused on its underlying mechanisms and other tasks. In this study we used a numerosity estimation task, where participants had to focus on a target set of dots while ignoring a non-target set of dots of a different color. The target and non-target sets’ numerical and non-numerical properties (total area, convex hull area, color light output) were manipulated. Using a small-N design, we asked participants (N = 9) to attend several testing sessions (Nsessions = 8 per participant), to measure the magnitude of intra-participant variability across sessions and reduce error variance. Results showed that numerosity estimates were significantly affected by the target numerosity, with a magnitude about 6 times larger than both target set’s non-numerical properties. Color cues and the properties of the non-target numerosity showed minor contributions that were not consistent across participants. Participants’ performance variability across sessions was 3-4 times smaller than variability across participants. Our results support the role of numerosity as the main driver of participants’ numerosity estimates, against proposals that focus on the role of non-numerical properties such as area measures or texture density.

This study traces the "Synthetic Turn" in digital methods—the transformation of generative AI from object of study to primary research instrument. Analyzing the complete archive of 474 projects from the Digital Methods Initiative (2007–2026), I document a fourteen-fold increase in AI/ML method adoption: from 4.9% of projects during algorithmic critique (2007–2015), to 33.5% during platform auditing (2016–2021), to 70.1% in the current period (2022–2026). The timing complicates popular narratives: 41.4% of projects in 2022 engaged substantively with AI/ML before ChatGPT's public release. I formalize four "synthetic protocols"—Performative Probing, Contrastive Generation, Recursive Amplification, and Symptomatic Reading—each tracing clear lineage to established practices. Yet two-thirds of Synthetic Turn projects employ AI/ML methods while only 4.8% position AI as their primary methodological lineage: adaptation, not displacement. Synthetic protocols offer pathways to critical AI research that do not depend on corporate cooperation, technical infrastructure, or privileged access.

There is significant research on support for political violence (SPV), its correlates, and interventions to reduce it. However, there is no framework for understanding who supports political violence. This article leverages the exploratory power of (causal) machine learning to conduct a registered meta-reanalysis of both the observational and experimental literature on SPV from 1995-2025 to synthesize and summarize previous research. First, we identify three categories of individual-level predictors: politically salient identities, psychological characteristics, and attitudes toward one's political system. Second, we find that young adults are the most likely to support political violence across many recent surveys, particularly in the U.S. Additionally, in two experiments in the U.S. and India we find that young people are by far the most affected by treatments aimed at both decreasing and increasing support, respectively. Third, and in contrast to research on the perpetration of violence, we find scant evidence of a relationship between gender identity and SPV.

This article examines how internet memes contribute to the sociotechnical imaginaries surrounding artificial intelligence (AI). Drawing on Castoriadis’s distinction between instituted and instituting imaginaries, we understand memes as narratives that symbolically construct AI in everyday culture. In the first section, we review research on sociotechnical imaginaries of AI across textual and visual domains, and show that memes that speak about AI have received comparatively little scholarly attention. We then introduce the notion of sociotechnical narratives to frame these imaginaries as contested and provisional rather than coherent or hegemonic. In the second section, we conceptualize memes as narratives that intervene in the symbolic institution of social reality, showing that they can reinforce dominant meanings through repetition and normalization, but also subvert or reframe them. The third section presents a mixed-methods empirical study of 560 memes collected from Imgflip.com (2016–2025). After building the corpus through manual filtering, we coded memes by topic and conducted a fine-grained qualitative analysis of four main categories: AI takeover, generative AI, art, and AI social impact. Our findings show that most memes reiterate rather than subvert dominant representations of AI. Humor tends to flatten disagreement rather than intensify it, producing what we describe as dormant agonism.

This article argues that public engagement with Artificial Intelligence (AI), as it becomes visible through media traces, is structured less as a technoscientific controversy among competing publics than as a displaced form of political antagonism. Intervening in current STS debates on AI “super-controversy,” we revisit controversy studies and recent calls for controversy elicitation, which seek to revitalize democratic problematisation by fostering participation and extended expertise. While these approaches foreground conflict, they retain an implicit epistemic horizon in which legitimate participation is tied to articulated critique and the formation of lay expertise. Drawing instead on Ernesto Laclau’s theory of antagonism and populist logic, we propose an alternative analytical lens. In this perspective, conflict is not necessarily organized around shared objects of dispute, but around the construction of political frontiers through which heterogeneous grievances are articulated against a common adversary. Empirically, we analyse 1,148,092 comments posted on 4,244 TF1.info YouTube news videos (March 2022–May 2024), comparing AI with electric vehicles, nuclear technologies, and climate change, and mapping intersections with party-political publics. While quantitative measures suggest weak AI issue-public formation, qualitative analysis reveals predominantly vertical antagonism targeting elites and institutions. AI functions less as a technical object of debate than as a symbolic condensation of institutional power.

Online health communities (OHCs) are conventionally recognized as information commons for mutual exchange among peer users with similar health concerns. Extant research reckons that engagement patterns universally conform to implicit norms guided by social exchange; that is, when a topic owner (i.e., user who initiates a topic thread) receives replies from peer users, they are said to acquire social support. This overlooks topic hijacking, a prevalent phenomenon where peer users solicit instead of providing support to topic owners. Drawing on the territoriality theory, we conceptualize that OHCs, as a form of health information commons, accommodate the emergence of personal territories when a user initiates a topic for support seeking. We posit topic hijacking as territorial infringement, and theorize a fight–flight–flex response framework for topic owners who experience topic hijacking, as well as the contingency of hijacking competitiveness on responses. Using data from 368 topics in an OHC, we develop measures of hijacking and hijacking competitiveness (competitive vs. complementary). Regression analyses attest to our research hypotheses that hijacking triggers (i) defensive responses at both the topic owner territory and community levels, including fight (marking self-presence) and flight (disengagement), and (ii) expansive response at the community level manifested by flex (subsequent hijacking of other topic owners’ territories). Moreover, competitive hijacking intensifies defensive responses, while complementary hijacking fosters territorial expansion. This study advances the OHC literature by recognizing topic hijacking as territorial infringements disrupting topic owner engagement, introducing a novel fight–flight–flex framework that captures both defensive and expansive responses, and identifying hijacking competitiveness as a boundary condition discerning defensive versus expansive responses to hijacking. Our findings offer implications for platform governance by showing how different hijacking forms may disrupt or enhance community vitality.

Emerging Internet of Things (IoT) technologies are transforming everyday practices of security in ways that extend beyond communication and discourse. This article introduces "tool media" as a new conceptual category to describe media technologies designed primarily for instrumental and operational purposes—such as surveillance, monitoring, and automated response—rather than symbolic human-to-human communication, yet which nonetheless mediate perception, decision-making, and social meaning. Focusing on IoT-based home security systems as a theoretically rich case, the article examines how tool media reconfigure the cultural meaning of protection by shifting emphasis from armed readiness toward prevention, surveillance, and delegation to technological systems. Drawing on media theory, science and technology studies, and scholarship on gun culture and surveillance, the analysis explores the implications of this shift for American gun culture and Second Amendment discourse, highlighting processes of cultural fragmentation and demographic differentiation. The article further examines how tool media introduce new tensions related to privacy, algorithmic authority, and civil liberties through the privatization and normalization of surveillance. By foregrounding non-discursive forms of mediation, the article argues for expanding media theory beyond content and representation to account for the growing influence of operational technologies on law, governance, and everyday life.

In Australia, governments fund Community Legal Centres (CLCs) as part of the legal assistance sector (LAS) to meet the ‘legal needs’ of people experiencing disadvantage who cannot afford private legal services. Persistent unmet demand for CLCs is well-documented. To increase access to justice, the sector has been a long-time adopter of once-revolutionary innovations, like video conferencing. As artificial intelligence (AI) is increasingly used in private legal practice to increase productivity and profits, some parts of the LAS are also exploring AI use cases. This article asks: What do we know about CLC clients and how services are currently delivered to meet their needs? What must we consider about client capabilities to ensure AI technologies are appropriate in the context of CLC service delivery? The research includes a review of policy documents, peer-reviewed research and grey literature, and secondary analysis of empirical data on how client capabilities contribute to the legal needs of CLC clients. We show in the article that the three-dimensional nature of legal need, a client’s capability and ability to self-assist, structural inequalities and current CLC service delivery models are vital considerations when developing AI tools to increase access to justice.

Frontier AI Safety Policies concentrate on prevention—capability evaluations, deployment gates, usage constraints—while neglecting institutional capacity to coordinate responses when prevention fails. We argue this coordination gap is structural: investments in ecosystem robustness yield diffuse benefits but concentrated costs, generating systematic underinvestment. Drawing on risk regimes in nuclear safety, pandemic preparedness, and critical infrastructure, we propose that similar mechanisms—precommitment, shared protocols, standing coordination venues—could be adapted to frontier AI governance. Without such architecture, institutions cannot learn from failures at the pace of relevance.

Our transition to a low-carbon future critically depends on technologies to mitigate climate change (CCMTs). These include renewable energies, carbon capture, utilisation and sequestration (CCUS), and electric vehicles. As many of them are still evolving technologies, they will likely present novel crime and security risks. Unfortunately, knowledge about such risks is still limited and fragmentary. This scoping review aims to bridge this gap and inform policymakers to prevent such emerging risks. We found 97 relevant articles from a total of 1139 references we screened from academic and non-academic sources across disciplines. They revealed 20 distinct crime threats of six different natures: property offences, cyber-attacks, financial crime and corruption, environmental threats, human rights abuse, and national security threats. Notable examples of criminogenic situations are CCUS-related environmental threats, greenwashing, and territorial conflicts over “green projects” that require adequate future crime prevention strategies. To that end, we also found 22 (potential) countermeasures, mostly of a legal or policy nature. This comprehensive overview highlights what appears to be an under-researched aspect of sustainable development, which we believe should include ensuring safety and security throughout climate mitigation supply chains.

Homophily, the principle that similarity breeds connection, shapes network formation across diverse social systems, from scientific collaborations to online communities. While this phenomenon profoundly influences how information flows, how communities form, and how opportunities distribute within networks, classical growth-based models typically lack general mechanisms for incorporating it. This paper presents a computational framework that bridges this gap. Through a retry-based wrapper algorithm, we augment any growth-based network model with homophilic bias while preserving its original selection mechanisms. The framework remains agnostic to both the underlying growth model and the similarity function, requiring only a measure of node similarity. Its efficiency is guaranteed through bounded retry counts, making it practical for large-scale network generation. Validation using the Barabási-Albert and Holme-Kim models demonstrates successful incorporation of statistically significant homophilic patterns. In our experiments, these variants preserved their characteristic properties - power-law distributions for both models and clustering coefficients for Holme-Kim. The extended Holme-Kim model is particularly valuable for social network research, combining scale-free topology, high clustering, and homophilic attachment. The framework provides a systematic method for incorporating arbitrary bias functions into network models, advancing our ability to study complex social systems computationally.

Intensifying climate change poses growing challenges for socio-economic stability and rural livelihoods in China, particularly in ecologically sensitive regions such as the Inner Mongolian grasslands. Although climate adaptation has become a key policy priority, translating national objectives into locally effective action remains complex. A central challenge lies in the emergence of adaptation lock-ins—self-reinforcing institutional, epistemological, and policy dynamics that stabilize specific adaptation pathways while limiting alternative responses. This study applies the adaptive lock-in framework to examine how such dynamics have developed within China's grassland governance and how they shape climate vulnerability and adaptive capacity over time. Focusing on interactions among political–economic structures, centralized decision-making, and subnational implementation, the analysis explores how adaptation goals become institutionalized through formal policies, administrative procedures, and dominant knowledge frameworks. The study draws on 207 in-depth interviews with pastoralists, village cadres, and local officials in Inner Mongolia, complemented by a systematic review of climate adaptation and grassland management policy documents issued between 2002 and 2024. The findings suggest that adaptation lock-ins are closely intertwined with broader development and conservation agendas that influence infrastructure investment, risk framing, and institutional practice. While these arrangements facilitate policy coordination and implementation, they may also constrain flexibility in addressing diverse local conditions. By elucidating the mechanisms through which adaptation lock-ins form and persist, this study offers policy-relevant insights into how future climate adaptation efforts might strengthen responsiveness and resilience within existing governance frameworks, with implications extending beyond the Chinese context.

This paper critically examines the development and transformation of civil society in Greece, particularly in the context of the economic crisis and its aftermath. Drawing on evidence from fifteen years of researching the sector by the author, which concluded in 2015, the article discusses the structural limitations, fragmentation, and evolving relationship between civil society organizations, the state, and market forces. The article highlights how NGOs became increasingly professionalized and co-opted into dominant political and financial frameworks, often at the expense of grassroots autonomy and democratic engagement. By interrogating liberal assumptions about civil society’s role in fostering democracy, the paper challenges conventional narratives and introduces the idea of “soft paternalism” to describe the state's strategic use of the third sector as a mechanism of control.

Social identities like class and religion are typically treated as stable antecedents of political preferences. This article shows that the causal arrow can also run in reverse: when exposed to narratives that pit immigrants against a discrete native social group, individuals can ‘update’ their identities to match their preferences over immigration. We theorise that anti-immigration individuals may claim membership of groups portrayed as threatened by immigrants as a form of instrumental belief justification: adopting this identity allows them to ground out-group aversion in concern for in-group interests. We test this framework with two original survey experiments: one on class identity in Britain and one on Christian identity in Italy. When primed with narratives framing immigration as a threat to the British working class or to the role of Christianity in Italian culture, respondents with anti-immigration preferences become more likely to claim working-class and Christian identities. In the British case, we also find evidence that pro-immigration individuals dis-identify from the working class when exposed to the treatment. These identity updates are driven by respondents who lack ‘objective’ markers of group membership (i.e., middle-class Britons and non-church-going Italians). They are also not reflected in changes in support for policies benefiting these groups, underscoring the instrumental nature of individuals' responses to these narratives. Overall, the findings speak to the literature on cleavage realignment, suggesting that when political actors strategically link immigration to ‘old’ dimensions of political conflict, traditional categories of politics such as class and religion acquire new meanings in people's minds.

Background. Food insecurity is associated with depression. Food insecurity involves distinctive patterns of dietary intake, and recent evidence suggests that dietary intake affects mood. Thus, an important pathway from food insecurity to depression may be via dietary changes. Methods. We studied two observational datasets (one from the UK, and NHANES 2017-8 from the USA) with measurements of food insecurity and affective state, plus dietary data from 24-hr food recalls. We examined variables concerning dietary composition and intake timing, as well as affective state, by food-insecurity status. Results. In both datasets, people experiencing food insecurity had significantly worse affective states. They showed dietary differences, notably more meal skipping, less regular timing of the first meal, and lower dietary diversity. A set of dietary variables (meal irregularity, night eating, dietary diversity, fruit and vegetable intake, and protein intake) partially mediated the association between food insecurity and affective state, accounting for 23% and 6% of the total association. Discussion. Dietary intake represents one pathway via which food insecurity can negatively affect mental health. Our findings suggest that while dietary intake plays a role in the association between food insecurity and poorer mood outcomes, it does not predominate.

The identification of the occupants of the Royal Tombs beneath the Great Tumulus at Vergina remains one of the central problems in Macedonian archaeology. Recent bioarchaeological and radiocarbon analyses have excluded Tomb I as the burial of Philip II of Macedon, removing the osteological and chronological basis for the traditional attribution and leaving Philip’s resting place unresolved. This paper proposes an integrative reinterpretation of Tomb II as either the primary cremation or a secondary monumentalized burial of Philip II, constructed or refurbished during the political reorganization of Macedonia following the death of Alexander the Great. We argue that the tomb’s cremation rites, exceptional monumentality, dynastic iconography, equestrian sacrifices, and elite military regalia correspond more closely to the commemoration of a foundational warrior king than to the historically marginal reign of Philip III Arrhidaeus. Situating Tomb II within broader Greek traditions of heroization, secondary burial, and dynastic legitimation, the model explains the archaeological and historical evidence with fewer assumptions and generates testable predictions for future research.

The Tripartite Perception of Race Theory (TPRT) advances a new theoretical framework for explaining how racial perception structures interracial interaction. Rather than treating anxiety, threat, or prejudice as primary explanatory endpoints, TPRT conceptualizes racial perception itself as the foundational mechanism organizing communicative experience prior to interaction. The theory specifies three analytically distinct but interrelated perceptual dimensions—racial distinctness, racial inequality, and racial incompatibility—through which racial hierarchy and difference are anticipated, interpreted, and negotiated. Racial distinctness concerns perceived cultural and normative divergence; racial inequality captures perceived hierarchical asymmetry and status differentiation; and racial incompatibility reflects beliefs about the feasibility of constructive cross-racial engagement. By formalizing these dimensions through a set of propositions, TPRT articulates how perceptual orientations shape communicative expectations, participation, and avoidance, particularly in contexts marked by historical and structural inequality. The framework reorients race and communication scholarship from outcome-centered models of anxiety and threat toward a perception-centered account that links macro-level racial structures to micro-level interactional processes. Although developed within the domain of interracial communication, TPRT offers a generalizable analytic structure for examining how perceptions of social difference condition interaction across diverse intergroup contexts. In doing so, the theory provides an empirically falsifiable and conceptually integrative foundation for understanding how race is anticipated, enacted, and reproduced in everyday communicative life.

Food insecurity (FI) in high income countries has become a major focus of academic and policy concern. FI is prevalent, and is consistently associated with poor physical and mental health outcomes. These associations are attenuated but not eliminated by controlling for more general social determinants, with which food insecurity is correlated. Though it is clear that the associations exist, it is less clear why. In this paper, we review four possible pathways between FI and poor health: (A) FI is a non-causal correlate of general deprivation and disadvantage; (B) FI causes poor health, but this is not mediated by diet; (C) FI causes poor health by changing what people eat; (D) FI causes poor health by changing the temporal patterning of their eating. These pathways are not mutually exclusive and we suggest that several play a role. Understanding their relative importance is nonetheless an important goal if we wish to intervene effectively to mitigate the health burden of FI.

How do minority communities move away from places they have inhabited for generations when departure is never consciously chosen? This article examines the livelihood practices of Kashmiri Sikhs, a long-settled micro-minority in the Kashmir Valley, to argue that migration can unfold as a slow, cumulative process driven by the gradual exhaustion of everyday endurance. Drawing on longitudinal ethnographic engagement with Kashmiri Sikh households conducted across multiple phases between the mid-2010s and early 2020s, the article traces how financial uncertainty under conditions of protracted political instability reshapes the temporal horizons, moral obligations, and bodily risks through which staying is sustained. Livelihood is analysed here as ethical practice: earning, saving, commuting, and investing are shown to be the sites where political instability, communal vulnerability, and institutional unpredictability converge and must be managed at the household level. Three ethnographic scenes examine how this ethical labour operates across small-scale entrepreneurship, intergenerational household geographies, and state employment. The article introduces the concept of slow migration to describe an incremental, ethically structured form of movement that differs from both crisis-driven displacement and aspiration-led mobility. Slow migration involves no singular decision point. It emerges through accumulation, when the work required to remain in place exceeds what financial life can sustain. By foregrounding livelihood as the medium through which minority endurance is produced and eventually strained, the article contributes to anthropological scholarship on ethics, precarity, and migration in South Asia.

Background Rising numbers of youth are living with chronic conditions that require sustained engagement with healthcare during a period of increasing expectations for autonomy. Communication is central to supporting their health literacy, participation, and transition to independent self-management. This scoping review synthesises evidence on how adolescents and young adults with chronic conditions experience communication with healthcare providers and what they need and value in these interactions. Methods Scopus, PubMed, and PsycINFO were searched for eligible peer-reviewed studies that reported on communication experiences of young people aged≥11 with chronic illness. Data on communication-related findings were extracted and synthesised using reflexive thematic analysis. Results Fifty-one publications met inclusion criteria. Across approximately 3073 young people, key communication needs centred on trust, autonomy, health literacy, and psychosocial support. Trust was strengthened by continuity of care, clear introductions, showing genuine interest, empathy, and respect. Youth valued being listened to, taken seriously, and involved in decisions; however, many reported limited opportunities to participate meaningfully, especially those from historically marginalised groups. The literature suggested that parental involvement could both support and inhibit engagement, underscoring the need for gradual, collaborative transitions. Significant gaps were identified in condition-specific and system-level health literacy. Psychosocial concerns strongly shaped communication needs. Young people wanted proactive discussions about sexuality, fertility, alcohol, and drug use. Observational research was scarce. Conclusion Trusting, person-centred relationships and proactive, developmentally appropriate communication are essential to support youth engagement and autonomy in clinical care. More observational research is needed to understand how best to support youth in healthcare interactions.

Microenterprises in Ghana are run mostly by people in the informal sector. These entrepreneurs often lack the skills needed to start a small business. As a result, most of the businesses they start up often collapse or cannot stand the test of time. The future of Ghanaian microenterprises should move away from a try-and-error approach and adopt a systematic approach. The study focused on how a model small Ghanaian business should be structured to ensure its sustainability. Important aspects of the microenterprise model, such as the composition of a new microenterprise system, including the microenterprise planning stage, the capital stage, and the execution stage, were considered. The research also considered how an entrepreneur can systematically save to enable him or her start a microenterprise venture in Ghana. This study, through a questionnaire survey, investigated entrepreneurs' awareness of starting microenterprises in Ghana and the success of those new startups, analyzing whether they have a future. The study also ascertained the difficulties entrepreneurs encounter in accessing financial support for their startups. The study revealed a low level of awareness among entrepreneurs about how to properly start a microenterprise and ensure its sustainability. Most Ghanaian entrepreneurs enter into microenterprises because there are no jobs. They lack the basic understanding of microenterprises and are unable to sustain their businesses. A number of specific action areas have been identified to proactively educate microenterprises in Ghana to ensure their sustainability.

This study sought to examine the relationship between borrower psychology or behaviour, the intended purpose of loans, and credit repayment performance. The methodology used was a cross-sectional survey design, with a sample of 800 respondents selected using purposive and simple random sampling. Self-administered questionnaires were used to collect data, which were processed and analyzed using the Statistical Package for the Social Sciences (SPSS V22.0.0). The findings showed significant positive correlations between borrower psychology or behaviour, intended purpose of loans and credit repayment performance which implied that the way borrowers behaved during credit accessibility or after acquiring credit from or even before taking the loan from the bank, had a lot of effects on how borrowers use the money acquired from the bank which would in turn affect effectiveness and efficiency of credit repayment. From the regression analysis, it was apparent that borrower psychology or behaviour was a strong predictor of credit repayment performance; therefore, the management of credit institutions should put a lot of emphasis on the training of loan officers to enable them screen prospective clients well before giving them loans, since what they use the loans for affects how they repay the loans. Management should also let borrowers know the importance of using the loans for their intended purpose, since it is the business that repays the loan, not the borrower, as most people think.

Intersectional stereotype research has consistently found that stereotypes vary simultaneously across categories such as race and gender. Recently, studies have started to investigate the complex interplay of multiple (more than two) categories, with some finding that stereotypes are best viewed as based on independent categories. By contrast, other studies find that stereotypes are intersectionally complex, meaning that they result from unique combinations of categories. We fielded a harmonized factorial survey experiment across nine European countries (n = 20,339) in which respondents evaluated perceived warmth and competence of vignette profiles that varied on gender, sexuality, ethnicity, and religion. We find that while main effects account for 95% of stereotype variance, compared with 5% of interactions, single category stereotypes still show effect variation; sometimes to the degree that a negative stereotype turns positive. Our study shows that stereotypes are primarily explained by categorical effects, but with small but consistent intersectional effects.

Over the past decades, there has been major progress in our understanding of how adversity influences cognitive abilities and strategies. However, most of this research is based on raw performance, such as response times and accuracy. These measures are informative about decision-making outcomes, but tell us little about cognitive processes. In this paper, we argue that adversity researchers should draw more on computational modeling of decision making. We focus on the Drift Diffusion Model, a well-established model of decision making which quantifies the efficiency of information processing, response caution, response bias, and speed of stimulus encoding and response execution. This model allows adversity researchers to gain insights into the cognitive processes that are associated with adversity exposure. We focus on recent insights in two areas of decision making: executive functioning and explore-exploit tradeoffs. We conclude with future directions for the field.

A major issue with the use of accessibility measures in transport studies is that it is not clear how to define the level of accessibility that people should have, and below which they may not be able to function within society. Although there are myriad studies on the impacts of low or unequal accessibility, only a few have made efforts to specify which opportunities must be reachable, how much choice is required, or under what circumstances access should be protected. As a result, the boundary below which accessibility becomes socially inadequate is often left implicit. This paper provides the first theoretical framework for defining accessibility thresholds grounded in Sen’s Capability Approach, theories of freedom, and existing conceptual work on sufficiency and thresholds. We identify the capabilities that accessibility must support, classify the conversion factors that condition their realisation, and propose normative principles—informed by philosophical accounts of freedom—to guide where and how thresholds should be set. We then outline a practical sequence of steps enabling researchers and practitioners to adapt existing accessibility measures to reflect what people have reason to value. By making explicit the ethical commitments underlying accessibility thresholds, this framework supports more transparent, just, and context-sensitive evaluation of transport systems.

This paper examines the rise of housing populism---narratives that cast financial investors as predatory, demand investor bans, and frame housing as a fundamental social right requiring state protection. We argue that politicians embrace housing populism less because it reflects economic realities than because it resonates with public moral commitments: distrust of finance capitalism and support for housing as a collective entitlement. Using U.S. property-level transaction data (2012-2021), a difference-in-differences analysis finds no consistent evidence that investor activity increases housing costs. Yet original surveys reveal widespread, bipartisan beliefs that investors undermine the right to housing and that government should safeguard access. A candidate-choice experiment further shows that candidates advocating investor bans framed in rights-based or anti-elite terms substantially outperform those prioritizing home-building through pragmatic or market-oriented appeals. Housing populism channels social-rights claims into symbolic confrontations between ``the people’’ and financial elites, often displacing more effective policy responses.

Introduction Climate change and extreme weather events are increasingly recognized as major stressors on mental health, yet research in West Africa remains scarce. Guinea-Bissau, one of the world’s most climate-vulnerable Small Island Developing States (SIDS), faces intensifying extreme weather events, including flooding, heat, and sea-level rise, which intersect with poverty, political instability, and limited health infrastructure. This study investigates how environmental and socio-economic vulnerabilities associated with climate change influence the mental well-being of women engaged in rural-urban mobility. Methods Ethnographic fieldwork was conducted among 27 Balanta women living temporarily in zinc-roofed dwellings at two docks in Bissau. Data were gathered through semi-structured interviews, informal conversations, and participant observation, with oral consent. A narrative analytical approach was employed to examine lived experiences, focusing on climate-related exposures, psychosocial stressors, and collective coping mechanisms. Results Participants described heightened psychological distress manifested as fatigue, anxiety, and sleep disruption related to recurrent heat, humidity, heavy rainfall, and tidal flooding. Rain-related sleep deprivation and caregiving demands emerged as particularly salient stressors. Structural inequities, including economic precarity and lack of access to health services, intensified mental strain. At the same time, strong communal organization and the replication of familiar rural social structures in urban space functioned as protective mechanisms, mitigating isolation and fostering psychological resilience. Conclusion Findings underscore the compounded mental health risks faced by women engaged in rural-urban mobility while temporarily living in climate-exposed urban settings. Community solidarity operates as a key resilience mechanism, highlighting the need for integrated, gender-responsive, and community-anchored mental health and climate adaptation policies in Guinea-Bissau and comparable SIDS contexts.

Background: Despite miscarriages being common, little is known about who and to what extent people experiencing miscarriage resort to miscarriage care at the hospital. Methods: We analysed healthcare records from the French National Health Insurance Information System (SNDS) from 2015 to 2022. Descriptive analyses and logistic regressions estimated the trend in day (ambulatory) or longer (inpatient) miscarriage hospitalisation, and characteristics of those who received that type of care instead of primary care, emergency department visit, hospital external consultation, or no care. Results: On average, 44% of miscarriages identified in the healthcare records led to ambulatory or inpatient care, with a decrease from 44% to 41% before the COVID-19 lockdown, after which the trend increased again and stabilised. Those from precarious groups, undergoing infertility treatments, with underlying chronic conditions, prior history of miscarriages and births, between 35 and 45 years old, and those from rural areas, were more likely to be hospitalised. Conversely, those from urban areas and younger age groups were less likely to receive ambulatory or inpatient hospital care. Among these hospitalisations, financially precarious women, those with chronic conditions, and prior miscarriages, were also more likely to receive inpatient rather than ambulatory care. Conclusions: Ambulatory and inpatient miscarriage care decreased over time, which signifies a shift towards other types of care, or an increase in pregnancy losses managed outside the formal healthcare system. However, the decline levelled off after the onset of the COVID-19 pandemic. Those with underlying conditions and prior miscarriage(s) may more often experience complications and therefore seek (inpatient) hospital care, or have more monitored pregnancies, leading to planned interventions at the hospital. The greater likelihood of receiving (inpatient) hospital care among those living in rural areas may reflect challenges in accessing primary care due to limited availability of practitioners. Similarly, the greater (inpatient) hospitalisation rates among financially precarious women raise concerns about potential barriers to timely miscarriage care and more complications. Improving miscarriage care should involve addressing access barriers, counselling, and potential interventions for groups with specific needs when receiving formal healthcare for a miscarriage.

Bol and van de Werfhorst’s article published in 2013 represents a milestone for researchers studying the effect of educational institutions on micro-level outcomes. In the above-mentioned article, tracking and other concepts, like vocational enrolment and vocational specificity, have been operationalized into numerical indicators and then used in regression models in order to establish their associations with individual outcomes. This article points out that Bol and van de Werfhorst’s analyses contain two errors. First, their model specifications disregard the role played by a confounder i.e., political orientation of policy makers. Second, their analytical strategy does not adequately correct for the fact that the dependent variables are estimated. I replicate their analyses regarding social inequality of educational attainment (OE) and educational gradient in occupational attainment (ED) correcting for both errors. These new findings do not support the existence of a trade-off between labour market allocation and equality of educational opportunity when it comes to educational and occupational attainment.

In pastoral communities, seeking animal health services for livestock is a male-dominated activity. Women are not always recognized as livestock keepers and face restrictions on interacting with men outside their households. This mixed-methods study qualitatively identified barriers to women's access to vaccines, tested a gender-accommodative intervention in a Rift Valley fever vaccination campaign serving 909 households, and assessed impact on women’s decision-making, financial contributions, and number of livestock vaccinated. In half of the vaccination sites, local government implemented co-designed interventions to improve communication with women. There was no improvement of the target indicators, indicating the intervention was insufficient to address barriers like restrictive gender norms and safety concerns. About half of women reported contributing financially to the vaccination of animals in their households and were more likely to contribute when the household heard about the vaccination campaign through word of mouth, suggesting that informal communication motivated women’s support for vaccination.

The social costs of climate change are of global interest, as vulnerable populations face new or heighted environmental stressors. Previous research has documented many social consequences of environmental change, but several important outcomes, including child marriage, remain underexplored. We address one of these gaps by examining the relationship between climate shocks and early marriage in Mali, a country where weather extremes are common and rates of child marriage are high. We draw on three decades of marriage records (1986-2016) from the Demographic Health Surveys (n=117,170 person-years), combined with high-resolution climate data. We measure overall climate impacts on early marriage and evaluate spatial differences across rural and urban areas, northern and southern Mali, and environmental conditions. Across the full sample, cooler than average temperatures reduce the probability of child marriage, while precipitation shocks show no statistically meaningful effect. However, the effects of climate conditions vary spatially. Linear models show that the marginal effect of very high rainfall increases child marriage for girls living in urban areas and northern Mali. In addition, exposure to very cold and very dry conditions predicts marriage before age 18. Overall, our findings point to meaningful but complex relationships between climate variability and child marriage, in which precipitation and temperature exposures can increase or decrease marriage risks, underscoring the need for more research on understudied populations and spaces affected by climate change.

Low- and middle-income countries host nearly three-quarters of the world’s refugees, yet research on refugee stereotypes and their social consequences remains heavily concentrated in high-income settings. This imbalance obscures how stereotypes operate in countries where refugees lack legal recognition, where welfare and labor protections are limited, and where public attitudes significantly shape the conditions of daily survival. Malaysia, home to almost 200,000 refugees despite not being a signatory to the 1951 Refugee Convention, offers a critical context for examining these dynamics. This study analyzes six focus group discussions with 47 Malaysian participants to assess the content, sources, and implications of refugee stereotypes in a developing-country setting. Using inductive content analysis of 382 excerpts, we identify a wide range of both positive and negative stereotypes, with self-generated opinions emerging as the most common source. Mapping these perceptions onto the Stereotype Content Model, developed by Fiske et al. (2002), reveals nuanced combinations of perceived intentions and capabilities that underpin both empathy and hostility toward refugees. These stereotypes, when reinforced through prejudice, discrimination, and stereotype threat, erode refugees’ sense of belonging and constrain long-term socioeconomic outcomes. Yet, the predominance of self-held rather than socially attributed stereotypes suggest meaningful opportunities for change. We argue that developing-country contexts such as Malaysia require tailored interventions that leverage media narratives, counter- stereotypical representations, and low-cost intergroup contact to shift public attitudes. By centering a middle-income host country, this paper underscores the urgent need to address stereotype-driven barriers to refugee well-being in the places where most displaced people reside.

We develop a demographic theory of similarity-biased social learning that formalizes our understanding of when and why individuals should preferentially copy others that look or act like them. We build an evolutionary model in which individuals can either learn on their own or copy others from a demonstrator pool that contains varying proportions of in-group and out-group members, and where group tags can be more or less informative about local knowledge. We find that where social learning becomes common, selection favors copying biases that track the direction of informational advantage---toward the group that tends to be better adapted to local conditions, including an anti-similarity bias when tags are negatively associated with local correctness (as may be the case for some immigrant communities). We also find conditions in which a similarity bias can stabilize social learning when such learners are already common, but not when they are rare, with implications for the role of group identities in cultural evolution. We discuss implications for understanding parochialism as risk aversion, majority-minority dynamics, the sociology of immigration, and the lasting impacts of colonialism.

This article develops composition theory as a pragmatist specification of the mesosocial. Existing theories describe situated social life without adequately explaining the mechanisms that produce it. Recent pragmatist scholarship has established important foundations: Gross on mechanisms, Lizardo on habit, and Hallett on inhabited institutionalism. Yet the mechanisms themselves remain underspecified. Composition theory fills this gap through four sets of mechanisms: composition, engagement, sedimentation, and circulation. Together, these explain how problem responsive actors assemble formations, how formations become consequential as affordances meet capacities, how residues accumulate over time and how patterns extend across settings through movement and echoing. The article reinterprets Dewey's concept of situation as the flow of actors' transactions with and within their present place (relational, symbolic and material environment) while remaining cognizant of their direct and indirect experiences with other places. Place is the somewhere somewhen locatable environment that necessarily grounds each situation and social reality as such. The framework reconceptualizes microsocial, mesosocial, and macrosocial as a continuum of compositional complexity anchored in the mesosocial. It expands the range of theory-driven research questions by directing attention to processes within and across places of action rather than to the forces of abstract structural properties.

A handful of individuals control social media platforms that collectively reach billions. Does this control give those owners influence over their platforms' users? To investigate this question we study the acquisition of Twitter by Elon Musk in October 2022. Musk changed Twitter from a predominantly liberal platform to one favored by conservatives. Using panel survey data on over 8,000 respondents and 145 survey questions, we find that the issue preferences of pre-acquisition Twitter users became more conservative post-acquisition. Twitter users moved right on economic and social issues -- especially racial issues -- but not on climate, an issue where Musk is less conservative. Republican Twitter users became more pro-Republican, but there was no aggregate move toward the Republican Party, in part due to backlash by strong Democratic partisans who left the site. Social media platforms empower their owners to persuade and polarize, but this power is constrained by which users choose to remain on the platform.

Research shows that children with similar levels of cognitive ability experience markedly different educational outcomes. This paper examines how innate abilities (measured using a polygenic index for cognition) and social origins (understood as different forms of family economic, educational, and sociocultural resources) interact to shape academic performance across primary and secondary education in England (ages 7 to 18). Drawing on data from the Millennium Cohort Study linked to the National Pupil Database, this study asks whether social origins moderate the association between genetic traits and academic performance, and whether the strength and direction of this moderation varies across educational stages. The findings show that gene-by-social origins interactions operate differently across levels of academic performance, becoming most evident at the tails of the performance distribution. At the lower tail, students from socioeconomically advantaged backgrounds are largely protected from low achievement regardless of their genetic traits, producing a ‘glass floor’ consistent with the Compensatory Advantage hypothesis. At the upper tail, genetic advantages translate into high performance primarily among students from advantaged backgrounds, creating a ‘glass ceiling’ for disadvantaged students in line with the Boosting Advantage hypothesis. These compensatory and boosting patterns operate consistently across educational stages: social origin gaps are already evident at the start of primary school and remain broadly stable throughout academic trajectories. Overall, this study demonstrates that the realisation of genetic propensities is strongly context dependent and points to a pattern of talent wastage, whereby high-ability students from disadvantaged backgrounds are less able to fulfil their potential within the British education system.

Scholars writing about the interface between qualitative and computational methods have rightly focused on machine learning. But computation can also change qualitative fieldwork in quieter ways, through scrapping, parsing, optical character recognition, archiving, and zooming. This paper situates computational methods within a wider digital era and argues that they entangle fieldwork spatially (by increasing its geographical reach), temporally (by accelerating research), and epistemically (by influencing what we can now). I show these kinds of entanglement by reflecting on my own comparative-historical study of Brazil’s decarbonization capacities, which was conducted within a Ph.D. structured by COVID-19. Before the lockdown, fieldwork relied on direct observation and interviews with environmental fieldworkers and policymakers. During lockdown, computation provided continuity: web scraping, archival digitization, and machine learning substituted travel and extended the field in time and space. After restrictions eased, these computational results were reintroduced into interviews through visualizations that prompted important findings but highlighted blind spots.

This article aims to contribute to a relatively understudied area of financial development, namely, the internal dispersion of trading activity. The focus is not on overall financial development measures such as total market capitalization and liquidity but rather on trading diversification, defined as the proportion of trading volume contributed by firms outside the VTX, representing the top ten most frequently traded firms. The article uses data from the World Bank’s Global Financial Development Database. The sample is constructed as a balanced panel of 23 countries over the period 2002-2021, starting with a sample of 38 countries. The article uses four key explanatory variables, namely, relative size of deposit-taking banks (DBS), remittance inflows (REM), market capitalization excluding the top ten firms (MCX), and outstanding international public debt (IPU). The article uses a combination of panel econometrics, hierarchical clustering, and machine learning methods. The econometric results show that a diversified financial system structure and remittance inflows are strongly, positively related to overall and less concentrated trading activity, while bank dominance and reliance on international public debt are related to more concentrated trading activity. The clustering results show significant cross-country heterogeneity and a core-periphery structure. The machine learning results show that, using all models, equity market structure is again found to be the most important explanatory variable, with external financial flows being important as well. The article concludes that equity market structure is key to understanding internal dispersion, with important policy implications.

With increasing concerns around food sustainability, estimating the environmental footprint of diets is critical. Supermarket transaction data are becoming prominent as a valuable source of objective dietary purchase data. We developed a method to map environmental sustainability metrics to foods and beverages sold by a major UK supermarket, using sales data from the Yorkshire and the Humber region (2022). Products were mapped to global Greenhouse Gas Emissions (GHGE) estimates for 45 commodities in four stages. Initially, products were grouped into categories and linked to commodities. Subsequent stages disaggregated high-complexity or high-sales categories into subcategories with similar ingredients, using retailer categorisations (Stage 2) and word searches within product descriptions (Stage 3), and finally refined categorisations to aid interpretability (Stage 4). The product with the highest sales in each subcategory was selected as an indicator product and mapped to commodities using data on ingredient proportions. Land Use and Water Use estimates were generated using the final mapping scheme. A look-up tool was produced linking categories to environmental sustainability metrics for use with other food product data. By Stage 4, 98·6% of >27,000 products were mapped to GHGE, using 200 category/subcategory-based GHGE estimates. Disaggregation revealed significant variation in GHGE estimates: up to a three-fold difference between Stage 1 and 4 estimates for the same category, and up to a 30-fold difference between subcategories within the same category. Disaggregation of complex categories is important for accurate estimation of sustainability indices. Our sales-guided approach balances accuracy and efficiency when dealing with large supermarket data and could support a wide range of research into sustainable diets.

Whether through red-pill conspiracy narratives or hashtags such as #FemininityNotFeminism, anti-feminism is widespread on social media platforms. This paper contributes to the research on women anti-feminist influencers within digital public spheres. While previous studies have identified various actors within the so-called 'manosphere', such as Incels or Pick-up-Artists, we still know little about women's involvement in (online) anti-feminism. This qualitative study aims to shed light on the global phenomenon of women anti-feminist influencers on visual social media platforms by developing a typology of women anti-feminist influencers on TikTok and Instagram. The study uncovers that women anti-feminist influencers adopt different roles such as political commentators, dating-coaches, and TradWives, among others, to disseminate their beliefs. The findings point to the unique role that women play as influencers within contemporary (online) anti-feminism, contributing to our understanding of this occurrence.

There is currently no widely accepted framework to guide decision-making for preventive approaches using genetic and genomic technologies. In the context of the PROPHET project, we developed a multidimensional framework integrating Health Technology Assessment (HTA) and Health Impact Assessment (HIA), complemented by a monitoring phase to assess the impact of policies implementing personalised prevention interventions. This integrated approach links technical, clinical, and societal dimensions, supporting prevention strategies that are effective, equitable and sustainable. The PROPHET framework supports policy makers in the equitable and efficient implementation of personalised prevention policies at scale.

BACKGROUND Young adulthood is characterised by the occurrence of many life events, the outcomes of which have long-term repercussions throughout the life course. Parental influences are known to be key to young adults’ life courses. Yet, young adults spend much of their time with siblings and school peers (particularly classmates), whose influences might complement or counterbalance parental influences. OBJECTIVE We review the literature on the roles of siblings and school peers in the occurrence, timing, and outcomes of important life-course events that tend to occur frequently in young adulthood: Leaving the parental home, returning home, entry into tertiary education, residential relocations, partnership formation and dissolution, and the transition to parenthood. We then present an agenda for research that aims to identify and disentangle the roles of siblings and school peers in these life-course events using longitudinal register micro-data. We intend to carry out parts of this agenda over the next few years and have initiated the work on it. We also pay attention to methodological issues associated with the envisaged research. CONTRIBUTION We provide (1) a review of the literature on the important but under-researched topic of the roles of siblings and peers in young adults’ life-course events, and (2) an agenda for research on this topic, which includes a preview of our own ongoing and future work in the context of two research projects.

The "Optimistic Consensus" suggested that fertility would recover at high development levels. We test this hypothesis using panel data from 161 countries (1990–2023, N=2,989) and find no evidence of J-curve recovery. Instead, wealthy democracies converge on a synchronized fertility decline toward a total fertility rate of 1.3–1.5 as of 2023—persistently below replacement. We construct a "Modernity Index" via principal components analysis of education, gross domestic product, and urbanization, and then estimate interaction models with cluster-robust standard errors. Modernity emerges as the primary predictor of fertility decline (β=-0.68, p<0.001), consistent with prohibitive opportunity costs that fiscal transfers cannot offset. Democracy shows no independent main effects but significantly moderates modernity's impact through an interaction term (β=+0.48, p=0.020): at high development, stronger democratic institutions correlate with marginally higher fertility. Robustness analysis with larger samples (N=5,589) strengthens these findings. Israel constitutes a statistically identified exception due to religio-cultural forces. We formalize these constraints as the "Liberal Trilemma": advanced societies struggle simultaneously sustain meritocratic education, demographic continuity, and economic growth. Policy implications are stark—even pro-natalist spending achieves TFRs 20–30% below replacement, confirming that transfers address direct costs but have not reversed structural decline.

This paper examines how exogenous economic shocks shape electoral accountability in local elections. We develop a theoretical framework in which a sudden increase in household income temporarily boosts support for incumbents, even when the shock is unrelated to their actions. As voters gradually update their expectations, however, the incumbent’s advantage fades. We test the model’s predictions using Brazil’s 2003 legalization of genetically engineered soybean seeds, a policy that triggered uneven productivity gains across municipalities due to variation in climate and soil. Leveraging this quasi-natural experiment over the 2000–2020 period, we show that incumbent mayors were more likely to be reelected in municipalities with larger gains in soy productivity --- but this advantage was short-lived. Our findings highlight how misattribution and voter learning jointly shape the political consequences of economic change in developing countries, where structural reliance on commodity exports increases vulnerability to external shocks.

The polarized reaction to the assassination of UnitedHealthcare CEO in December 2024 underscored the potential of ideologically framed acts of violence to undermine societal cohesion and challenge democratic norms. While many condemned the killing as an unjustifiable attack on a private citizen, others celebrated Mangione as a “folk hero,” glorifying him and his act as a symbol of resistance against an industry perceived as corrupt and dehumanizing. Using data from a rolling cross-sectional survey in the U.S., we causally tested partisan differences in support for political violence before and after the CEO’s assassination and the perpetrator’s subsequent arrest. While Democrats initially condemned violence against Republicans, their support for partisan violence increased following Mangione’s arrest. These results underscore the role of public discourse in shaping attitudes towards political violence, raising concerns about the normalization of politically motivated aggression, even among groups traditionally less inclined to endorse it.

In the last decade, an important literature in the social sciences has examined public attitudes toward immigrants in host societies. In it, a prominent experimental method---the conjoint design, where participants are tasked with rating or choosing between randomized profiles---has been used reliably to understand how immigrant characteristics shape admission preferences. We collate replication datasets from 100 individual studies spanning 1,475,403 immigrant profiles with 26 randomized attributes evaluated by 142,817 survey respondents from 36 countries. Meta-analyses reinforce well-established findings: economic, cultural, humanitarian, and procedural factors all influence evaluations. Meta-reanalyses show that preferences are broadly similar across countries and demographic groups. However, they also reveal two additional patterns: economic considerations have become more influential over time, and evaluations of individual immigrants differ sharply depending on where people stand on the broader immigration debate. These findings shed light on ongoing debates and point to fruitful areas for future research.

We present a dynamic, stochastic, and spatial model that incorporates disaster risk to study the role of local aggregate risks and moving frictions in the spatial economy. A disaster temporarily reduces regional productivity and suspends transportation networks. The model is applied to the analysis of Japan’s Tokai Trough Earthquake (TTE) and maglev train project. Estimation is based on sufficient statistics of future expected values by future migration flows and novel data on rail network disruption from the 2011 Tohoku earthquake. The TTE risk reduces welfare not only in vulnerable regions close to the expected epicenter but also in more distant regions, revealing the regional spillover effects of the disaster risk. The maglev train project increases welfare by 1.6\% on average, with effects that are larger in the north-east regions under the economy with TTE risk, highlighting the distributional effect under the disaster risk.

Education and public engagement are increasingly recognized as essential levers for biodiversity conservation. Over the past decade, biodiversity-related education and engagement initiatives have expanded considerably, yet their evaluation remains fragmented and methodologically uneven. This diversity complicates assessments of effectiveness, comparability, and long-term conservation relevance. We conducted a scoping review of peer-reviewed empirical studies published between 2015 and 2025 to examine how evaluation practices are designed, implemented, and reported in biodiversity-related education and engagement initiatives. Following PRISMA-ScR guidelines, 74 articles were selected from the Web of Science Core Collection and analyzed in terms of implementation contexts, target publics, educational practices, evaluation objectives, methodologies, temporalities, reported outcomes, limitations, and levers. The review reveals a strong concentration of evaluations in formal education settings, primarily targeting children and young people. Objectives are largely structured around the knowledge–attitudes–behaviors (KAB) framework, with limited attention to competencies, empowerment, collective processes, or ecological outcomes. Most studies rely on short-term, self-reported quantitative measures, while longitudinal, qualitative, participatory, and process-oriented approaches remain underrepresented. Although experiential, place-based, creative, and participatory practices are identified as promising levers, their impacts are rarely assessed beyond immediate individual-level outcomes. Overall, the findings expose a structural tension between the diversity of biodiversity education practices and the absence of shared, integrative evaluation frameworks. Advancing evaluation in this field requires systemic, reflexive, and multi-scalar approaches linking individual learning, collective action, institutional change, and conservation outcomes. Such a shift is essential to strengthen the contribution of education to conservation and to support more robust, cumulative, and policy-relevant evidence.

This paper proposes a science governance framework based on the research values of openness and mutual responsiveness. It reviews the efforts made since Merton and addresses the current shortcomings and misleading open science practices

Women, and especially mothers, are overrepresented in part-time and low-wage jobs in Germany. Yet, little is known about how minimum wage floors affect the employment of childless women and mothers. We use a difference-in-differences design based on county-level variation in average wage levels to assess how the 2015 minimum wage reform in Germany affected the employment of 1) mothers and childless women, 2) mothers of pre-school and school-aged children, and 3) mothers in counties with low and high childcare availability. We contrast theoretical predictions from neoclassical economics and theories of gender norms to derive hypotheses. Using panel data from the German Microcensus (2014-2015) for West Germany, we estimate the impact of the minimum wage at the county level (N=324 counties) on women’s transition probabilities between inactivity, marginal, part-time, and full-time employment. Findings support that inactive mothers were more likely to take up marginal or part-time work after the reform, whereas already employed mothers tended to reduce their working hours, thus consolidating maternal marginal and part-time work. Childless women show little response to the reform. Overall, raising wage floors may reduce gaps in employment participation between mothers and childless women, but is unlikely to reduce gaps in employment intensity.

This study provides new evidence for the understanding of the consequences of family policies on poverty: we investigate if and to what extent higher childcare availability when the youngest child is aged 0-2 affects household poverty in subsequent years. Unlike prior cross-country research, we focus on within-country variation in childcare availability over 400 German counties using panel data from the Microcensus (2012–2019) linked to local childcare provision data. Our findings show a significant reduction in household poverty risk over and above the mediating role of maternal employment. This effect is notably stronger in Eastern than in Western counties. In Western counties, higher ECEC coverage is associated with poverty declines primarily for single mothers and mothers whose partners work non-standard jobs, while in Eastern counties mostly for mothers with partners employed in standard or non-standard jobs. Poverty risks decrease as children grow older for less affluent households regardless of childcare availability. We conclude that more childcare “today” does improve the economic wellbeing of households with children “tomorrow”. We discuss policy implications arguing that more widespread and substantial poverty reduction cannot be envisaged via higher childcare availability only. This is particularly true in institutional settings promoting the “adult worker model” for mothers against the background of persistent and large gender pay gaps and where the burden of reconciling work and care falls largely on mothers’ shoulders.

Objective This brief report examines German parents’ post-birth employment trajectories, highlighting gender differences in mismatches between work-hour preferences and actual employment. Background Previous studies on post-birth employment rarely considered work-hour preferences, while research on such preferences rarely takes a longitudinal perspective. We bridge these two literature streams by using a dynamic approach, illustrating how actual-to-preferred-hour mismatches evolve when the youngest child is aged 0-3. Method We apply multichannel sequence and fuzzy clustering analysis on data from the German Socio-Economic Panel (SOEP, 2008-2023), restricting our sample to 645 cohabitating couples. Next, we use Dirichlet regression to link the identified (fuzzy) patterns to individual, household, and contextual characteristics. Results Among mothers, mismatches between actual and preferred working hours increase as children grow older, with many mothers employed in short part-time jobs wishing to work more hours (i.e., underemployment), while most full-time working mothers would prefer to reduce their hours (i.e., overemployment). Among full-time working fathers, a substantial share feels either overemployed or satisfied with their current hours. Dirichlet regression reveals that among fathers, especially job characteristics are associated with overemployment, while individual characteristics and constraints are associated with longer-term preferences for inactivity among mothers. Conclusion Results highlight that overemployment and employment matched with preferences is much more common among parents than underemployment, leaving little room for reallocation of paid and unpaid work within couples.

The United States (U.S.) food system is governed by an extensive set of regulations that determines, in part, which foods reach consumers and how. Regulations play an important role in protecting public interests, such as environmental well-being, but their complexity and number are criticized for delaying innovation and increasing business costs. We explored how the regulatory landscape varies across U.S. food industries and compares to industries’ associated environmental impacts. We analyzed five decades of federal regulatory data from the Code of Federal Regulations (CFR) for 44 food industries across five food production sectors. We found that the total number of food system regulations has increased over time, with large disparities across individual food sectors. Since at least 1970, the aquaculture sector was annually subject to a greater number of direct regulations than any other food sector, on average. Aquaculture regulation originates from a larger number of CFR titles and federal agencies, and aquaculture is often subject to more regulations within each title and agency, than other food sectors. Our analysis identified several cases where food industries with smaller environmental impacts (e.g., greenhouse gas emissions, water use, land use)—including industries in the aquaculture sector—were subject to as many or more total regulations as food industries with larger environmental impacts. This pattern also persisted when comparing impacts only to the number of environmental regulations. While the number of regulations is only a proxy measure of regulatory burden, our results suggest that the U.S. federal regulatory landscape might disadvantage some lower-environmental-impact food industries and their products in the U.S. marketplace, especially aquaculture.

Eco-anxiety is gaining attention as a growing mental health issue. This phenomenon emerges due to perceived lack of control over ecological destruction, and is characterized by a spectrum of emotions, such as grief, anger, worry, uncertainty and hopelessness. However, eco-anxiety appears to affect more than one’s emotional state, with consequences for behaviour and engagement with environmental and societal issues. While existing mental health interventions such as Acceptance Commitment Therapy have been adapted and studied for addressing eco- anxiety with mixed results, there remains a gap in understanding and addressing the experiential dimension of this challenge. To address this gap, this study uses Interpretive Phenomenological Analysis to explore the lived experience of eco-anxiety and the impact of psychedelic experiences on coping mechanisms and meaning-making processes. In-depth interviews exploring individual accounts revealed that psychedelics could serve as transformative catalysts for eco-anxiety. Psychedelic experiences triggered shifts in worldviews and broadened perspectives, leading to a sense of interconnectedness of the self, nature and the universe. Furthermore, such experiences enabled emotional release and reconfiguration, further alleviating distress. Those emotional and cognitive shifts gave opportunities for new ways of understanding and responding to eco-anxiety, mitigating feelings of hopelessness and anger through adaptive environmental action. This study contributes to the current dialogue on eco-anxiety and offers insights into understanding how ecological distress and psychedelics interact, proposing psychedelics as transformative catalysts.

This study aims to examine the interrelated effects of finance structure, institutional quality, and macro-demographics on CO₂ emissions per capita in OECD countries from 2004 to 2021. Building on the conventional linear and aggregate nature of the finance–environment relationship, this study suggests an improved methodology based on a hybrid framework combining panel estimation, machine learning-based clustering, and nonlinear modeling. The empirical findings support a positive relationship between bank-based intermediation structure, represented by private credit and credit quality, and CO₂ emissions per capita, which could be explained by a scale effect. At the same time, a negative relationship is found between non-performing loans and CO₂ emissions per capita. In addition, a negative relationship is found between the assets of pension funds and mutual funds and CO₂ emissions per capita. This suggests a critical role played by long-horizon investors in offsetting the carbon footprint of economic activity. Government effectiveness is found to have a positive relationship with CO₂ emissions per capita. This could reflect development stage considerations rather than institutional failure. Finally, a weak positive relationship is found between population density and CO₂ emissions per capita. This supports scale efficiencies. The K-means clustering methodology reveals a strong structural heterogeneity in the finance–environment relationship. This supports the view that there are unique structural regimes in which similar CO₂ emissions per capita outcomes are influenced by a variety of interrelated finance structure and institutional quality drivers. In addition, the Random Forest methodology outperforms other machine learning techniques. This suggests a strong nonlinear nature in the finance–environment relationship. Finally, the empirical findings support a relatively stronger emphasis placed on structural finance structure and institutional quality variables rather than short-run macroeconomic variables in explaining variations in CO₂ emissions per capita.

Present-day mobility systems centered around automobility need transformative change to become just and sustainable. In these processes of societal transitions, citizen-led social movements are often theorized to be valuable actors, yet when it comes to mobility transitions, they have received little attention. We therefore investigate a prominent fifty-year mobilization of community activism against highway construction and expansion in the city of Utrecht, the Netherlands. The social movement to protect Amelisweerd forest is described in a historical narrative drawing on contemporary primary and secondary sources. We analyze the movement through its ability to exercise agencies for transition governance: how a highly localized movement attempts to support systemic change. Identifying destabilization, visioning alternatives, independent spaces, and reflexivity as key mechanisms, we demonstrate how activists have deployed each type of agency as required. The Amelisweerd case indicates that local social movements can build broad coalitions around alternative solutions through strategic adaptability, whose greatest obstacle is ideological entrenchment on the national scale. These transformative social movements and their potential obstructions are worthy of greater consideration in mobility transitions.

Immigration attitudes research is often centered on cultural and economic threat debates. However, this focus has missed an important mechanism that guides our everyday judgments: fairness. Very limited work has engaged with fairness and little has done so in the context of immigration. To address this, I construct a theoretically grounded method for measuring different dimensions of fairness. Using an original conjoint experiment, I test how varying state-level policy attributes such as eligibility requirements, intended beneficiaries, and assistance types influence perceptions of fairness. Agreement with different dimensions of fairness and policy support increase when policies include social services and exclusion criteria. I find limited evidence for xenophobic cultural threat and sociotropic economic threat in motivating policy support. The results offer a reevaluation of immigration attitude debates and demonstrate opportunities for broader use of a multidimensional measurement of fairness, as well as suggest a framework for democratically popular subnational immigrant integration policy design.

Cultures of shared governance in academia may appear as a noble tradition to be upheld and defended against the steady encroachment of audit culture. However, building upon recent interest in the ‘dark side’ of collegiality, this theoretically-motivated article proposes that the collegial ideal of collective and participatory decision-making now co-exist alongside performance metrics in an uneasy alliance that softens their surface-level opposition. Invoking the paradoxical concept of ‘participatory Taylorism,’ this study demonstrates that faculty engagement is essential to audit culture’s apparent staying power. Performance metrics survive by opening themselves to the demos, inviting robust debates about their composition and legitimacy – provided these dialogues stop short of contesting audit culture itself. In this sense, permissible modes of shared governance perform a type of ‘collegiality-washing,’ substituting a simulacra of participation for the real thing. Moreover, because ‘participation’ is precisely the lever through which performance measures exert their influence, conventional oppositional strategies risk co-optation. In a university setting that demands constant engagement and actively recuperates dissent, resistance may take the form of withdrawal, silence, or even a more recent trend, ‘quiet quitting.’

Open science is an increasingly important movement in contemporary social science. Many funders have begun to mandate open practices, newer journals like Socius are open access, and preprint servers have increased readership for paywalled articles. Feminist scholars have written about the values and pitfalls of open research. In this paper, we put those ideas in conversation with each other and empirical data on open access publishing to develop a feminist framework for thinking about feminist knowledge, data, publishing, and audience. Using a survey of 19,462 social scientists, linked with their entire Web of Science publication history from 2000 to 2023 and all papers posted to SocArXiv, we replicate past work showing that articles by women are less likely to be some types of open access. We extend these findings to scholars of color and feminist scholarship, while also demonstrating a few surprising null results for all three groups.

The MLCVI R package implements tools for cross-cultural research based on the machine learning-based cultural values inventory (ML-CVI) developed by Sheetal et al. (2025). The package provides three core functions: measuring cultural distance between country pairs using three methods (Kogut-Singh, Shulgin, and ML-CVI), identifying which of the 60 ML-CVI items statistically mediate a cultural difference in any outcome variable, and predicting country-level scores for countries missing from a given dataset using ML-CVI-weighted Ridge regression. This guide describes each function's purpose, inputs, and outputs, and includes replication code for the mediation studies reported in Sheetal et al. (2025).

En este artículo analizamos los programas presentados por los 155 convencionales constituyentes divididos en cuatro grupos: convencionales de pueblos originarios, convencionales independientes en cupos de partido, convencionales de partido y convencionales independientes. Exploramos los conceptos que emplean y las relaciones que se establecen entre estos por medio de herramientas de humanidades digitales. Empleamos una herramienta simple de visualización denominada bigram. Ella permite observar una red de términos relacionados a partir del cálculo de la frecuencia de coocurrencia entre dos términos (el número de veces que aparecen juntos) dentro de un documento. Identificamos cuatro nodos semánticos en los programas de los convencionales constituyentes: uno en torno al concepto de derechos, otro sobre expectativas del proceso constitucional, uno que aborda temas socioinstitucionales y uno asociado a los pueblos originarios. El nodo semántico de los derechos es compartido por los cuatro grupos de convencionales. En este se incluye el catálogo de derechos propios de la modernidad (civiles, políticos, fundamentales, humanos, sociales, culturales). Por otro lado, los cuatro grupos muestran diferencias de énfasis en expectativas y en aspectos institucionales, aunque en este último ámbito hay coincidencias importantes. Una diferencia importante se observa a nivel de la denominación “pueblos originarios” versus “pueblos indígenas”. Esta afecta incluso a los propios pueblos originarios y sugiere posibles divergencias en futuras prácticas políticas al interior de este grupo y en sus relaciones con los otros. Los programas escritos no son la única forma por medio de la cual las y los convencionales expresan conceptos, ideas e imaginarios sobre la nueva Constitución. Sin embargo, este tipo de archivos contribuye a formar una línea de base desde la cual la discusión constitucional puede desplegarse. Palabras clave: convencionales constituyentes, programas, semántica, derechos, expectativas, instituciones, pueblos originarios

Combinatorial invention—the process by which new technologies emerge through the combination of existing ones—is central to technological evolution, yet it remains poorly understood. This paper develops a novel framework for analysing combinatorial invention by recognising its dual nature as both a design problem-solving process and a lineage-generating process. While existing approaches often treat combinatorial invention as a stochastic process mapping precursor technologies to composite ones, this framework reveals how the challenge of interfacing components generates multiple concurrent technological traditions. By identifying genuine design sub-problems—those requiring solutions that were novel, necessary, and culturally transmitted—we can reconstruct aspects of combinatorial invention processes through the phylogenetic traces their solutions left in the archaeological record. Using the invention of hafted tools by Neanderthals and their African contemporaries as an illustrative case study, I show how this framework reveals a complex, multi-tiered invention process involving functional organization, material implementation, and assembly procedures. The combinatorial invention of complex technologies should be understood not merely as producing composite technologies, but in addition as one generating a manifold of technological lineages through the solving of multiple design sub-problems, specifically traditions of interfaces between the components of the technologies. The proposed framework provides preliminary methodological grounds for reconstructing prehistoric invention processes.

This article examines how competitive pressures within transnational labor alliances can undermine their potential for effective global solidarity. Drawing on a decade-long struggle by the United Auto Workers to organize a major automotive plant in the US, this research explores how internal conflicts within transnational coalitions contribute to organizing outcomes. The concept of solidarity arbitrage is introduced to describe how multinational corporations strategically exploit existing rivalries among employee representative bodies to weaken labor's collective power. This strategy involves the calculated promotion of less confrontational partners while marginalizing more militant ones—a form of differential inclusion. These findings challenge overly optimistic views of network effects, revealing that transnational alliances are not an unalloyed good. Successful organizing may require independent, adversarial strategies to counter solidarity arbitrage.

Türkiye sosyal hizmet sistemi son yirmi yılda hızlı bir kurumsal dönüşüm geçirmiş; hizmet kapsamı ve erişilebilirliği önemli ölçüde genişlemiştir. Bu gelişime paralel olarak, risk değerlendirme süreçlerinin nicel, çok boyutlu ve teknoloji entegreli araçlarla güçlendirilmesi giderek daha fazla önem kazanmaktadır. Mevcut Sosyal İnceleme Raporu (SİR), bilgi toplama sürecini standartlaştırma açısından değerli bir işlev görmekle birlikte, ağırlıklı puanlama, dinamik risk izleme ve yapay zekâ destekli karar desteği gibi bileşenler sisteme henüz entegre edilmemiştir. Bu çalışma, söz konusu boşluğu gidermek amacıyla Bireysel Risk Skorlama Çerçevesi'ni (BRSC) ve üç fazlı Yapay Zekâ Destekli Sosyal Hizmet Karar Destek Modeli'ni (YZDM) kavramsal düzeyde sunmaktadır. Model birbiriyle bağlantılı üç faz üzerine inşa edilmektedir. Faz 1 - Statik Risk Skorlama Çerçevesi, sekiz ana risk kategorisi ve 47 risk faktöründen oluşan, uzman ağırlıklı çok kriterli karar modellemesine (MCDM) dayanan yapılandırılmış bir sistemdir. Faktörlerin puanlanmasında yedi ağırlıklandırma kriteri (Şiddet, Aciliyet, İşlevsellik Etkisi, Kronikleşme Riski, Kümülatif Etki, Müdahale Gerektirme Düzeyi, Epidemiyolojik Kanıtlar) kullanılmakta; kriter ağırlıkları Analitik Hiyerarşi Süreci (Analytic Hierarchy Process, AHP) ile, faktör geçerliliği Modified Delphi uzman konsensüsü yöntemiyle belirlenecektir. Faz 2 - Dinamik Ağırlıklandırma, bağlam duyarlı ağırlıklandırma (CBW), etkileşim sinerjisi (ISW) ve zaman duyarlı ağırlıklandırma (TSW) bileşenlerini içeren hesaplamalı bir uzantıdır. Faz 3 - Öğrenen Sistem, bireyselleştirilmiş risk profili üretimi ve sürekli model güncelleme kapasitesini barındıran tam otomasyon mimarisidir. Her risk faktörü 2828, 5395, 6284 ve 6698 sayılı kanunlar başta olmak üzere güncel Türkiye sosyal hizmet mevzuatıyla ilişkilendirilmiştir. YZDM, uzman klinik yargısının yerini almayı değil; görüşme desteği, otomatik raporlama, kanıta dayalı müdahale planlaması ve hizmet eşleştirme işlevleriyle mesleki kapasiteyi güçlendirmeyi hedeflemektedir. Bu ön baskı, çerçevenin fikir önceliğini zaman damgalı biçimde kayıt altına almakta ve çok aşamalı araştırma programının teorik zeminini oluşturmaktadır. Anahtar Kelimeler: bireysel risk değerlendirmesi, çok kriterli karar modelleme, MCDM, Modified Delphi, AHP, sosyal hizmet, yapay zekâ destekli karar desteği, dinamik ağırlıklandırma, öğrenen sistem, Türkiye

How can innovation in digital ecosystems be used to support the societal inclusion of marginalized groups around the world? This paper argues that platform-based business innovation can facilitate refugee integration and inclusion in societies where access to basic human rights, such as legal status, is fraught. To do this, we examine the theoretical and empirical foundations of three fields of study: first, digital platforms and marketplaces; next, platform-based innovation; and finally, refugee displacement and movement, one of the most complex humanitarian issues of the modern era. This paper contributes to the literature by unifying platform-based innovation theory with refugee integration scholarship, identifying financial access as a cross-cutting determinant of digital inclusion in legally restrictive contexts. The paper first defines digital platforms and platform-based innovation, then situates digital practices within Ager and Strang’s refugee integration framework. Finally, it synthesizes evidence from digital platforms across Asia and presents new analysis on the critical role of financial access to broader integration outcomes.

This study investigates the corporate capture of vocational education at a North Carolina community college, arguing that public institutions are being repurposed as subsidized human resources arms for transnational capital. Grounded in the concept of the “shadow college,” the analysis reveals how the democratic mission of public education is subordinated to the short-term profitability needs of private firms. Using Critical Discourse Analysis, the study demonstrates how the curriculum combines “human capital” and “deficit” models to engineer compliant neoliberal subjects. The program enforces labor discipline through intrusive behavioral interventions—such as self-optimization and scripted social interactions—that extend corporate control into the student’s subjectivity. Situated within the anti-union context of the American South, this model reinscribes historical industrial paternalism under the guise of workforce development. Ultimately, the study concludes that this employer-driven model compromises workforce resilience by producing non-transferable skills, leaving workers vulnerable to market volatility while socializing the costs of training onto the public.

This article seeks to explore and analyze the interrelationship between environmental factors, the structure of the energy sector, and stability/resilience within the financial sector by employing data from OECD countries between 2004 and 2021. The article utilizes new data sets provided by the World Bank Group's Global Financial Development Data and Sovereign ESG Data, with specific emphasis placed on the bank capitalization indicator, which is described as the bank capital asset ratio, and is considered an important factor in sectoral stability/resilience. Using fixed effect panel data econometrics, the article suggests that methane emissions, PM2.5 air pollution, and net energy imports have statistically significant impacts on the bank capitalization process, while renewable energy and bank capitalization have positive and statistically significant associations. The positive association between fossil fuel consumption and bank capitalization suggests that there is an inherent contradiction between current sectoral stability/resilience and the challenges associated with the energy transition process. The Hausman test suggests that omitted variables may exist and that fixed effect econometrics is an appropriate model. Clustering analysis suggests that each country has an underlying regime driven by environmental factors, the structure of the energy sector, and sectoral stability/resilience. Moreover, machine learning regression analysis employing K-Nearest Neighbors (KNN) and Random Forest models indicate that significant predictive potential is possible and that energy dependence, renewable energy, and air pollution are important factors in bank capitalization processes. The article suggests that robust evidence is provided regarding environmental quality and its interrelationship with sectoral stability/resilience and has significant implications for developing macroprudential frameworks that incorporate elements of the energy transition process.

Well-being research has long sought to identify what enables human flourishing, with frameworks like PERMA providing structured approaches to understanding psychological well-being components. However, existing frameworks conceptualize well-being as relatively stable individual differences measured at discrete time points, an approach that cannot capture rapid fluctuations characteristic of digital environments where well-being responds to continuous social feedback, algorithmically-curated content, and frequent context switching. This paper introduces the Adaptive PERMA Framework (APF), which reconceptualizes well-being as a dynamic, temporally evolving system. By integrating foundational well-being theory with computational psychology methods, APF addresses gaps through three core mechanisms: bidirectional feedback loops, adaptive weighting, and state-dependent transitions. Unlike prior extensions adding new PERMA dimensions, APF explicitly models how well-being evolves in digitally-mediated contexts where psychological states fluctuate rapidly. This enables predictive modeling of well-being trajectories, provides a theoretical foundation for adaptive interventions, and advances understanding of how digital environments shape human flourishing.

This study proposes a theoretical framework that reconceptualizes workplace harassment not as isolated deviant acts but as a staged transformation of avoidance strategies selected in response to criticism or problem-raising. Prior research has examined anger as aggressive behavior (Averill, 1982; Gibson & Callister, 2010) and silence as voice suppression or interpersonal risk avoidance (Morrison, 2014; Van Dyne et al., 2003), yet the dynamic relationship between these phenomena has not been sufficiently integrated. Building upon prior conceptualizations of silent harassment as communicative exclusion grounded in meta-communication dysfunction and structural ambiguity (Hiraoka, 2025b), the present study develops a Dual-Stage Avoidance Harassment Model. It theorizes anger-based immediate avoidance as the first stage and silent harassment as a subsequent, more invisible and sustainable avoidance strategy. Furthermore, the study demonstrates that this transition process is consistent with social learning theory (Bandura, 1977), institutional isomorphism (DiMaggio & Powell, 1983), and organizational learning theory (Argyris & Schön, 1978). The shift from anger to silence is interpreted not as emotional calming but as a strategic transformation. By bridging harassment research, employee silence research, psychological safety, and organizational learning, the model provides a theoretical foundation for structural intervention.

This article offers an autoethnographic and multimodal analysis of the #MeTooSTS/#WeDoSTS movement, initiated through a public Medium testimony on gender-based violence and abuse of power in academia. Writing from a scholar-survivor-activist standpoint, I trace how public disclosure operates as both epistemic intervention and affective labour, revealing field “shadow zones” in science and technology studies (STS). The article documents the testimonial writer’s journey after going public, including legal threats, institutional backlash, and attempts at containment. Methodologically, the piece combines autoethnography, visual storytelling, and movement analysis to conceptualise disclosure as field shadow work: a reparative practice that exposes hidden power relations while generating new collective forms of knowing, solidarity, and critique. Against institutional logics of closure, I argue that survivor-led disclosure produces fragile yet generative openings for transformative justice in academic fields. The article theorises public testimony as a mode of survivance that resists silencing, reclaims epistemic authority, and reimagines the conditions of academic belonging.

This paper addresses the challenges of empirically studying populism and similar social science concepts in large text datasets. We begin by reviewing existing research on predicting populism, highlighting definitional ambiguities and limitations for classifying populism on social media data. We then propose a narrow, practical definition for social media data, develop a coding scheme and label data. Next, using a substantial Twitter dataset and our revised definition, we compare various machine learning and deep learning models, including LLMs. This comparison offers methodological insights applicable to classifying populism and similar concepts in diverse contexts. Finally, we examine how model accuracy impacts substantive conclusions about populism’s prevalence, informing optimal modeling choices for such analyses.

Kehadiran Taman kanak–kanak (TK) dalam dunia pendidikan sangat dibutuhkan untuk menyesuaikan dengan kebutuhan para orang tua dalam memenuhi pendidikan anak-anaknya. Pemilihan sekolah, termasuk TK menjadi perhatian khusus para orang tua, dengan mempertimbangkan fasilitas yang memadai dan sumber daya pengajar yang berkualitas menjadi salah satu faktor penting sebuah lembaga Pendidikan. Oleh karena itu, kegiatan pengabdian kepada masyarakat ini bertujuan untuk mengidentifikasi, mensosialisasikan, dan memantau tata kelola Sumber Daya Manusia (SDM) oleh Politeknik Kutaraja yang diterapkan di TK Aisyiyah Bustanul Athfal Lhong Raya Banda Aceh. Hasil yang diperoleh dari kegiatan pengabdian kepada Masyarakat ini menunjukkan bahwa sosialisasi dan pembinaan terkait tata kelola SDM berjalan dengan baik. Pihak sekolah dan guru menerima materi pembinaan melalui sosialisasi, pelatihan, dan diskusi yang bersifat berkelanjutan. Proses monitoring yang dilakukan memberikan gambaran positif mengenai kemajuan yang dicapai, khususnya dalam penerapan tata kelola SDM yang lebih efektif. Secara keseluruhan, program ini memberikan kontribusi yang baik terhadap kualitas pendidikan dan pengelolaan sekolah di TK Aisyiyah Bustanul Athfal Lhong Raya Banda Aceh, meskipun masih terdapat beberapa aspek yang perlu diperbaiki lebih lanjut.

Background Children and young people with complex medical needs are increasingly supported at home by family carers, often with statutory healthcare funding. In England, Personal Health Budgets (PHBs) are promoted as mechanisms to increase choice and control in how healthcare funding is used, yet evidence on their use in children’s complex care remains limited. Aim To map and synthesise existing evidence on the experiences and outcomes of children and young people with complex medical needs and their families accessing PHBs or comparable self-directed health funding schemes. Methods A rapid scoping review was conducted following PRISMA-ScR guidance. Eight academic databases were searched alongside targeted grey literature sources, including national bodies, third-sector organisations, and all 42 Integrated Care Boards in England. Sources published between 2010 and January 2026 were screened and charted. Eligible sources addressed children/young people with complex medical needs (and/or families) and examined experiences or outcomes of accessing PHBs in England or comparable health-funded self-directed schemes internationally; social care-only budgets were excluded. Data were synthesised thematically across academic and grey literature. Results Twenty-six sources were included (10 peer-reviewed studies and 16 UK grey literature sources). Three higher-order themes were identified: (1) the promise of choice and control alongside burden transfer to family carers; (2) system conditions shaping PHB viability, including workforce stability, information infrastructure, governance, and transitions; and (3) uneven distribution of benefits and outcomes, with a clear equity gradient linked to family resources and local system context. Conclusions PHBs and comparable schemes can enable continuity and relational care for families of children with complex medical needs, but often do so by redistributing labour and risk onto family carers. Without adequate system support, PHBs risk amplifying inequities rather than delivering equitable personalised care. Substantial gaps remain in UK empirical evidence, highlighting the need for further research to inform the design of sustainable, joined-up models of care.

Large language models (LLMs) are increasingly used as synthetic survey respondents, yet it is unclear whether their belief-system structure matches that of real publics. We compare 28 LLMs to the 2024 General Social Survey (GSS) using 52 attitude items and demographic persona traits. We estimate polychoric correlation matrices and propagate uncertainty in the GSS via bootstrap resampling with multiple imputation. Constraint is measured by the variance share explained by the first principal component and by effective dependence, a determinant-based measure of global linear dependence. Across models, LLM personas exhibit substantially higher constraint than humans; conditioning on persona traits reduces constraint far more for LLMs, indicating greater demographic mediation. Projection onto a shared GSS basis further shows overemphasis of the leading dimension and missing secondary structure. These results caution against treating LLM personas as a reliable foundation for synthetic survey data generation.

The present study aims to contribute to the exploration of the combined effect of sustainability strategies and family governance on corporate risk-taking, with a focus on the temporal dimension of ESG engagement and the multidimensional nature of family involvement. Although a number of research papers have attempted to investigate the interrelations between ESG performance, corporate risk, and ownership structure, the existing research is fragmented, static, and limited in terms of its research methodology. Therefore, this article aims to provide a framework that (a) distinguishes between long-term and short-term ESG performance and (b) distinguishes between ownership incentives and management control in family firms. The present study uses a sample of listed corporations and combines three different research methods: fixed effects panel regressions, cluster analysis, and machine learning regression methods. The results of this study suggest that long-term ESG performance is negatively related to corporate risk, as proxied by the volatility of operating performance. The effect of short-term ESG performance on corporate risk is less robust and less consistent. Furthermore, this study finds that family cash-flow rights and family CEOs are negatively related to corporate risk, in accordance with the SEW hypothesis. Finally, this study reveals that the positive interaction effect of long-term ESG performance and family cash-flow rights mitigates the negative effect of sustainability on corporate risk in family-controlled corporations. The results of this study show that cluster analysis reveals a high degree of heterogeneity in corporate strategic profiles, with different clusters characterized by specific configurations of ESG orientation, family involvement, corporate governance structure, firm size, and corporate risk. The results of this study also show that the proposed model has a high predictive power in relation to corporate risk levels, as indicated by the results of the random forest regression analysis. Finally, this study reveals that financial fundamentals are more important in determining corporate risk than ESG engagement and family control; however, ESG engagement and family control are secondary but significant and nonlinear determinants of corporate risk.

Current safety protocols for social AI companions rely on binary age thresholds (e.g., "18+") or self-reported declarations of maturity. However, chronological age poorly predicts psychosocial capacity to navigate high-intimacy AI systems, and self-report is easily gamed by users seeking unrestricted access. Adolescence is characterized by significant heterogeneity in social cognition and regulatory capacity; a 16-year-old and an 18-year-old may possess comparable capabilities regarding impulse control, rejection tolerance, and boundary reasoning. This paper argues that high-intimacy AI affordances require a safety layer beyond age verification: a brief, validity-informed behavioral screening battery. This screening tiers access to high-risk features (e.g., erotic roleplay, exclusivity cues) based on vulnerability-relevant metrics, such as inhibitory control or mentalization. Performance validity testing (PVT) informed checks help detect invalid responding/gaming, while task performance provides probabilistic vulnerability signals. An operational framework for risk-tiering is presented, alongside evaluation metrics, privacy safeguards to prevent discriminatory deployment and example implementation as a Chrome browser extension.

This study investigates whether the diversity of researchers’ collaboration influences research visibility and whether its benefits differ by gender. Using bibliometric data from 881 academics at the University of Aberdeen (UK), we measured collaboration diversity through Gini indexes based on co-authors’ institutional and country affiliations and assessed research visibility using field-normalised citation percentiles. Regression analyses revealed that collaboration diversity strongly predicts citation impact: researchers with broader institutional and international networks achieve higher citation percentiles. However, contrary to widely reported patterns of gender disadvantage, we found no systematic gender differences in collaboration diversity or citation impact. Women and men engaged in similarly diverse collaborations and derived comparable visibility benefits. An exploratory model suggested that women may gain slightly more from collaborating with different institutions than men, though this effect was not significant after controlling for disciplinary differences. These findings challenge assumptions of universal gender gaps in collaborative practices and highlight the role of inclusive institutional environments in promoting equitable research outcomes. They also suggest that structural factors beyond publication metrics likely drive persistent gender disparities in academic career progression.

Multiracial scholarship has long treated Black-White biracial individuals as a homogeneous group, often overlooking how proximity to whiteness influences their lived experiences. This oversight is particularly evident in the case of Black biracial individuals, defined here as those with one Black and one White parent who are socially identified as Black. These individuals experience a dual burden: they are subjected to the same anti-Black racism as monoracial Black individuals and simultaneously encounter monoracism, a mixed-race-specific form of oppression that frequently manifests as identity invalidation (e.g., societal dismissal of multiracial heritage, social pressure to identify with a single racial group). Despite its significance, this form of dual marginalization remains under-theorized within existing literature. The present article addresses this gap. Drawing on critical race theory, critical multiracial theory, and intersectionality theory, I propose a theoretical framework for understanding Black biracial positionality and experiences by considering the intersection of Blackness and biraciality. This framework provides scholars with the analytical tools to examine an overlooked aspect of the multiracial experience and challenges academic discourse to move beyond monolithic conceptions of Black-White biracial identity.

This thesis examines how the co-evolution of physical (transport) and digital mobilities shapes inequality and wellbeing in rapidly urbanising, digitalising cities. As residents navigate increasingly complex mobility systems, understanding these dynamics is critical for equitable urban futures. It asks: (1) What causal pathways link evolving infrastructure–individual relationships to poverty risks and quality of life (QoL)? (2) How do transport and digital mobilities interact to produce these outcomes? (3) How do social ties mediate these effects across age groups? The thesis makes three contributions. Theoretically, it bridges micro–meso gaps by showing how socio-technical regime evolution influences individual outcomes through “mobility assemblages.” Methodologically, it advances fuzzy-set Qualitative Comparative Analysis (fsQCA) with a novel two-step design that connects individual mobility patterns to regime-level conditions, including a configurational propinquity index and accompanying visualisation software. Empirically, it provides original survey evidence from Wuhan, Guangzhou and Shenzhen (n=739; July–September 2022), demonstrating how transport–digital mobility interactions generate differentiated pathways to poverty risks and wellbeing. QoL is measured using EQ-5D-5L with Chinese value sets. Findings reveal multiple, non-linear, city- and population-specific pathways: exclusion is not universal to any single demographic, but emerges from configurations combining life-course stage, education, infrastructure trajectories and perceptions, socio-economic/social capital, and mobility skills. Younger groups tend to achieve good QoL via flexible multimodal strategies that avoid platform lock-ins, while older groups do so through sustained physical mobility combined with context-appropriate digital engagement. Across generations, social ties consistently support good QoL, and “city membership” is not required in configurations linking social ties to QoL—suggesting more generalisable social pathways across the three cities. Policy implications emphasise integrated mobility planning that treats transport and digital systems as interdependent, platform design that prevents lock-ins while remaining accessible across age groups, and interventions that mobilise social capital as a protective factor. Overall, the thesis offers a framework for analysing mobility–inequality dynamics in digitalising cities globally, with particular relevance for ageing societies undergoing technological transition.

This study developed a schema to illustrate the physical healthcare experiences of Māori (Indigenous Peoples of Aotearoa New Zealand) with mental health and substance use conditions and their whānau (support network). This research conducts a mixed-methods meta-synthesis of nine studies: seven qualitative and two quantitative. Employing Kaupapa Māori methodologies and Actor-Network theory, it centres Māori knowledge to critique settler-colonial power structures of Aotearoa New Zealand’s healthcare system. From the analysis, a network graph mapped the key actors and relationships in these healthcare experiences. Findings identified 28 actors and 175 connections, revealing the complex, cumulative barriers Māori face in accessing quality care. The study highlights systemic disruptions across health, social, and legal systems, emphasising the need for targeted service improvements. By applying actor-network theory, this research identifies priority actors and relationships for future interventions and advocates for culturally responsive models that address structural inequities in healthcare access for Māori.

The "retirement spending smile" (Blanchett, 2014), a U-shaped pattern in the rate of retiree spending change, has influenced how advisors project retirement spending. We replicate Blanchett's analysis using RAND HRS/CAMS data (2001–2009) and extend it with panel methods through 2021. The smile pattern appears when comparing different households at different ages but is not statistically detectable when tracking the same households over time. In our replication, coefficient signs match Blanchett's specification, but 95% bootstrap confidence intervals for Age² and Age include zero — the curvature is not statistically distinguishable from simple linear decline. We also document that the ln(Spending) coefficient sign depends on whether spending is measured at interval start or end, an implementation choice unspecified in the original. The smile attenuation finding is robust to survey weighting. For individual client projections, a constant real decline (~1%, sensitivity 0–2% annually) is a more defensible baseline than assuming a smile.