María Zitto Soria, Alberto López Rosado, Jaime Tatay
Abstract A solution to the current socio-environmental crisis requires consensus and agreement between people and groups with different visions (Pascual et al. 2023). Regardless of individual ideologies or beliefs, it is essential to find common ground and act collectively to address a global problem. This paper identifies the similarities and differences between the anthropological vision underlying the UN documents, in particular the 1972 Stockholm conference, and the Catholic anthropological vision of the encyclical Laudato si’. The analysis delves deep into Stockholm 72 (S72) and its historical context for two reasons. First, S72 was the first major international conference to comprehensively address the relationship between human economic development and environmental protection, leading the way for subsequent conferences in Rio, Kyoto, Johannesburg, Copenhagen, Rio+20, Paris, etc., which have led (so far) to the 2030 Agenda. Second, there is a need to establish a general methodology of anthropological analysis, hitherto non-existent, applicable to UN conferences. Delving into the very first one is instrumental to understanding how the social, economic, and philosophical influences of the time are reflected in its vision of the individual and collective human being, in its contents, and in the global environmental policies that followed. The comparison of S72 with the ethical vision of Laudato si’, and more broadly with Catholic Social Teaching (CST), reveals many anthropological points of convergence. These provide a strong basis for constructive dialogue between UN documents and the Christian worldview, which also strongly promotes the care of our common home.
History of scholarship and learning. The humanities, Social Sciences
Agricultural digitization is crucial for enhancing agricultural productivity and efficiency and promoting green low-carbon development. Based on the provincial panel data of China from 2012 to 2021, this study employs the entropy value method and the GML index based on SBM-DDF to quantify agricultural digitization and agricultural green total factor productivity. It utilizes two-way fixed effects, group regression, and threshold effect models to examine the influence of agricultural digitization in agriculture on the green and carbon-reduction progression of farming practices, as well as to clarify the underlying mechanisms behind these effects. The study finds that agricultural digitalization significantly promotes agricultural green low-carbon development. Green innovation and scale operation mediate the impact path of agricultural digitalization, and there is a threshold effect of digital financial inclusion. Moreover, agricultural digitization has a significant impact on the eastern region and a smaller impact on the central and western areas, and the effect is better in regions with high levels of innovation. The results of the study provide a scientific basis for the synergizing of agricultural digitization and agricultural development that is green and low-carbon, as well as for the construction of relevant subjects for interest cooperation and sharing mechanisms.
Paula López Caballero y Ariadna Acevedo-Rodrigo, Más allá de la identidad indígena. Ciudad de México, Grano de Sal/Universidad Nacional Autónoma de México, 2025.
Context: X, formerly known as Twitter, is one of the largest social media platforms and has been widely used for communication during research conferences. While previous studies have examined how users engage with X during these events, limited research has focused on analyzing the content posted by computer science conferences. Objective: This study investigates how conferences from different areas of computer science perform on social media by analyzing their activity, follower engagement, and the content posted on X. Method: We collect posts from 22 computer science conferences and conduct statistical experiments to identify variations in content. Additionally, we perform a manual analysis of the top five posts for each engagement metric. Results: Our findings indicate statistically significant differences in category, sentiment, and post length across computer science conference posts. Among all engagement metrics, likes were the most common way users interacted with conference content. Conclusion: This study provides insights into the social media presence of computer science conferences, highlighting key differences in content, sentiment, and engagement patterns across different venues.
Enhancing economic resilience is crucial to sustainable development. However, issues such as resource misallocation and financing difficulties have severely impacted supply chain stability and security. The rise of digital finance presents potential solutions to these problems. Based on panel data from 30 provinces in China from 2011 to 2020, this study explores the mechanisms and pathways through which digital finance enhances economic resilience. The results reveal four key findings. First, the development of digital finance significantly enhances economic resilience by improving innovation capabilities and consumption vitality. Second, a high degree of marketization strengthens the promoting effect of digital finance on economic resilience. Third, in areas with higher levels of industrial advancement or lower levels of traditional financial development, the enhancement effect of digital finance on economic resilience is more significant. Fourth, digital finance significantly improved the economic resilience of geographically adjacent areas through spatial spillover effects. Overall, this study provides a new perspective on the impact of digital finance on economic resilience in developing countries such as China. In addition to its academic contributions, this study offers detailed practical implications.
Technology-facilitated abuse in relationships (TAR) is a relatively new form of intimate partner violence. Research exploring the impact of TAR on young people is limited, and while robust measures of TAR itself are emerging, measures of TAR impact lack evidence of validity. A mixed-methods approach was used to establish preliminary face and content validity for the measurement of TAR impact. Youth discussion groups (n = 38) revealed that (1) distress is favored over upset as a preferred measure of TAR impact, and (2) fear is an appropriate impact measure for some TAR behaviors. In an online survey, frontline practitioners (n = 171) perceived and subsequently rated a total of 54 TAR behaviors in the upper half of the severity range on fear and distress, with 6 behaviors ranking among each of the top 10 most fear- and distress-inducing behaviors. These findings provide evidence of both face and content validity for the use of fear and distress measures when seeking to understand the impact of TAR. Scholars, practitioners, and educators alike can use this evidence to enhance the validity of investigations into TAR and its impact, to support victims of TAR, and to improve TAR education among youth.
Background: Digestive issues are recognized as significant contributors to various chronic diseases, including obesity, diabetes, and cardiovascular disease. Barley, a traditional grain, offers considerable promise in addressing these health challenges due to unique nutritional and bioactive compounds. Objective: This review examines the therapeutic potential of various parts of barley, underutilized resource, for chronic disease prevention and management. Method: ology: A comprehensive literature search was conducted across multiple databases like Google Scholar, PubMed, and ISI Web of Science, to identify nutritional components and functional ingredients in barley that contribute to gut health and chronic disease mitigation. Results: The finding suggests that humans digest barley starch more slowly than wheat and rice, which benefits chronic disease management. Barley's high-molecular-weight β-glucan high content acts as a prebiotic, promotes gut health through microbiome modulation and short-chain fatty acid production, potentially preventing colon cancer and boosting immunity. Recent studies on exploring barley grass of high land showed functional ingredients such as flavonoids, saponarin lutonarin, superoxide dismutase, gamma-aminobutyric acid, polyphenols K, Ca, Se, tryptophan chlorophyll, and vitamins, suggesting potential for enhanced antioxidant activity and improved management of chronic conditions like diabetes, cholesterol, hypertension, cardiovascular health, liver protection, and even boosted immunity. Conclusion: This review underscores the therapeutic potential of barley and its components in chronic disease management, highlighting the need for well-designed clinical trials to translate these findings into effective interventions.
Recent advancements in artificial intelligence, particularly with the emergence of large language models (LLMs), have sparked a rethinking of artificial general intelligence possibilities. The increasing human-like capabilities of AI are also attracting attention in social science research, leading to various studies exploring the combination of these two fields. In this survey, we systematically categorize previous explorations in the combination of AI and social science into two directions that share common technical approaches but differ in their research objectives. The first direction is focused on AI for social science, where AI is utilized as a powerful tool to enhance various stages of social science research. While the second direction is the social science of AI, which examines AI agents as social entities with their human-like cognitive and linguistic capabilities. By conducting a thorough review, particularly on the substantial progress facilitated by recent advancements in large language models, this paper introduces a fresh perspective to reassess the relationship between AI and social science, provides a cohesive framework that allows researchers to understand the distinctions and connections between AI for social science and social science of AI, and also summarized state-of-art experiment simulation platforms to facilitate research in these two directions. We believe that as AI technology continues to advance and intelligent agents find increasing applications in our daily lives, the significance of the combination of AI and social science will become even more prominent.
Privacy is a human right. It ensures that individuals are free to engage in discussions, participate in groups, and form relationships online or offline without fear of their data being inappropriately harvested, analyzed, or otherwise used to harm them. Preserving privacy has emerged as a critical factor in research, particularly in the computational social science (CSS), artificial intelligence (AI) and data science domains, given their reliance on individuals' data for novel insights. The increasing use of advanced computational models stands to exacerbate privacy concerns because, if inappropriately used, they can quickly infringe privacy rights and lead to adverse effects for individuals -- especially vulnerable groups -- and society. We have already witnessed a host of privacy issues emerge with the advent of large language models (LLMs), such as ChatGPT, which further demonstrate the importance of embedding privacy from the start. This article contributes to the field by discussing the role of privacy and the issues that researchers working in CSS, AI, data science and related domains are likely to face. It then presents several key considerations for researchers to ensure participant privacy is best preserved in their research design, data collection and use, analysis, and dissemination of research results.
Understanding human social behaviour is crucial in computer vision and robotics. Micro-level observations like individual actions fall short, necessitating a comprehensive approach that considers individual behaviour, intra-group dynamics, and social group levels for a thorough understanding. To address dataset limitations, this paper introduces JRDB-Social, an extension of JRDB. Designed to fill gaps in human understanding across diverse indoor and outdoor social contexts, JRDB-Social provides annotations at three levels: individual attributes, intra-group interactions, and social group context. This dataset aims to enhance our grasp of human social dynamics for robotic applications. Utilizing the recent cutting-edge multi-modal large language models, we evaluated our benchmark to explore their capacity to decipher social human behaviour.
Este artigo tem por objetivo discutir o crescimento das atividades criativas, que fazem interface com o turismo, nas 27 capitais brasileiras e nas cidades criativas reconhecidas pela Organização das Nações Unidas para a Educação, a Ciência e a Cultura de Santos (SP) e Paraty (RJ). Para tanto, realizou-se uma aplicação estatística com dados da Relação Anual de Informações Sociais de 2011 a 2020. Para comparar as potencialidades locais em diferentes períodos, optou-se pelo uso do quociente locacional, shift-share e seu desdobramento Esteban-Marquillas. Os resultados encontrados ilustram que, a partir de 2017, as taxas de encolhimento das atividades criativas foram superiores ao encolhimento das atividades convencionais. O quociente locacional elucida que não houve mudanças estruturais abruptas em termos de concentração espacial das atividades criativas, o shift-share enfatiza o agravamento do encolhimento da economia criativa, coincidindo com os períodos das crises econômicas/institucionais e de distanciamento social derivado da covid-19.
Communication. Mass media, Social sciences (General)
Rebeca-Illiana Arévalo-Martínez, Guillermo García Mayo
La información que se hace pública por parte de las organizaciones privadas que cotizan en la Bolsa Mexicana de Valores (BMV), tiene como objetivo dar cuenta principalmente de sus resultados financieros, pero también incluye información relevante sobre su operación, filosofía organizacional y actividades que permitan evaluar su rol dentro de la sociedad, sus contribuciones e impacto. Sin embargo, dada la cantidad de información que actualmente existe en la web, y la dificultad que se tiene para reconocer la importancia de la información a la que se tiene acceso, se plantea en este artículo una serie de categorías para evaluar la calidad de la comunicación (logística, atención, utilidad e influencia) y que se presenta en el informe anual de 2021 de los cuatro supermercados en México que cotizan en la bmv con la finalidad de relacionarlas con la formación de capital social (Bourdieu, 1990; Lin, 2001), cohesión social (Durkheim, 2007) e impacto social (Esteves et al., 2012). La metodología empleada fue cualitativa por medio de análisis de contenido. Entre los principales hallazgos se encuentra que los informes anuales cumplen con los niveles de calidad de la comunicación, aunque la atención que dan a sus criterios es diferente en cada caso. En este sentido, la calidad de la comunicación tiene un impacto social en sus públicos a través del contenido que incluyen aspectos que potencian la cohesión y el capital social que generan este tipo de organizaciones.
We present the Multi-Modal Discussion Transformer (mDT), a novel methodfor detecting hate speech in online social networks such as Reddit discussions. In contrast to traditional comment-only methods, our approach to labelling a comment as hate speech involves a holistic analysis of text and images grounded in the discussion context. This is done by leveraging graph transformers to capture the contextual relationships in the discussion surrounding a comment and grounding the interwoven fusion layers that combine text and image embeddings instead of processing modalities separately. To evaluate our work, we present a new dataset, HatefulDiscussions, comprising complete multi-modal discussions from multiple online communities on Reddit. We compare the performance of our model to baselines that only process individual comments and conduct extensive ablation studies.
Over the past decade, an explosion in the availability of education-related datasets has enabled new computational research in education. Much of this work has investigated digital traces of online learners in order to better understand and optimize their cognitive learning processes. Yet cognitive learning on digital platforms does not equal education. Instead, education is an inherently social, cultural, economic, and political process manifesting in physical spaces, and educational outcomes are influenced by many factors that precede and shape the cognitive learning process. Many of these are social factors like children's connections to schools (including teachers, counselors, and role models), parents and families, and the broader neighborhoods in which they live. In this article, we briefly discuss recent studies of learning through large-scale digital platforms, but largely focus on those exploring sociological aspects of education. We believe computational social scientists can creatively advance this emerging research frontier-and in doing so, help facilitate more equitable educational and life outcomes.
Reseña con breve descripción de los contenidos que se desarrollan en la obra ‘La transparencia de los partidos políticos (2016-2019). Entre la estrategia de comunicación y su apertura efectiva’, escrita por la Doctora María Díez Garrido y publicada por la colección de monografías del Congreso de los Diputados en 2021. Se trata de un monográfico que analiza el estado actual de la transparencia en los partidos políticos españoles desde el punto de vista de la comunicación y la política durante las elecciones celebradas entre 2016 y 2019. La obra aporta una visión general y completa de la transparencia en la política, además de presentar las pautas necesarias para elaborar una Guía de buenas prácticas para partidos políticos abiertos.
Political institutions and public administration (General), Accounting. Bookkeeping
В статье делается попытка переопределения термина «сообщество» применительно к исследованиям площадок группового общения транснациональных мигрантов в интернете. Сегодня платформы виртуальных социальных сетей позволяют создавать группы общения, объединяющие людей с общими интересами, но не обязательно знакомых друг с другом. В исследовательской литературе для анализа такого рода феноменов широкое распространение получило понятие «сообщество». Однако насколько такое решение является правомерным? Всегда ли онлайн-группы являются сообществами? Какие механизмы обеспечивают их активность? Для ответа на данные вопросы автор проводит концептуальный анализ различных антропологических и социологических моделей сообщества в контексте их приложения к онлайн-среде. На основании проведенного анализа формулируется определение сообщества как состояния максимальной солидаризации группы, возникающей в фокусированных коллективных ритуалах взаимодействия. В качестве теоретико-методологического основания статьи выступает теория ритуалов взаимодействия Рэндалла Коллинза, которая позволяет определить цепочки успешных ритуалов как ключевой механизм, лежащий в основе устойчивой групповой активности. Успешные ритуалы способствуют производству и/или воспроизводству символов идентичности группы и эмоциональной энергии (готовности вступать в схожие взаимодействия). Выработанный способ концептуализации применяется к исследованию двух русскоязычных Facebook-групп (деятельность социальной сети запрещена на территории РФ), объединяющих трудовых мигрантов из стран СНГ в Южной Корее и из стран Средней Азии в России. Проведенный анализ демонстрирует, что воспроизводство активности онлайн-групп в значительной степени опирается на эмоционально насыщенные символы, даже если основная часть сообщений сосредоточена вокруг сугубо инструментальных целей (таких как поиск вакансий). Тем не менее различия в культурном капитале могут препятствовать возникновению групповой солидарности, даже если участники номинально разделяют общие эмоции по отношению к одному и тому же объекту внимания.
Благодарность. Мы благодарим Полину Антонову, Анастасию Бабикову, Елизавету Кучерову, Анастасию Лаптеву, Дарью Юдину, а также Наталью Трегубову за ценные комментарии к первым вариантам статьи и за помощь в сборе данных.
Using the example of the Kursk province, the article examines the main methods of government work with persons with dubious «political reliability», «potential» and «real» political criminals in the second half of the XIX - early XX centuries. This paper examines the types (investigative, judicial and administrative) of police supervision. Special attention is paid to the analysis of the public and secret (secret) modes of police surveillance. During the period under review, persons who, by their behavior, gave any reason for distrust (in political terms) were subject to secret (secret) supervision. Persons whose «political unreliability» was established «officially» were subordinated to public police supervision, but the decision of the authorities recognized that stricter measures of state coercion could not be applied to these persons to correct them. The study also provides grounds for establishing supervision over persons with questionable «political reliability», describes the mechanisms of interaction between different departments of the Kursk province that monitor the political situation in the region, the activities of «potential», «real» political criminals. At the end of the study, conclusions were drawn about the role of police surveillance (both public and secret) in the system of punitive and protective measures.
Archaeology, Law in general. Comparative and uniform law. Jurisprudence
Fighting the ongoing COVID-19 infodemic has been declared as one of the most important focus areas by the World Health Organization since the onset of the COVID-19 pandemic. While the information that is consumed and disseminated consists of promoting fake cures, rumors, and conspiracy theories to spreading xenophobia and panic, at the same time there is information (e.g., containing advice, promoting cure) that can help different stakeholders such as policy-makers. Social media platforms enable the infodemic and there has been an effort to curate the content on such platforms, analyze and debunk them. While a majority of the research efforts consider one or two aspects (e.g., detecting factuality) of such information, in this study we focus on a multifaceted approach, including an API,\url{https://app.swaggerhub.com/apis/yifan2019/Tanbih/0.8.0/} and a demo system,\url{https://covid19.tanbih.org}, which we made freely and publicly available. We believe that this will facilitate researchers and different stakeholders. A screencast of the API services and demo is available.\url{https://youtu.be/zhbcSvxEKMk}
Date of birth (DOB) has historically been considered as private information and safe to use for authentication, but recent years have seen a shift towards wide public sharing. In this work we characterize how modern social media users are approaching the sharing of birthday wishes publicly online. Over 45 days, we collected over 2.8M tweets wishing happy birthday to 724K Twitter accounts. For 50K accounts, their age was likely mentioned revealing their DOB, and 10% were protected accounts. Our findings show that the majority of both public and protected accounts seem to be accepting of their birthdays and DOB being revealed online by their friends even when they do not have it listed on their profiles. We further complemented our findings through a survey to measure awareness of DOB disclosure issues and how people think about sharing different types of birthday-related information. Our analysis shows that giving birthday wishes to others online is considered a celebration and many users are quite comfortable with it. This view matches the trend also seen in security where the use of DOB in authentication process is no longer considered best practice.
Luca Barni, María Ruiz-Muñoz, Manuel Gonzalez-Sanchez
et al.
Abstract Introduction There is no systematic review that analyzes the psychometric properties of questionnaires in Italian. Previous studies have analyzed the psychometric characteristics of instruments for the measurement of pathologies of upper limbs and their joints in different languages. The aim of the present study was to analyze the psychometric properties of the questionnaires published in Italian for the evaluation of the entire upper limb or some of its specific regions and related dysfunctions. Evidence acquisition For the development of this systematic review, the following databases were used: PubMed, Scopus, Cochrane, Dialnet, Cinahl, Embase and PEDro. The selection criteria used in this study were: studies of transcultural adaptation to Italian of questionnaires oriented to the evaluation of upper limbs or any of their structures (specifically shoulder, elbow and wrist/hand), and contribution of psychometric variables of the questionnaire in its Italian version. Evidence synthesis After reading the titles and applying the inclusion and exclusion criteria to the complete documents, 16 documents were selected: 3 for the upper limb, 8 for the shoulder, 1 for the elbow and 4 for the wrist and hand. The cross-sectional psychometric variables show levels between good and excellent in all the questionnaires. Longitudinal psychometric variables had not been calculated in the vast majority of the analyzed questionnaires. Conclusions Italian versions of the questionnaires show good basic structural and psychometric characteristics for the evaluation of patients with musculoskeletal disorders of the upper limb and its joints (shoulder, elbow and wrist/hand).
Computer applications to medicine. Medical informatics