Татьяна Михайловна Пермякова, Елизавета Александровна Смирнова
В статье выполнен количественный и качественный анализ терминов английского языка, связанных с изучением миграции. Источниками выступили научно-исследовательские статьи по социальным наукам, опубликованные в период с 2018 по 2020 гг. в международных журналах 1-го квартиля в наукометрической базе Scopus. Корпусно-лингвистическое исследование решает две задачи: определение функционирующих систем терминов в научных статьях, описание их дисциплинарной принадлежности по признакам семантических полей. Выделен корпус текстов объемом около 280 тыс. слов, обработанных с помощью функций конкорданса и списка ключевых слов программы AntConc. В текстах определялись двусловные сочетания, содержащие единицы migration и migrant(s). Качественный анализ семантики единиц служил дополнительной верификацией к семантической дифференциации.
Результаты исследования показывают, что с точки зрения семантического анализа терминов в настоящее время формируются два подхода к изучению миграции: во-первых, это время-ориентированное изучение, а во-вторых, это предметно-ориентированное исследование миграции в рамках определенных дисциплин.
В результате анализа установлено, что поле миграционных исследований структурировано, во-первых, вокруг изучения сообществ или индивидуального опыта, а во-вторых, вокруг временного или предметного подходов, которые часто сочетаются. Также выявлено, что устоявшаяся терминология характерна для экономики, образования и госуправления, тогда как история, география и психология еще не выработали собственного аппарата для этого явления.
Abstract In rapidly urbanizing cities, historical neighborhoods often experience drastic spatial transformation, leading to the erosion of urban form, memory, and identity. This study examines the morphological transformation of the Siwenli Lilong neighborhood in central Shanghai, tracing its evolution from 1948 to 2021. Drawing on a 70-year fine-scale GIS dataset at the lane-block level which is a rare longitudinal resolution in related urban research, the study integrates historical cartography, urban morphology, and heritage interpretation to identify three key phases: wartime densification, socialist consolidation, and market-driven redevelopment. Each phase reflects distinct governance rationales, cumulatively producing a shift from spatial continuity to fragmentation. The research introduces the concept of “interface rupture” to capture the disjunction between old and new typologies, particularly in façade logic and public–private transitions. Rather than treating transformation as incidental, it proposes a conceptual model linking governance regimes, development logics, and spatial consequences. While symbolic heritage elements are selectively retained, most morphological memory is weakened or erased. By integrating urban morphology with the Historic Urban Landscape (HUL) framework, the study contributes to heritage-led urbanism by moving beyond site-specific diagnosis toward transferable explanatory mechanisms. It calls for adaptive conservation frameworks that recognize spatial memory as a planning asset, promoting continuity during inevitable change. The Siwenli case thus serves as both empirical evidence and a theoretical lens for understanding structural dynamics behind morphological rupture in East Asian cities.
Hayate Iso, Pouya Pezeshkpour, Nikita Bhutani
et al.
Large Language Models (LLMs) offer the potential to automate hiring by matching job descriptions with candidate resumes, streamlining recruitment processes, and reducing operational costs. However, biases inherent in these models may lead to unfair hiring practices, reinforcing societal prejudices and undermining workplace diversity. This study examines the performance and fairness of LLMs in job-resume matching tasks within the English language and U.S. context. It evaluates how factors such as gender, race, and educational background influence model decisions, providing critical insights into the fairness and reliability of LLMs in HR applications. Our findings indicate that while recent models have reduced biases related to explicit attributes like gender and race, implicit biases concerning educational background remain significant. These results highlight the need for ongoing evaluation and the development of advanced bias mitigation strategies to ensure equitable hiring practices when using LLMs in industry settings.
Junio Soares dos Santos, Jaqueline Guimarães Santos, Mariana Teodoro Santos
et al.
A gestão ordinária é um tema importante no campo da gestão e seu uso tem sido difundido nas ciências sociais aplicadas. Assim, esse estudo teve como objetivo analisar como a gestão ordinária se caracteriza no cotidiano dos artesãos vinculados a associação ARTESAL e suas contribuições para o desenvolvimento local e regional. No que se refere aos procedimentos metodológicos, foi realizada uma pesquisa de abordagem qualitativa, utilizando a entrevista semiestruturada e observação não participante, além do grupo focal, como as técnicas de coleta de dados. Os dados, por sua vez, foram analisados a partir da técnica de análise de conteúdo. Os principais resultados da pesquisa apontam para a utilização de algumas práticas de gestão ordinária por artesãos e artesãs vinculadas a associação de artesanato estudada, tais como reciprocidade, solidariedade e valorização das trocas. Contudo, a partir de um olhar crítico para o fenômeno, observamos que a forma como a associação é conduzida exerce alguma força de padronização de alguns processos de gestão, condizentes aos modelos de produção capitalistas caracterizados pela padronização e massificação.
Manoel Horta Ribeiro, Robert West, Ryan Lewis
et al.
Effective content moderation in online communities is often a delicate balance between maintaining content quality and fostering user participation. In this paper, we introduce post guidance, a novel approach to community moderation that proactively guides users' contributions using rules that trigger interventions as users draft a post to be submitted. For instance, rules can surface messages to users, prevent post submissions, or flag posted content for review. This uniquely community-specific, proactive, and user-centric approach can increase adherence to rules without imposing additional burdens on moderators. We evaluate a version of Post Guidance implemented on Reddit, which enables the creation of rules based on both post content and account characteristics, via a large randomized experiment, capturing activity from 97,616 posters in 33 subreddits over 63 days. We find that Post Guidance (1) increased the number of ``successful posts'' (posts not removed after 72 hours), (2) decreased moderators' workload in terms of manually-reviewed reports, (3) increased contribution quality, as measured by community engagement, and (4) had no impact on posters' own subsequent activity, within communities adopting the feature. Post Guidance on Reddit was similarly effective for community veterans and newcomers, with greater benefits in communities that used the feature more extensively. Our findings indicate that post guidance represents a transformative approach to content moderation, embodying a paradigm that can be easily adapted to other platforms to improve online communities across the Web.
Nadezhda Yashina, Oksana Kashina, Sergey Yashin
et al.
The need to take into account imbalances among regional indicators in the development of state policy for financing national projects makes it necessary to develop a methodology that will enable objective assessment of the effectiveness of socially significant projects in Russia. This paper reports the development of a methodology for financial monitoring of national project implementations in the constituent entities of the Russian Federation, taking into account the correlation of their target indicators and using cluster analysis and methods in mathematical statistics. The proposed methodology was tested on health and demography national project data obtained from the Federal Treasury of Russia, the Federal State Statistics Service and the Accounts Chamber for 2020–2021. The analysis of public funding for national projects based on centralization indices and target indicators for their implementation enabled classifying the regions of Russia according to the levels of effectiveness and the financial risks of implementing the projects. The results of the study correspond to the actual effectiveness of national projects and can be used in the development of flexible state policy in financing national projects, taking into account the level of the target indicators achieved.
Communities, ranging from homes to cities, are a ubiquitous part of our lives. However, there is a lack of adequate support for applications built around these communities. As a result, current applications each need to implement their own notion of communities, making it difficult for both the app developers and the app users (\ie the community admins and members) to create and use these community apps. In this paper, we argue that communities should be supported at the infrastructure-level rather than at the app-level. We refer to this approach as the Platform-Managed Community (PMC). We propose Comverse, a platform designed to this end. Comverse is predicated on the principle of federation, allowing autonomous nodes representing community members to voluntarily associate and share data while maintaining control over their data and participation. Through Comverse, we explore the vision of community computing by showcasing its applicability with real-world community apps.
Non-Fungible Tokens (NFTs) are non-interchangeable assets, usually digital art, which are stored on the blockchain. Preliminary studies find that female and darker-skinned NFTs are valued less than their male and lighter-skinned counterparts. However, these studies analyze only the CryptoPunks collection. We test the statistical significance of race and gender biases in the prices of CryptoPunks and present the first study of gender bias in the broader NFT market. We find evidence of racial bias but not gender bias. Our work also introduces a dataset of gender-labeled NFT collections to advance the broader study of social equity in this emerging market.
The detection of community structure is probably one of the hottest trends in complex network research as it reveals the internal organization of people, molecules or processes behind social, biological or computer networks\dots The issue is to provide a network partition representative of this organization so that each community presumably gathers nodes sharing a common mission, purpose or property. Usually the identification is based on the difference between the connectivity density of the interior and the boundary of a community. Indeed, nodes sharing a common purpose or property are expected to interact closely. Although this rule appears mostly relevant, some fundamental scientific problems like disease module detection highlight the inability to determine significantly the communities under this connectivity rule. The main reason is that the connectivity density is not correlated to a shared property or purpose. Therefore, another paradigm is required for properly formalize this issue in order to meaningfully detect these communities. In this article we study the community formation from this new principle. Considering colors formally figures the shared properties, the issue is thus to maximize group of nodes with the same color within communities.. We study this novel community framework by introducing new measurement called \emph{chromarity} assessing the quality of the community structure regarding this constraint. Next we propose an algorithm solving the community structure detection based on this new community formation paradigm.
Political races are often predicted by polls, but such investigations are costly to conduct and the results can be elusive because of their self-report nature. Alternative quantitative modeling approaches are promising to alleviate the prior concerns and therefore, this paper predicted outcomes of the 2020 US Congress elections from computational analyses of language data. Psychological profiles of 918 candidates were created from their social media records (N = 2,836,114 Tweets) and three preregistered dimensions — common words, analytic thinking, and affect — were associated with race outcome. Congressional race winners wrote with common words, communicated in an analytic style, and used more positive affect than congressional race losers. The predictive accuracy of these language dimensions alone was substantial (AUC = 0.844; 79.8% 10-fold cross-validated accuracy, 95% CI [73.2%, 85.4%]), values consistent with or exceeding most polling accuracies. Together, social media language data reveal psychological information about politicians and can indicate race outcomes.
Yury A. Doroshenko, Maria S. Starikova , Viktoriya N. Ryapukhina
New industrialisation challenges, turbulent economic environment and opening market niches change the structure of competitiveness factors and determine the innovativeness of industrial development. In the current context, it is necessary to deepen the analysis of industrialisation and innovation performance of regions. Therefore, this study aims to identify industrial and innovative development models present in Russian regions. To this end, we propose a methodology based on assessing the localisation coefficients of both regional industrialisation and innovation performance. Calculation of these indicators resulted in the creation of four models: Model 1 (low industrial development and low innovation performance), Model 2 (low industrial development and high innovation performance), Model 3 (high industrial development and high innovation performance), Model 4 (high industrial development and low innovation performance). The classification of the constituent entities of the Russian Federation according to the industrial and innovative development model shows that more than 40 % of regions use Model 1 and about 12 % of territories use Model 2. Simultaneously, approximately 27 % of regions (including Tula, Lipetsk, Chelyabinsk, Vladimir oblasts, Republic of Bashkortostan) chose Model 3, which most fully meets the new industrialisation challenges. The high stability of this disproportionate structure indicates the absence of positive dynamics and poor balance of industrial and innovation policy measures in most Russian regions in the period 2015–2019. The study results can be used to create an alternative ranking of innovative development of regions. Further research can apply these findings to assess the efficiency of regional industrial and innovation policies.
The differences in travel times of passenger cars, traffic stream, and trucks depend on the area type, temporal factors, reference speed, and traffic condition. These explanatory variables account for the effect of geometric conditions and variations in the traffic flow. The focus of this research is to examine the correlations and estimate truck travel time to passenger car or traffic stream travel time ratio of a road link (dependent variable) as a function of these explanatory variables. Travel time data for Mecklenburg County and Iredell County in North Carolina, USA were gathered for the year 2017 to examine correlations, develop generalized estimating equations (GEE) models, and identify explanatory variables influencing the ratios. Gamma log-link distribution-based models are the best-fitted models to estimate the average travel time (ATT) of trucks to the ATT of passenger cars or traffic stream ratios. Notable differences in the coefficients were observed when the ATT of trucks was compared with the ATT of passenger cars or traffic stream. The area type (urban or rural) was observed to influence the ratios differently. The influence of traffic condition, reference speed (or free-flow speed), day-of-the-week (DOW) and time-of-the-day (TOD) on the ratios also varied with the area type.
A diferencia del enfoque historiográfico común, este artículo no asume la similitud doctrinaria como la explicación principal de la política comercial. En su lugar, propone considerarla como el resultado de un proceso político que conjuga múltiples intereses. En particular, la política comercial chilena (1850-1914), mediante sus Ordenanzas de Aduanas, ha sido considerada un fiel reflejo de las doctrinas económicas de la época. Sin embargo, este artículo propone ampliar el análisis empírico a las distintas medidas de política, tales como las leyes y decretos, enfatizando su estructura arancelaria ex ante (de iure) más que la ex post (efectiva). Los resultados sugieren un uso compensatorio de los aranceles que llevó a una reducción persistente de estos, independiente de la doctrina imperante en la ordenanza. Sus “designios” fueron, por tanto, más pragmáticos que doctrinarios.
Latin America. Spanish America, Regional economics. Space in economics
Nathan TeBlunthuis, Charles Kiene, Isabella Brown
et al.
Large-scale quantitative analyses have shown that individuals frequently talk to each other about similar things in different online spaces. Why do these overlapping communities exist? We provide an answer grounded in the analysis of 20 interviews with active participants in clusters of highly related subreddits. Within a broad topical area, there are a diversity of benefits an online community can confer. These include (a) specific information and discussion, (b) socialization with similar others, and (c) attention from the largest possible audience. A single community cannot meet all three needs. Our findings suggest that topical areas within an online community platform tend to become populated by groups of specialized communities with diverse sizes, topical boundaries, and rules. Compared with any single community, such systems of overlapping communities are able to provide a greater range of benefits.
Thomas Krenc, Robert Beverly, Georgios Smaragdakis
BGP communities are a popular mechanism used by network operators for traffic engineering, blackholing, and to realize network policies and business strategies. In recent years, many research works have contributed to our understanding of how BGP communities are utilized, as well as how they can reveal secondary insights into real-world events such as outages and security attacks. However, one fundamental question remains unanswered: "Which ASes tag announcements with BGP communities and which remove communities in the announcements they receive?" A grounded understanding of where BGP communities are added or removed can help better model and predict BGP-based actions in the Internet and characterize the strategies of network operators. In this paper we develop, validate, and share data from the first algorithm that can infer BGP community tagging and cleaning behavior at the AS-level. The algorithm is entirely passive and uses BGP update messages and snapshots, e.g. from public route collectors, as input. First, we quantify the correctness and accuracy of the algorithm in controlled experiments with simulated topologies. To validate in the wild, we announce prefixes with communities and confirm that more than 90% of the ASes that we classify behave as our algorithm predicts. Finally, we apply the algorithm to data from four sets of BGP collectors: RIPE, RouteViews, Isolario, and PCH. Tuned conservatively, our algorithm ascribes community tagging and cleaning behaviors to more than 13k ASes, the majority of which are large networks and providers. We make our algorithm and inferences available as a public resource to the BGP research community.
Eleanor Wedell, Minhyuk Park, Dmitriy Korobskiy
et al.
Clustering and community detection in networks are of broad interest and have been the subject of extensive research that spans several fields. We are interested in the relatively narrow question of detecting communities of scientific publications that are linked by citations. These publication communities can be used to identify scientists with shared interests who form communities of researchers. Building on the well-known k-core algorithm, we have developed a modular pipeline to find publication communities. We compare our approach to communities discovered by the widely used Leiden algorithm for community finding. Using a quantitative and qualitative approach, we evaluate community finding results on a citation network consisting of over 14 million publications relevant to the field of extracellular vesicles.
Reddit has found its communities playing a prominent role in originating and propagating problematic socio-political discourse. Reddit administrators have generally struggled to prevent or contain such discourse for several reasons including: (1) the inability for a handful of human administrators to track and react to millions of posts and comments per day and (2) fear of backlash as a consequence of administrative decisions to ban or quarantine hateful communities. Consequently, administrative actions (community bans and quarantines) are often taken only when problematic discourse within a community spills over into the real world with serious consequences. In this paper, we investigate the feasibility of deploying tools to proactively identify problematic communities on Reddit. Proactive identification strategies show promise for three reasons: (1) they have potential to reduce the manual efforts required to track communities for problematic content, (2) they give administrators a scientific rationale to back their decisions and interventions, and (3) they facilitate early and more nuanced interventions (than banning or quarantining) to mitigate problematic discourse.
In this paper we study social exclusion in social (information) networks using a game-theoretic approach, and study the stability of a certain class community structures that are a Nash equilibrium. The main result of our analysis shows that all stable community structures (Nash equilibria) in this class are community structures under which some agents are socially excluded, and do not belong to any of the communities. This result is quite striking as it suggests that social exclusion might be the "norm" (an expected outcome) in social networks, rather than an anomaly.
<p>Durante el siglo XX Bahía Blanca fue un caso peculiar en la reestructuración ferroviaria argentina. Si bien la ciudad había sido un importante núcleo ferroportuario, la racionalización de infraestructuras —a cargo del Ministerio de Transporte e iniciada en 1948— estuvo concentrada en otras ciudades del país. Por ello, en la historia urbana y urbanística de Bahía Blanca la sensación de un desarrollo incompleto contrasta con grandes aspiraciones inalcanzadas. El objetivo del artículo es comparar imaginarios y realidades en torno a los predios ferroviarios desafectados, analizando documentos de la prensa y de los planes urbanos. Dicha tarea ha sido concebida en referencia a la historia del urbanismo en la Argentina y a sus paradigmas disciplinares.</p>
Cities. Urban geography, Urbanization. City and country