What does it mean to publish ethically in a world where knowledge production is shaped by human rights violations, social inequalities, colonial legacies, and systemic exclusions? This reflection draws on ten years of experience with plaNext, an open access journal created by the Young Academics Network of the Association of European Schools of Planning to support early career scholars. It explores how ethical publishing can act as a form of resistance to dominant academic norms, the marginalization of alternative epistemologies, and the politicization of knowledge. Through personal and collective experiences, the article examines plaNext's commitment to academic freedom, equity, decolonisation, and inclusivity, expressed through practices such as voluntary management, half-blind peer review, and a justice-based ethical policy. It also addresses the challenges of sustaining these principles within the constraints of institutional expectations, the publishing industry, and global crises. Ethical publishing, it argues, is not about pretentious neutrality but about taking a principled stance in support of marginalized voices, critical scholarship, and transformative knowledge production. Whether this vision remains viable is an open question that plaNext and many other international journals must continue to examine.
Abstract The Coronavirus Disease 2019 (COVID-19) pandemic prompted governments worldwide to enforce biosecurity measures such as border closures, lockdowns, and testing protocols to contain the virus. These measures significantly impacted cross-border truck drivers at the Beitbridge border between South Africa and Zimbabwe, a key trade corridor. Recognized as essential workers, these drivers sustained supply chains despite stringent biopolitical controls that heightened their vulnerabilities. This paper, grounded in a biopolitical framework, explores the ways in which pandemic-induced mobility restrictions and irregular border policies have heightened health vulnerabilities and economic challenges for cross-border truck drivers. Through examining these challenges, this research underscores the importance of integrating mobility-conscious considerations into public health policies to enhance pandemic preparedness. Using an inductive qualitative approach, the study recruited 20 male truck drivers through convenience sampling for in-depth retrospective interviews enhanced by memory-eliciting prompts. Thematic content analysis uncovered key insights from their narratives. Findings reveal that while governments implemented stringent health protocols to control virus transmission, these measures disproportionately disadvantaged truck drivers by limiting healthcare access, prolonging border delays, and reinforcing economic precarity. The study also highlights the contradictions of essential worker status, where drivers were instrumental in maintaining supply chains yet denied fundamental protections. Utilizing memory-eliciting devices, the research captures drivers’ lived experiences, illustrating how biopolitical governance prioritized economic stability over individual well-being. The study calls for mobility-conscious public health policies, improved occupational health standards, and participatory approaches to border management. Future research should examine the long-term effects of pandemic policies on mobile essential workers and assess the role of technology in mitigating logistical and health challenges.
Abstract Background Although the Screen for Child Anxiety Related Emotional Disorders (SCARED) is a widely used tool for assessing anxiety, its 41-item format makes it a time-intensive method for identifying children and adolescents at high risk of anxiety. This study aims to develop an optimized version of the SCARED for Chinese children and adolescents using a novel machine learning approach, Fast and Accurate Interpretable Risk Scores (FasterRisk), to improve the efficiency of prediction and intervention. Method The full version of the SCARED scale and sociodemographic information were given to 8,315 children and adolescents aged 4–9 years in Henan Province, China. The FasterRisk model was utilized to select the optimal items for constructing the Chinese version of SCARED, and receiver operating characteristic (ROC) curves were employed to determine the optimal cutoff scores. Results The results showed that a 5-item Chinese version of the SCARED accurately reproduced full SCARED scores. By evaluating the performance of risk scoring models containing 1 to 8 items, the 5-item model showed the best performance in AUC (0.96), and other performance indicators, with high prediction accuracy (R²= 0.82). Under the condition of an equal number of items, the AUC value of the newly developed 5-item Chinese version of the SCARED (0.96) surpassed that of the existing SCARED-5 (0.92), with the optimal cutoff score determined to be 14. Conclusion The 5-item Chinese version of the SCARED is a reliable self-report tool that aids users with limited time and resources in assessing anxiety among children and adolescents in China. Trial registration Ethical approval in this study was approved by the Ethics Committee for Social Development and Public Policy at Beijing Normal University (SSDPP-HSC20230014).
This paper employs agent-based modelling to explore the factors driving the high rate of tertiary education completion in the Netherlands. We examine the interplay of economic motivations, such as expected wages and financial constraints, alongside sociological and psychological influences, including peer effects, student disposition, personality, and geographic accessibility. Through simulations, we analyse the sustainability of these trends and evaluate the impact of educational policies, such as student grants and loans, on enrollment and borrowing behaviour among students from different socioeconomic backgrounds, further considering implications for the Dutch labour market.
Pearson's chi-square tests are among the most commonly applied statistical tools across a wide range of scientific disciplines, including medicine, engineering, biology, sociology, marketing and business. However, its usage in some areas is not correct. For example, the chi-square test for homogeneity of proportions (that is, comparing proportions across groups in a contingency table) is frequently used to verify if the rows of a given nonnegative $m \times n$ (contingency) matrix $A$ are proportional. The null-hypothesis $H_0$: ``$m$ rows are proportional'' (for the whole population) is rejected with confidence level $1 - α$ if and only if $χ^2_{stat} > χ^2_{crit}$, where the first term is given by Pearson's formula, while the second one depends only on $m, n$, and $α$, but not on the entries of $A$. It is immediate to notice that the Pearson's formula is not invariant. More precisely, whenever we multiply all entries of $A$ by a constant $c$, the value $χ^2_{stat}(A)$ is multiplied by $c$, too, $χ^2_{stat}(cA) = c χ^2_{stat} (A)$. Thus, if all rows of $A$ are exactly proportional then $χ^2_{stat}(cA) = c χ^2_{stat}(A) = 0$ for any $c$ and any $α$. Otherwise, $χ^2_{stat} (cA)$ becomes arbitrary large or small, as positive $c$ is increasing or decreasing. Hence, at any fixed significance level $α$, the null hypothesis $H_0$ will be rejected with confidence $1 - α$, when $c$ is sufficiently large and not rejected when $c$ is sufficiently small, Yet, obviously, the rows of $cA$ should be proportional or not for all $c$ simultaneously. Thus, any reasonable formula for the test statistic must be invariant, that is, take the same value for matrices $cA$ for all real positive $c$. KEY WORDS: Pearson chi-square test, difference between two proportions, goodness of fit, contingency tables.
Leveraging large language model (LLM) based agents to simulate human social behaviors has recently gained significant attention. In this paper, we introduce a novel social simulator called YuLan-OneSim. Compared to previous works, YuLan-OneSim distinguishes itself in five key aspects: (1) Code-free scenario construction: Users can simply describe and refine their simulation scenarios through natural language interactions with our simulator. All simulation code is automatically generated, significantly reducing the need for programming expertise. (2) Comprehensive default scenarios: We implement 50 default simulation scenarios spanning 8 domains, including economics, sociology, politics, psychology, organization, demographics, law, and communication, broadening access for a diverse range of social researchers. (3) Evolvable simulation: Our simulator is capable of receiving external feedback and automatically fine-tuning the backbone LLMs, significantly enhancing the simulation quality. (4) Large-scale simulation: By developing a fully responsive agent framework and a distributed simulation architecture, our simulator can handle up to 100,000 agents, ensuring more stable and reliable simulation results. (5) AI social researcher: Leveraging the above features, we develop an AI social researcher. Users only need to propose a research topic, and the AI researcher will automatically analyze the input, construct simulation environments, summarize results, generate technical reports, review and refine the reports--completing the social science research loop. To demonstrate the advantages of YuLan-OneSim, we conduct experiments to evaluate the quality of the automatically generated scenarios, the reliability, efficiency, and scalability of the simulation process, as well as the performance of the AI social researcher.
This article addresses scholars concerned about public sociology’s position within the field and academia. It offers new reflections on public sociology to enrich our understanding of its nature and highlight gaps that need further attention. The article also presents propositions regarding the theoretical and practical issues that currently shape how public sociology is perceived, and it outlines some of the visible challenges in practicing it today. In this article, I review the existing discussion on public sociology and comment on it based on qualitative research conducted with scholars in Kraków, as well as my observations as an early-career researcher. These reflections are intended to hopefully strengthen the position of public sociology within the sociological community and to foster further discussion on public sociology 20 years after Burawoy first introduced it.
The narrative biographical interview is a research tool that has been successfully used to study the reproductions of the overall constellations of social life that occur within an individual life. The entire methodological proposal as well as the issue of reproduction are based on a dichotomous epistemology. In the presented article, we analyse this issue of reproduction as it appears in Fritz Schütze’s work. Next, we describe a proposal for an alternative narrative interview – interview about the present based on a non-dichotomous epistemology. In our opinion, this epistemological perspective addresses the issue of reproduction in a completely different way. And, more importantly it introduces in the field of sociology an issue of emergence. To illustrate this non-dichotomous logics, we are using the material from one of the interviews from the research data collection.
Ethnology. Social and cultural anthropology, Sociology (General)
Maria Waheed, Michael Milford, Xiaojun Zhai
et al.
Visual Place Recognition has been the subject of many endeavours utilizing different ensemble approaches to improve VPR performance. Ideas like multi-process fusion, Fly-Inspired Voting Units, SwitchHit or Switch-Fuse involve combining different VPR techniques together, utilizing different strategies. However, a major aspect often common to many of these strategies is voting. Voting is an extremely relevant topic to explore in terms of its application and significance for any ensemble VPR setup. This paper analyses several voting schemes to maximise the place detection accuracy of a VPR ensemble set up and determine the optimal voting schemes for selection. We take inspiration from a variety of voting schemes that are widely employed in fields such as politics and sociology and it is evident via empirical data that the selection of the voting method influences the results drastically. The paper tests a wide variety of voting schemes to present the improvement in the VPR results for several data sets. We aim to determine whether a single optimal voting scheme exists or, much like in other fields of research, the selection of a voting technique is relative to its application and environment. We propose a ranking of these different voting methods from best to worst which allows for better selection. While presenting our results in terms of voting method's performance bounds, in form of radar charts, PR curves to showcase the difference in performance and a comparison methodology using a McNemar test variant to determine the statistical significance of the differences. This test is performed to further confirm the reliability of outcomes and draw comparisons for better and informed selection a voting technique.
Background: This study examined how experiences with discrimination relate to inflammation, a key biological pathway in mental and physical illnesses, and whether associations are moderated by gender across two samples of adolescents of color. Methods: Study 1 was a longitudinal study of 419 African American adolescents assessed on discrimination (ages 19–20), with trajectories of biomarkers of low-grade inflammation (C-reactive protein and soluble urokinase plasminogen activator receptor) measured from ages 25 to 29. Study 2 was a cross-sectional study of 201 eighth graders of color assessed on discrimination and mechanistic indicators of a proinflammatory phenotype: 1) in vitro studies of immune cells’ inflammatory cytokine responses to stimuli; 2) in vitro studies of cells’ sensitivity to anti-inflammatory agents; 3) circulating numbers of classical monocytes, key cellular drivers of low-grade inflammation; and 4) a composite of six biomarkers of low-grade inflammation. Results: Interactions of discrimination by gender were found across both studies. In study 1, African American males experiencing high discrimination showed increasing trajectories of soluble urokinase plasminogen activator receptor over time (p < .001). In study 2, adolescent boys of color experiencing greater discrimination evinced a more proinflammatory phenotype: larger cytokine responses to stimuli (p = .003), lower sensitivity to anti-inflammatory agents (p = .003), higher numbers of classical monocytes (p = .008), and more low-grade inflammation (p = .003). No such associations were found in females. Conclusions: Discrimination is a pressing societal issue that will need to be addressed in efforts to promote health equity. This study suggests that adolescent males of color may be particularly vulnerable to its effects on mental health–relevant inflammatory processes.
Maria Waheed, Michael Milford, Xiaojun Zhai
et al.
Visual Place Recognition has recently seen a surge of endeavours utilizing different ensemble approaches to improve VPR performance. Ideas like multi-process fusion or switching involve combining different VPR techniques together, utilizing different strategies. One major aspect often common to many of these strategies is voting. Voting is widely used in many ensemble methods, so it is potentially a relevant subject to explore in terms of its application and significance for improving VPR performance. This paper attempts to looks into detail and analyze a variety of voting schemes to evaluate which voting technique is optimal for an ensemble VPR set up. We take inspiration from a variety of voting schemes that exist and are widely employed in other research fields such as politics and sociology. The idea is inspired by an observation that different voting methods result in different outcomes for the same type of data and each voting scheme is utilized for specific cases in different academic fields. Some of these voting schemes include Condorcet voting, Broda Count and Plurality voting. Voting employed in any aspect requires that a fair system be established, that outputs the best and most favourable results which in our case would involve improving VPR performance. We evaluate some of these voting techniques in a standardized testing of different VPR techniques, using a variety of VPR data sets. We aim to determine whether a single optimal voting scheme exists or, much like in other fields of research, the selection of a voting technique is relative to its application and environment. We also aim to propose a ranking of these different voting methods from best to worst according to our results as this will allow for better selection of voting schemes.
In this paper we're going to explore the ways in which security proofs can fail, and their broader lessons for security engineering. To mention just one example, Larry Paulson proved the security of SSL/TLS using his theorem prover Isabelle in 1999, yet it's sprung multiple leaks since then, from timing attacks to Heartbleed. We will go through a number of other examples in the hope of elucidating general principles. Proofs can be irrelevant, they can be opaque, they can be misleading and they can even be wrong. So we can look to the philosophy of mathematics for illumination. But the problem is more general. What happens, for example, when we have a choice between relying on mathematics and on physics? The security proofs claimed for quantum cryptosystems based on entanglement raise some pointed questions and may engage the philosophy of physics. And then there's the other varieties of assurance; we will recall the reliance placed on FIPS-140 evaluations, which API attacks suggested may have been overblown. Where the defenders focus their assurance effort on a subsystem or a model that cannot capture the whole attack surface they may just tell the attacker where to focus their effort. However, we think it's deeper and broader than that. The models of proof and assurance on which we try to rely have a social aspect, which we can try to understand from other perspectives ranging from the philosophy or sociology of science to the psychology of shared attention. These perspectives suggest, in various ways, how the management of errors and exceptions may be particularly poor. They do not merely relate to failure modes that the designers failed to consider properly or at all; they also relate to failure modes that the designers (or perhaps the verifiers) did not want to consider for institutional and cultural reasons.
Social networks represent a common form of interconnected data frequently depicted as graphs within the domain of deep learning-based inference. These communities inherently form dynamic systems, achieving stability through continuous internal communications and opinion exchanges among social actors along their social ties. In contrast, neural message passing in deep learning provides a clear and intuitive mathematical framework for understanding information propagation and aggregation among connected nodes in graphs. Node representations are dynamically updated by considering both the connectivity and status of neighboring nodes. This research harmonizes concepts from sociometry and neural message passing to analyze and infer the behavior of dynamic systems. Drawing inspiration from opinion dynamics in sociology, we propose ODNet, a novel message passing scheme incorporating bounded confidence, to refine the influence weight of local nodes for message propagation. We adjust the similarity cutoffs of bounded confidence and influence weights of ODNet and define opinion exchange rules that align with the characteristics of social network graphs. We show that ODNet enhances prediction performance across various graph types and alleviates oversmoothing issues. Furthermore, our approach surpasses conventional baselines in graph representation learning and proves its practical significance in analyzing real-world co-occurrence networks of metabolic genes. Remarkably, our method simplifies complex social network graphs solely by leveraging knowledge of interaction frequencies among entities within the system. It accurately identifies internal communities and the roles of genes in different metabolic pathways, including opinion leaders, bridge communicators, and isolators.
Daniel S. Seara, Jonathan Colen, Michel Fruchart
et al.
Living systems display complex behaviors driven by physical forces as well as decision-making. Hydrodynamic theories hold promise for simplified universal descriptions of socially-generated collective behaviors. However, the construction of such theories is often divorced from the data they should describe. Here, we develop and apply a data-driven pipeline that links micromotives to macrobehavior by augmenting hydrodynamics with individual preferences that guide motion. We illustrate this pipeline on a case study of residential dynamics in the United States, for which census and sociological data is available. Guided by Census data, sociological surveys, and neural network analysis, we systematically assess standard hydrodynamic assumptions to construct a sociohydrodynamic model. Solving our simple hydrodynamic model, calibrated using statistical inference, qualitatively captures key features of residential dynamics at the level of individual US counties. We highlight that a social memory, akin to hysteresis in magnets, emerges in the segregation-integration transition even with memory-less agents. This suggests an explanation for the phenomenon of neighborhood tipping, whereby a small change in a neighborhood's population leads to a rapid demographic shift. Beyond residential segregation, our work paves the way for systematic investigations of decision-guided motility in real space, from micro-organisms to humans, as well as fitness-mediated motion in more abstract genomic spaces.
This review paper marks the 70th anniversary of Current Sociology, the first journal founded by the International Sociological Association (ISA). The past seven decades have been a time of immense change within sociology and around the world, and the shifts within the structure and content of the journal mirror these transformations. Current Sociology today is a vastly different publication to the bibliography focused journal of 1952, and remains one of the top global sociology journals, and a proudly international publication. This short overview traces the history of Current Sociology across the decades, highlighting the work of the editors in guiding the development of the journal, and providing a glimpse into the development of the discipline, and the social developments of the past 70 years.
Cryo-electron tomography (Cryo-ET) has been regarded as a revolution in structural biology and can reveal molecular sociology. Its unprecedented quality enables it to visualize cellular organelles and macromolecular complexes at nanometer resolution with native conformations. Motivated by developments in nanotechnology and machine learning, establishing machine learning approaches such as classification, detection and averaging for Cryo-ET image analysis has inspired broad interest. Yet, deep learning-based methods for biomedical imaging typically require large labeled datasets for good results, which can be a great challenge due to the expense of obtaining and labeling training data. To deal with this problem, we propose a generative model to simulate Cryo-ET images efficiently and reliably: CryoETGAN. This cycle-consistent and Wasserstein generative adversarial network (GAN) is able to generate images with an appearance similar to the original experimental data. Quantitative and visual grading results on generated images are provided to show that the results of our proposed method achieve better performance compared to the previous state-of-the-art simulation methods. Moreover, CryoETGAN is stable to train and capable of generating plausibly diverse image samples.
Fernanda Machado Dill, Maíra Longhinotti Felippe, Angela Favaretto
et al.
A pandemia de COVID-19 impôs à população novas condições de vida, isolamento social, medidas de higiene entre outras. Assim, questiona-se que novos olhares e direcionamentos nossas cidades e projetos terão no futuro. Desenvolveu-se uma pesquisa para análise da percepção dos usuários no Brasil quanto às suas rotinas e expectativas durante o período de enclausuramento entre maio e junho de 2020. A pesquisa consistiu na elaboração de um questionário online e as 1858 respostas coletadas trouxeram reflexões sobre as mudanças que ocorreram durante este período, sobre a satisfação das pessoas com suas próprias residências, com suas cidades e seus bairros.
Architecture, Urban groups. The city. Urban sociology