Ephraim Senkyire, Robert Kogi, Gloria Senkyire
et al.
BackgroundBreast ironing is a harmful cultural practice reported in some African communities and, although often culturally justified, it is increasingly recognised as a violation of the rights of affected girls. This review aims to answer: (1) What is the prevalence of breast ironing? (2) What motivations are reported? (3) What are its health and social impacts?ObjectiveThe objective of this scoping review is to map evidence on prevalence, drivers, consequences, and interventions related to breast ironing.Method and analysisSearches will be conducted in MEDLINE (PubMed), CINAHL (EBSCOhost), Scopus, and Web of Science, with grey literature identified through Google Scholar and institutional repositories, including African Journals Online (AJOL). The review will follow the Joanna Briggs Institute (JBI) scoping review methodology, and study selection will be reported in accordance with PRISMA-ScR guidelines. Two reviewers will independently screen titles/abstracts and full texts, while two reviewers will extract data. Findings will be synthesised using a descriptive analytical approach and presented as a structured narrative summary.DiscussionThis review will strengthen the existing evidence base on the impact of breast ironing across Africa. Across studies, common motivations are expected to centre on perceived protection from sexual attention, early pregnancy, sexual violence, or forced marriage, while consistently reporting substantial physical harms—such as pain and tissue damage—and psychological consequences, including fear, shame, trauma, and loss of bodily autonomy. Recognising the practice within gender-based violence legislation may enhance legal accountability and protection for girls, while targeted training for healthcare providers and community-based education initiatives may support efforts to prevent the practice and mitigate its health and social consequences.
This study examines the harsh and vulgar language found in public graffiti in
the capital of Kosovo, focusing on the linguistic analysis of slogans encountered on the walls of
Pristina such as “Death to the oligarchs,” “Men kill women, the state remains silent,” “Fuck police,”
“Porno,” “Adios mother fucker,” “Kill hip hop.” Employing a sociolinguistic and critical discourse
perspective, we analyze the lexicon in use, the syntactic structures, and the semantic connotations
of these phrases, as well as their stylistic and pragmatic functions within contexts of protest,
rebellion, and identity expression. We discuss how Pristina’s graffiti shape public discourse and the
local sociolinguistic milieu. The study also incorporates references to scholarly literature on vulgar
language and urban art, alongside observations concerning Kosovo’s legislation on graffiti and
offensive language in public spaces. Our findings indicate that the use of vulgar language in graffiti
is closely tied to expressions of social and political discontent; their content is inherently protest-
oriented, critical, or identity-driven, while the presence of profanities underscores a desire to shock
the public and challenge the sanctioned norms of official discourse. Nevertheless, graffiti remain
illegal in Kosovo and are frequently treated as property damage—evidenced by reports that “graffiti
continue to be outlawed, and the police still arrest”. This phenomenon highlights the tensions
between urban art as a form of free expression and the legal constraints imposed on public spaces.
El populismo se caracteriza por un discurso que contrapone el pueblo a las élites y coloca a un líder o partido como representante de ese pueblo. En la mayoría de los discursos populistas, el pueblo se identifica con la nación, definida en términos orgánicos y culturales. El artículo considera las reformas legales propuestas y aplicadas por líderes y partidos populistas para dar forma al vínculo jurídico de la nacionalidad a partir de su concepción política de la nación. Es posible en este sentido identificar algunas estrategias recurrentes, como la restricción del jus soli, la imposición de mayores exigencias para la obtención de la nacionalidad por naturalización o el rechazo de la doble nacionalidad.
IntroductionIn today's fast-paced world, the growing dynamics of the global economy, society, and technology have given rise to new business models. Among these, startups have emerged as vital engines of economic development due to their innovative potential. These emerging companies contribute significantly to job creation and economic advancement by introducing creative business models and cutting-edge technologies. However, like many social phenomena, business paradigms are evolving. A notable trend is the increasing recognition of startups as the key drivers of economic growth and innovation, attracting international attention as countries strive to enhance their startup ecosystems. Iran is no exception to this movement with various initiatives aimed at developing its startup sector. Despite this progress, much of the existing research on startups has overlooked the specific requirements for their establishment in particular contexts, often taking a generalized approach. Additionally, many studies have focused on macro-level analyses, neglecting a deeper understanding of the perspectives of individuals involved in this field at the micro level. To address these gaps, the present study aimed to analyze the process of becoming a startup and the associated contexts and requirements in the city of Isfahan, utilizing an economic sociology framework. By concentrating on the viewpoints of startup managers, this study sought to provide a clearer understanding of these requirements within this specific context. Materials & MethodsThis qualitative research grounded in the interpretive paradigm and utilizing the thematic network approach (Attride-Stirling, 2001) was designed to uncover meaningful patterns within the data. The study population consisted of all startup and knowledge-based company managers in the city of Isfahan. From this group, 14 experienced managers of active startups—each with a minimum of 5 years in innovation and technology—were selected through purposive sampling to provide rich, in-depth insights on the topic. Data collection was conducted via semi-structured in-depth interviews from early April to late November 2024. These discussions centered on the managers' experiences in the startup formation process and their identification of key requirements from their perspectives. The data were analyzed using MAXQDA 2020 software, following the systematic steps of the thematic network approach, which included initial coding, organizing themes at both basic and global levels, and explicating the organizing themes while mapping the relationships between them. To enhance the credibility and reliability of the research findings, two key mechanisms were employed: member checking to confirm that the findings accurately reflected the participants' experiences and an independent evaluation by an external auditor familiar with qualitative research methods and economic sociology, ensuring an impartial review of the analysis process. Discussion of Results & ConclusionThe analysis of startup managers' perspectives in Isfahan highlighted that the requirements for becoming a startup could be encapsulated within a comprehensive theme: "Becoming a Startup as an Innovation Ecosystem". This overarching theme elucidated the formation and development of a dynamic, interactive network composed of diverse structural, individual, micro-, macro-, and economic-social elements, all of which contributed to the growth and success of entrepreneurship in the form of startups within a specific geographical area. This innovative ecosystem functioned as a coordinated and synergistic system.The key organizing themes within this ecosystem included:Startup Ecosystem: Encompassing innovative policymaking structures, startup legislation, supportive government initiatives, internationalization, and the startup communityStrategic Idea: Serving as an innovative and market-reality-based foundationStartup Mentality: Reflecting the leadership, entrepreneurial spirit, and risk-taking attributes of foundersAffinity of Strategic Financial Approach: Manifested in funding strategies and the alignment between investors and foundersTeam Dynamics: Emphasizing the importance of teamwork and specialized division of laborMarket Realism: Informed by accurate analyses of customer needsStartup Networking: Focusing on creating and strengthening connectionsAccording to the managers of Isfahan startups, the formation, strengthening, and sustainability of these ventures relied on the interaction and synergy of these organizing themes at various levels. A robust startup ecosystem created a comprehensive platform that connected all elements and, through diverse supports, bolstered innovation and sustainability of startups. Within this framework, the strategic idea served as the initial catalyst, while the startup mentality embodied the essential characteristics of founders. Financial affinity acted as a critical survival factor, team dynamics provided the driving force, market realism guided actions, and networking served as a lever for development. Together, these components facilitated the process of becoming a startup in conjunction with the startup ecosystem. In conclusion, "Becoming a Startup as an Innovation Ecosystem" illustrated the interconnectedness and synergy of essential requirements for innovation. Without the presence and mutual interaction of these elements at various layers of business, the process of establishing a startup might be hindered or indefinitely delayed.
The study aims to analyse demographic, economic, and social aspects and identify the impact of migration in EU Member States, especially in Romania. It focuses on finding methods for more efficient migration management and faster, higher-level immigrant integration. These efforts aim to benefit both the native population and migrants. The study is innovative due to its interdisciplinary methodology. It couples economic and social research from fields such as macroeconomics and sociology with an analysis of migration policies. Main findings reveal that migration helps mitigate demographic decline and supports economic development by increasing labour force employment. The immigrants' integration is positively influenced by best practices, such as Sweden’s labour market model, which combines strong collective bargaining mechanisms, high union membership, and coordinated wage-setting processes, as well as relatively flexible employment protection legislation. The research conclusions and policy recommendations aim to transform the challenge of migration into an opportunity that stimulates sustainable economic and social development and addresses labour market deficits in Romania.
Melissa Liset Santos-Peláez, Karla Stefanny Huertas-Vilca, Franklin Cordova-Buiza
El objetivo de la investigación se orienta a determinar los criterios jurisdiccionales que se consideran para el otorgamiento de medidas de protección frente a hechos de violencia intrafamiliar en Latinoamérica, tomando como base de datos a páginas registradas como Legis Pe, Colectivo Derecho de Familia y Corte Constitucional de Colombia. La metodología aplicada fue proyectada bajo un enfoque cualitativo, de diseño no experimental y con un nivel descriptivo aplicando la revisión documental a través del análisis de tres jurisprudencias emitidas en procesos judiciales en los países de Perú, Argentina y Colombia. Según el análisis se determinó que, en Perú los jueces emiten medidas de protección extra y ultra petita aplicando criterios jurisdiccionales. Respecto a Argentina, se identificó que los conflictos de violencia contra la mujer se abordan bajo la perspectiva de la afectación a derechos humanos y la libertad individual que ello implica. Por otro lado, para Colombia, al dictarse medidas de protección, el órgano judicial se basa en el enfoque diferencial de género. Finalmente, se concluye que, en Perú, Argentina y Colombia, los órganos judiciales aplican criterios jurisdiccionales orientados a un fin preventivo, pues, se busca prever nuevos actos de violencia en cualquiera de sus modalidades.
Positive social interactions can occur in groups of many shapes and sizes, spanning from small and private to large and open. However, social media tends to binarize our experiences into either isolated small groups or into large public squares. In this paper, we introduce Burst, a social media design that allows users to share and curate content between many spaces of varied size and composition. Users initially post content to small trusted groups, who can then burst that content, routing it to the groups that would be the best audience. We instantiate this approach into a mobile phone application, and demonstrate through a ten-day field study (N=36) that Burst enabled a participatory curation culture. With this work, we aim to articulate potential new design directions for social media sharing.
Understanding and predicting user behavior on social media platforms is crucial for content recommendation and platform design. While existing approaches focus primarily on common actions like retweeting and liking, the prediction of rare but significant behaviors remains largely unexplored. This paper presents a hybrid methodology for social media user behavior prediction that addresses both frequent and infrequent actions across a diverse action vocabulary. We evaluate our approach on a large-scale Bluesky dataset containing 6.4 million conversation threads spanning 12 distinct user actions across 25 persona clusters. Our methodology combines four complementary approaches: (i) a lookup database system based on historical response patterns; (ii) persona-specific LightGBM models with engineered temporal and semantic features for common actions; (iii) a specialized hybrid neural architecture fusing textual and temporal representations for rare action classification; and (iv) generation of text replies. Our persona-specific models achieve an average macro F1-score of 0.64 for common action prediction, while our rare action classifier achieves 0.56 macro F1-score across 10 rare actions. These results demonstrate that effective social media behavior prediction requires tailored modeling strategies recognizing fundamental differences between action types. Our approach achieved first place in the SocialSim: Social-Media Based Personas challenge organized at the Social Simulation with LLMs workshop at COLM 2025.
On the basis of several universal and regional international documents, Bosnia and Herzegovina, as well as a number of modern states, foresees the criminal offense of terrorism in several different forms of manifestation, but with identical content, characteristics, elements, legal description, legal nature, that is, forms or types of manifestation. It is an extremely serious, dangerous crime, with an international content, that is, with international basis for prescribing criminal responsibility and punishment. Due to the high degree of social danger of various forms of manifestations of terrorism, all modern criminal legislations move the limit of punishment to the previous stage - to the stage of preparation of criminal offenses, the undertaking of which, through physical or psychological activities, creates the conditions or prerequisites for the perpetration of one of the criminal offenses of terrorism in general, or to a faster, easier, simpler or more efficient way. In the positive law in Bosnia and Herzegovina, numerous preliminary actions that precede the perpetration of criminal offenses of terrorism in general or preliminary actions that contribute to their more efficient, successful or better execution are also provided as independent criminal offenses. The paper investigates and problematizes the system, concept, content, elements and characteristics, and forms of manifestation of the preparation of criminal offenses of terrorism in the criminal legislation of Bosnia and Herzegovina, especially in the context of international standards.
Background. The combination of internal and external challenges faced by the modern Russian state and society predetermine a high demand for innovation. It determines the high relevance of research into the features of state innovation policy, which is consid-ered as a type of legal policy. The purpose of the work is to consider the features of legal regulation of innovation policy, identify problems and propose ways to solve them. Materi-als and methods. The implementation of the research tasks was achieved on the basis of an analysis of regulations, strategic planning documents, as well as scientific research devoted to the implementation of innovation policy in various areas of public relations. The meth-ods of dialectics, induction, synthesis and formal legal analysis predetermined the possibil-ity of obtaining formulated conclusions. Results. An analysis of the provisions of normative sources allowed us to come to the conclusion that the conceptual apparatus of innovation policy is inconsistent. This conclusion confirms the appeal to scientific research on relevant topics, pointing to the inconsistency of the regulatory framework with the actual existing social relations. Conclusions. The author has formulated conclusions about the advisability of clarifying the concept of «innovation» in relevant legislation, as well as developing the principle of transparency in the implementation of the state’s innovation policy. In addition, the role of balance between ensuring private and public interests in this industry is empha-sized.
Reinforcement learning (RL) enables social robots to generate trajectories without relying on human-designed rules or interventions, making it generally more effective than rule-based systems in adapting to complex, dynamic real-world scenarios. However, social navigation is a safety-critical task that requires robots to avoid collisions with pedestrians, whereas existing RL-based solutions often fall short of ensuring safety in complex environments. In this paper, we propose SoNIC, which to the best of our knowledge is the first algorithm that integrates adaptive conformal inference (ACI) with constrained reinforcement learning (CRL) to enable safe policy learning for social navigation. Specifically, our method not only augments RL observations with ACI-generated nonconformity scores, which inform the agent of the quantified uncertainty but also employs these uncertainty estimates to effectively guide the behaviors of RL agents by using constrained reinforcement learning. This integration regulates the behaviors of RL agents and enables them to handle safety-critical situations. On the standard CrowdNav benchmark, our method achieves a success rate of 96.93%, which is 11.67% higher than the previous state-of-the-art RL method and results in 4.5 times fewer collisions and 2.8 times fewer intrusions to ground-truth human future trajectories as well as enhanced robustness in out-of-distribution scenarios. To further validate our approach, we deploy our algorithm on a real robot by developing a ROS2-based navigation system. Our experiments demonstrate that the system can generate robust and socially polite decision-making when interacting with both sparse and dense crowds. The video demos can be found on our project website: https://sonic-social-nav.github.io/.
The analysis of the problem field is a serious problem from the methodological and methodical point of view. The solution of this problem becomes particularly difficult in cases when the object under study is characterized by a high level of structural and process diversity, has a dynamic character, i. e. it is constantly evolving, and exists in many variants with the presence of the invariant enshrined in international acts and legislation of most states. The end of the last century was a period of rethinking of many concepts that define the complex processes of political and social interaction of various levels and elements of the system of power and public administration in Russia. The adoption of the Constitution of the Russian Federation in 1993 put forward fundamental problems that needed to be solved to move the country along the path of democratization, build a market economy and form an effective governing system. Article 12 of the first chapter establishes the autonomy of local self-government as an institution, guarantees its protection from excessive state influence. This provision reflects the global trend of consolidating the right to local self-government in democratic states. However, the European Charter of Local Self-Government includes a provision on the independence of local self-government in resolving issues of local significance only within the framework of state legislation, i. e. it establishes its subordinate nature. The latter provision automatically makes local self-government part of the unified system of public power and public administration, which is reflected in the corresponding amendment to Ch. 8 of the Constitution of the Russian Federation “Local self-government” in 2020. This makes t relevant he problem of the local authorities ‘ own powers, the division of functions between them and state authorities to achieve the fundamental goal of the modern state — to ensure an optimal uniform quality of life throughout the territory. The purpose of the article is to characterize the problem field in which the concepts of “public power” and “public administration” are defined and analysed in the context of considering local self-government as a key actor of both systems. The objectives of the research are to determine the boundaries of this problem field, its structure, as well as the difference in approaches to this problem in the works of Russian and foreign authors, including scientists from Central Asian countries.
Political institutions and public administration (General)
Constantin Marius Profiroiu, Ionuț Ciprian Negoiță
<p>This article provides an account of the transformational capacity of Romanian public administration in relation to four main aspects: (1) human resource performance and integrity; (2) territorial, functional and institutional decentralization; (3) public policies and (4) capitalizing on the digital and innovative component. The Romania case study highlights the gradual transformation of public administration in the last 30 years, as a reaction to the emergence of economic, social and political crises. For an imperative and irreversible change, we have identified directions for capitalizing on opportunities and good practices in the matter, in the context of the intensified integration process in NATO and the EU. We have analyzed the strategic documents on strengthening and accelerating the transformation of public administration and highlighted the need for the interconnection and interdependence of its four pillars to meet the specific objectives of Horizon 2030. For decision-makers, practitioners and researchers, this article aims to stimulate and contribute to the dedicated public debate and consultation of coherent, predictable and sustainable legislation and practices in the matter.</p>
Political institutions and public administration (General)
Wahyu Sasongko, Hamzah Hamzah, Harsa Wahyu Ramadhan
et al.
Indonesia's heterogeneity with diverse ethnic groups, languages, and customs, creates a potential for social conflict, which Law No. 7 of 2012 aims to address by establishing traditional institutions for conflict resolution. This research employs a legal concept approach focused on Lampung customary law, revealing that the law lacks specific procedural regulations and fails to empower traditional institutions adequately. However, Lampung customary law can effectively resolve social conflicts through the internalized values of Piil Pesenggiri and the convening of perwatin adat meetings for rembuk pekon and consensus-building. Therefore, it is recommended that future regulations on social conflict resolution incorporate Lampung customary law principles into national legislation, and that local governments actively engage traditional institutions to foster a supportive environment for customary law.
Law in general. Comparative and uniform law. Jurisprudence
This opening editorial aims to interest researchers and encourage novel research in the closely related fields of sociophysics and computational social science. We briefly discuss challenges and possible research directions in the study of social phenomena, with a particular focus on opinion dynamics. The aim of this special issue is to allow physicists, mathematicians, engineers and social scientists to show their current research interests in social dynamics, as well as to collect recent advances and new techniques in the analysis of social systems.
The massive spread of visual content through the web and social media poses both challenges and opportunities. Tracking visually-similar content is an important task for studying and analyzing social phenomena related to the spread of such content. In this paper, we address this need by building a dataset of social media images and evaluating visual near-duplicates retrieval methods based on image retrieval and several advanced visual feature extraction methods. We evaluate the methods using a large-scale dataset of images we crawl from social media and their manipulated versions we generated, presenting promising results in terms of recall. We demonstrate the potential of this method in two case studies: one that shows the value of creating systems supporting manual content review, and another that demonstrates the usefulness of automatic large-scale data analysis.
Chiyu Zhang, Muhammad Abdul-Mageed, El Moatez Billah Nagoudi
With the proliferation of social media, many studies resort to social media to construct datasets for developing social meaning understanding systems. For the popular case of Twitter, most researchers distribute tweet IDs without the actual text contents due to the data distribution policy of the platform. One issue is that the posts become increasingly inaccessible over time, which leads to unfair comparisons and a temporal bias in social media research. To alleviate this challenge of data decay, we leverage a paraphrase model to propose a new persistent English Twitter dataset for social meaning (PTSM). PTSM consists of $17$ social meaning datasets in $10$ categories of tasks. We experiment with two SOTA pre-trained language models and show that our PTSM can substitute the actual tweets with paraphrases with marginal performance loss.
Traffic jams on roadways, echo chambers on social media, crowds of moving pedestrians, and opinion dynamics during elections are all complex social systems. These applications may seem disparate, but some of the questions that they motivate are similar from a mathematical perspective. Across these examples, researchers seek to uncover how individual agents -- whether drivers, Twitter accounts, pedestrians, or voters -- are interacting. By better understanding these interactions, mathematical modelers can make predictions about the group-level features that will emerge when agents alter their behavior. In this tutorial, which is based on the lecture that I gave at the 2021 American Mathematical Society Short Course, I introduce some of the terms, methods, and choices that arise when building such data-driven models. I discuss the differences between models that are statistical or mathematical, static or dynamic, spatial or non-spatial, discrete or continuous, and phenomenological or mechanistic. For concreteness, I also describe models of two complex systems, election dynamics and pedestrian-crowd movement, in more detail. With a conceptual approach, I broadly highlight some of the challenges that arise when building and calibrating models, choosing complexity, and working with quantitative and qualitative data.
Images shared on social media help crisis managers gain situational awareness and assess incurred damages, among other response tasks. As the volume and velocity of such content are typically high, real-time image classification has become an urgent need for a faster disaster response. Recent advances in computer vision and deep neural networks have enabled the development of models for real-time image classification for a number of tasks, including detecting crisis incidents, filtering irrelevant images, classifying images into specific humanitarian categories, and assessing the severity of the damage. To develop robust real-time models, it is necessary to understand the capability of the publicly available pre-trained models for these tasks, which remains to be under-explored in the crisis informatics literature. In this study, we address such limitations by investigating ten different network architectures for four different tasks using the largest publicly available datasets for these tasks. We also explore various data augmentation strategies, semi-supervised techniques, and a multitask learning setup. In our extensive experiments, we achieve promising results.