Hasil untuk "Social pathology. Social and public welfare. Criminology"

Isabel García Domínguez

Los delitos de odio son un tema de actualidad que no ha eludido el ciberespacio. El objetivo de la investigación es analizar los delitos de odio online cometidos en la jurisprudencia española, abarcando el periodo 2018-2022. La metodología es la revisión sistemática de sentencias, con una muestra de 29 procedentes de Audiencias Provinciales, ya que las sentencias de los Juzgados de lo penal no suelen publicarse. El análisis de datos fue cuantitativo. Los resultados apuntaron que la mayoría de las sentencias versaron sobre el artículo 510 del Código Penal y fueron condenatorias. La red social más utilizada fue Facebook, seguida de Twitter, y la motivación discriminatoria predominante el racismo, encontrándose, frecuentemente, en combinación con otras. Este estudio ha encontrado evidencia favorable al aumento de las sentencias que versan sobre delitos de odio cometidos online, la aplicación restrictiva del artículo 510 del Código Penal y el mensaje intimidatorio como una característica esencial de las victimizaciones.

Dayana Christina R. de Souza Juliano

Resumo: A proposta estabelece o processo de luto à luta das mulheres mães em face da violência racial letal do Estado, a partir das concepções elencadas na Teoria da Reprodução Social. Temos como premissa que o engajamento ativista de mulheres mães é determinado pela continuidade do Trabalho de Cuidado. Nessas interfaces, destacamos as considerações provocativas dos Movimentos Sociais de Mulheres Negras. Este é um fruto do processo de doutoramento em Serviço Social.

Adeniyi Sunday Gbadegesin, Godwin O. Ikwuyatum

Common mental disorders (CMDs) have been on the rise in developing countries. This study set out to unravel the pattern of CMD prevalence in a traditional African city, Ibadan. The study, in addition to socio-economic and demographic variables, takes into cognisance the effect of some peculiar environmental variables. The Self-Reporting Questionnaire-20 was used for CMD screening, and the questionnaire was administered to 1,200 respondents in a cross-sectional survey approach. The results showed that the overall pattern of CMD prevalence is random (Global Moran’s I (P = 0.78, I = 0.00 and Z = 0.29)). Respondents without education reported the highest cases of CMD (48.6%). When combined together, migrants reported 52.5% of the CMDs. The significant variables are food security (β = −0.198), green space (β = −0.057), migration status (β = −0.054), flood-prone residence (β = 0.453), low-quality housing (β = −0.061), frequent recreation participation (β = −0.071), experience of spousal violence (β = 0.199), positive self-rated health (β = −0.134) and positive quality of life (β = −0.205). The predictors of CMD explained about 35.8% of the variation (R2) and an R value of 59.9%. The study showed that CMDs occur among most of the urban population. Adequate media sensitization will have significant ameliorating effects on urban residents.

HAMIDEH ADDELYAN RASI

The management of disaster recovery processes plays a vital role in reducing negative impacts and restoring routine in communities. These processes require precise planning, effective strategies, and coordination among various institutions to ensure resilience in the face of post-crisis challenges. The aim of this study is to identify the challenges and obstacles in the bio-psychosocial recovery process after a crisis. This qualitative study involved 20 experts in the fields of crisis and recovery. Data were collected through semi-structured interviews and analyzed using thematic analysis. The results are divided into two main sections: (a) challenges and complexities of the recovery pathway, and (b) efficiency and dynamism of recovery systems. In the first section, considering the current situation, the problems and barriers in the post-crisis recovery process are explained, including structural, management, and resource-related obstacles. The second section focuses on strategies for developing and strengthening recovery systems to enhance efficiency, flexibility, and dynamism in dealing with crises. The findings provide solutions to improve the performance and resilience of systems in the future.

Isura Manchanayaka, Zainab Razia Zaidi, Shanika Karunasekera et al.

The rise of social media has been accompanied by a dark side with the ease of creating fake accounts and disseminating misinformation through coordinated attacks. Existing methods to identify such attacks often rely on thematic similarities or network-based approaches, overlooking the intricate causal relationships that underlie coordinated actions. This work introduces a novel approach for detecting coordinated attacks using Convergent Cross Mapping (CCM), a technique that infers causality from temporal relationships between user activity. We build on the theoretical framework of CCM by incorporating topic modelling as a basis for further optimizing its performance. We apply CCM to real-world data from the infamous IRA attack on US elections, achieving F1 scores up to 75.3% in identifying coordinated accounts. Furthermore, we analyse the output of our model to identify the most influential users in a community. We apply our model to a case study involving COVID-19 anti-vax related discussions on Twitter. Our results demonstrate the effectiveness of our model in uncovering causal structures of coordinated behaviour, offering a promising avenue for mitigating the threat of malicious campaigns on social media platforms.

Tunazzina Islam, Dan Goldwasser

Grasping the themes of social media content is key to understanding the narratives that influence public opinion and behavior. The thematic analysis goes beyond traditional topic-level analysis, which often captures only the broadest patterns, providing deeper insights into specific and actionable themes such as "public sentiment towards vaccination", "political discourse surrounding climate policies," etc. In this paper, we introduce a novel approach to uncovering latent themes in social media messaging. Recognizing the limitations of the traditional topic-level analysis, which tends to capture only overarching patterns, this study emphasizes the need for a finer-grained, theme-focused exploration. Traditional theme discovery methods typically involve manual processes and a human-in-the-loop approach. While valuable, these methods face challenges in scalability, consistency, and resource intensity in terms of time and cost. To address these challenges, we propose a machine-in-the-loop approach that leverages the advanced capabilities of Large Language Models (LLMs). To demonstrate our approach, we apply our framework to contentious topics, such as climate debate and vaccine debate. We use two publicly available datasets: (1) the climate campaigns dataset of 21k Facebook ads and (2) the COVID-19 vaccine campaigns dataset of 9k Facebook ads. Our quantitative and qualitative analysis shows that our methodology yields more accurate and interpretable results compared to the baselines. Our results not only demonstrate the effectiveness of our approach in uncovering latent themes but also illuminate how these themes are tailored for demographic targeting in social media contexts. Additionally, our work sheds light on the dynamic nature of social media, revealing the shifts in the thematic focus of messaging in response to real-world events.

Ana Páez-Mérida, Alicia Montero Molera

Algunos estudios apuntan que las mujeres reciben un trato benévolo por parte de los jueces, mientras que otros muestran una respuesta penal más dura contra ellas. No obstante, la mayoría de las investigaciones han sido realizadas en el ámbito internacional y abordan esta cuestión en el sistema de penal de adultos, desconociendo qué sucede en el sistema de justicia juvenil. El objetivo de este trabajo es conocer cuál es la respuesta penal que dan los jueces a esta delincuencia y si existen diferencias por sexo. Para ello, se ha llevado a cabo una investigación exploratoria en la que se han revisado los expedientes de reforma de 522 menores enjuiciados en tribunales españoles. Si bien se han encontrado algunas diferencias en el tipo y la duración de las medidas impuestas según el sexo de los menores, estas podrían ser legítimas debido a que las chicas cometen delitos leves y son menos reincidentes.

Joakim Wahlström, Gabriella Olsson

Introduction: Protective factors of adolescent gambling at the school level and their buffering potential are scarcely explored in prior research. This study aims to examine the protective possibility of low student–teacher ratio on youth gambling, both directly and by moderating the effect of low school performance. Methods: Data were derived from the 2016 Stockholm school survey, collected among 5,221 grade 11 students (∼17–18 years) in 46 schools, with information on schools’ composition and student–teacher ratio obtained through registers. Gambling and risk gambling were coded as binary variables. School performance was captured by self-reported marks in three core subjects, dichotomised into average/above average and below average, respectively. Student-teacher ratio was used both as a continuous and trichotomised variable. Two-level binary logistic regression analyses were performed. Results: A below average school performance was associated with gambling and risk gambling but the association with gambling was only statistically significant at the 10%-level in the fully adjusted model. Student-teacher ratio was not directly associated with gambling and risk gambling but moderated the associations between school performance and both gambling and risk gambling, as these relationships were less pronounced in schools with a low student–teacher ratio. Conclusions: In sum, a low student–teacher ratio may protect students from gambling and risk gambling by buffering against the adverse effects of other risk factors, such as poor school performance. These findings suggest that a higher teacher density in upper secondary schools can be beneficial beyond school matters by positively influencing student behaviour outside of school.

Indrė Čergelytė-Podgrušienė, Vida Gudžinskienė

Diabetes mellitus is a disease during which certain processes in the body which maintain a normal blood glucose concentration become imbalanced. With diabetes, the level of blood glucose increases, affecting the entire metabolism. Diabetes mellitus is becoming a leading disease in paediatric endocrinology, and causes health problems and complications that can shorten life expectancy. In Lithuania, cases of type 1 diabetes mellitus in children have been registered since 1983. More than 995 children and young people (up to 19 years of age) were registered in 2019. On average, more than 80 children are diagnosed with diabetes in the country per year. After 10–20 years, poorly controlled diabetes can cause damage not only to the endocrine system, but also to other bodily systems: it can cause the appearance of diabetic retinopathy, diabetic neuropathy, chronic kidney disease, cardiovascular diseases (stroke, ischemic heart disease, peripheral vascular diseases), infertility problems, and foot complications. Moreover, in order to keep glucose levels as optimal as possible, children with diabetes need daily insulin injections, as without them they are not able to survive. Diabetes mellitus becomes a challenge for the whole family, as the rhythm of family life changes and additional responsibilities to maintain the stability of the child’s health are assumed. In order to control the disease, children and their parents need information, skills and values that can be acquired in various educational environments. Research conducted in Lithuania and abroad is focused on the treatment of patients with diabetes, disease management, and the psychological problems experienced by parents who have learned about their child’s illness. Nonetheless, this topic has not been extensively studied from an educational perspective, and there is a lack of research that analyses the diversity of environments in which the health competences of children with diabetes mellitus can be developed. Researchers note that the involvement of children with diabetes in the process of health competence development as well as their acquisition of knowledge and skills depend on their educational environments. By providing educational functions, the shapers of educational environments convey knowledge regarding health competence, teach, offer advice and demonstrate the necessary skills, as well as form value attitudes that help children and their parents to achieve better control of the disease, which is the goal of secondary prevention. Thus, the diversity of environments for the development of health competences helps parents and their children to learn as much as possible about this chronic disease and acquire skills that enable them to properly manage its consequences. However, not all environments for the development of health competences encourage their development. Accordingly, this article aims to reveal the development of the health competences of children with diabetes mellitus in various environments. The research object is the development of the health competences of children with diabetes mellitus in various environments. The aim of the article is to reveal the development of the health competences of children with diabetes mellitus in various environments. Tasks: 1. Highlight the importance of the educational environment for education. 2) Identify environments for the development of children’s health competences. 3) Reveal how and in which environments children with diabetes mellitus develop health competences. Research questions: 1. What environments exist for the development of the health competences of children with diabetes mellitus? 2. What health competence aspects do children with diabetes mellitus develop in various environments? 3. Which educational environments are the most acceptable for children and why? Research methods. Theoretical – the analysis, summarization and systematization of scientific literature methods were used; empirical – the semi-structured interview method was used for data collection; the content analysis method was applied for the analysis of research data. Research context and participants. Semi-structured interviews with children with diabetes mellitus were conducted in the period from 5 February 2019 to 1 September 2021. Children were chosen because their health states depended on their health competences (knowledge, skills and value attitudes). In total, 7 children (4 girls and 3 boys) aged from 12 to 16 with diabetes mellitus agreed to participate in the qualitative research. The children had been diagnosed from 1 to 7 years ago and were selected according to the following criteria: 1) children with diabetes mellitus; 2) children with diabetes mellitus aged from 7 to 18 years. The analysis of the experiences of children with diabetes mellitus who participated in the research allowed six environments for the development of children’s health competences to be distinguished: medical institutions; family environments; summer/health camps; self-directed learning environments; social media; and environments involving other people with similar issues. However, it is not only the diversity of environments for the development of health competence that is important, but also how different environments encourage children with diabetes mellitus to get involved and actively develop their health competences. The analysis of research data on the importance of environments for the development of health competences in children with diabetes mellitus allowed four factors to be distinguished. The research results show that it is important for children that their educational environment: is safe and cosy; provides them with the opportunity to reveal their personalities, be themselves and express their thoughts; enables them to develop through experiences; and is organised in a manner that motivates children and includes interesting activities and creative methods. Conclusions: 1. Children with diabetes mellitus find the diversity and availability of educational environments important, since diabetes is a chronic disease and needs to be extensively controlled to avoid possible complications in the future. It is easier for children with diabetes to get involved in the process of health competence development when interesting and relevant topics are discussed, when there is mutual encouragement and interaction between the participants of the educational process, and when the child can actively engage and learn. 2. Empirical research established that children with diabetes mellitus can acquire health competences in the following environments: medical institutions; family environments; summer/health camps; self-directed learning environments; social media; and environments involving other people with similar issues. In these environments, children receive knowledge regarding type 1 diabetes mellitus, develop skills that help them to control this chronic disease, and form value attitudes and understand that health is the most important thing. 3. The research identified that it is important for children with diabetes mellitus to create various educational environments where they can fully understand their disease.

Enric Benavent-Vallès, Mercè Puig-Pey-Saurí, Roser Díaz-López et al.

La espiritualidad es una dimensión de la persona que está relacionada con la búsqueda de sentido e íntimamente vinculada a las decisiones tomadas a lo largo de la vida. Desde una visión antropológica que tiene en cuenta la dimensión espiritual de la persona, y a partir de un enfoque cualitativo, se realizaron diecisiete entrevistas semidirigidas a personas usuarias de diversos albergues en los que se acompaña a personas sin hogar de la Orden Hospitalaria San Juan de Dios, Aragón. La identidad, el arraigo, la trascendencia, la valoración de la realidad y la toma de decisiones emergen como categorías visibles y significativas que nos acercan a la dimensión espiritual a partir de un lenguaje no religioso basado en experiencias vitales. Los resultados proporcionan una comprensión amplia de dicha dimensión, que hace posible un tipo de intervención que tiene en cuenta las capacidades espirituales de la persona. Se ha generado una guía para la conducción y el análisis de entrevistas biográficas que puede ayudar a los profesionales a ampliar su mirada sobre la espiritualidad humana, así como a captar su potencial y su relación intrínseca con las decisiones que, junto a factores extrínsecos, van definiendo la dirección vital de cada persona.

Jaspreet Ranauta

This paper offers a transnational analytical framework to inform contemporary anti-racist solidarity building in what is now called Canada by engaging with migration, colonialism, and indigeneity. In particular, I trace the historical entanglements of modernity/coloniality from the British Empire’s Canal Colonies project in Punjab to colonial policies in what is now called British Columbia while centring land and Indigenous sovereignty.

Susannah Kate Devitt, Tamara Rose Pearce, Alok Kumar Chowdhury et al.

Against the backdrop of a social media reckoning, this paper seeks to demonstrate the potential of social tools to build virtuous behaviours online. We must assume that human behaviour is flawed, the truth can be elusive, and as communities we must commit to mechanisms to encourage virtuous social digital behaviours. Societies that use social platforms should be inclusive, responsive to evidence, limit punitive actions and allow productive discord and respectful disagreement. Social media success, we argue, is in the hypothesis. Documents are valuable to the degree that they are evidence in service of, or to challenge an idea for a purpose. We outline how a Bayesian social platform can facilitate virtuous behaviours to build evidence-based collective rationality. The chapter outlines the epistemic architecture of the platform's algorithms and user interface in conjunction with explicit community management to ensure psychological safety. The BetterBeliefs platform rewards users who demonstrate epistemically virtuous behaviours and exports evidence-based propositions for decision-making. A Bayesian social network can make virtuous ideas powerful.

Tamika C.B. Zapolski, Richelle L. Clifton

Introduction: Cultural socialization is associated with reduced risk for several health outcomes among racial/ethnic minority youth. However, to date, less is known about its effect on substance use or the mechanisms through which this process may operate. The current study aimed to examine the effect of cultural socialization on alcohol use through alcohol expectancies among racial/ethnic minority youth. Methods: 113 minority adolescents (69.9% African American; 13.3% Hispanic; 10.6% Multiracial; 2.7% American Indian/Alaskan Native) between ages 12 and 18 (mean age 15) were recruited from community-based after school centers. Participants completed measures on cultural socialization, four alcohol expectancy domains (i.e., positive social, wild and crazy, negative arousal, and sedation), and past year alcohol use. Results: A significant indirect pathway between cultural socialization, alcohol expectancies and alcohol use was found for negative arousal expectancies (b = −0.160, Boot CI [95] = −0.413, −0.021). Indirect paths were non-significant for the other three alcohol expectancies. Conclusions: Our findings suggest that cultural socialization can help reduce alcohol use among racial/ethnic minority adolescents, in part though influencing negative arousal expectancies. Given evidence that alcohol expectancies play an important and long-lasting role in alcohol use across development, incorporating cultural socialization into intervention programming for racial/ethnic minority youth may prove beneficial to reduce risk for alcohol use. Keywords: Cultural socialization, Alcohol expectancies, Alcohol use, Racial/ethnic minorities

Uğur Ümit Üngör

Video as a Weapon in Contemporary Conflicts

Aaditeshwar Seth

We recount in this essay the decade-long story of Gram Vaani, a social enterprise with a vision to build appropriate ICTs (Information and Communication Technologies) for participatory media in rural and low-income settings, to bring about social development and community empowerment. Other social enterprises will relate to the learning gained and the strategic pivots that Gram Vaani had to undertake to survive and deliver on its mission, while searching for a robust financial sustainability model. While we believe the ideal model still remains elusive, we conclude this essay with an open question about the reason to differentiate between different kinds of enterprises - commercial or social, for-profit or not-for-profit - and argue that all enterprises should have an ethical underpinning to their work.

Georgios Katsimpras, Georgios Paliouras

This paper proposes a method to guide tensor factorization, using class labels. Furthermore, it shows the advantages of using the proposed method in identifying nodes that play a special role in multi-relational networks, e.g. spammers. Most complex systems involve multiple types of relationships and interactions among entities. Combining information from different relationships may be crucial for various prediction tasks. Instead of creating distinct prediction models for each type of relationship, in this paper we present a tensor factorization approach based on RESCAL, which collectively exploits all existing relations. We extend RESCAL to produce a semi-supervised factorization method that combines a classification error term with the standard factor optimization process. The coupled optimization approach, models the tensorial data assimilating observed information from all the relations, while also taking into account classification performance. Our evaluation on real-world social network data shows that incorporating supervision, when available, leads to models that are more accurate.

Hancheng Cao, Zhilong Chen, Fengli Xu et al.

Past few years have witnessed the emergence and phenomenal success of strong-tie based social commerce. Embedded in social networking sites, these E-Commerce platforms transform ordinary people into sellers, where they advertise and sell products to their friends and family in online social networks. These sites can acquire millions of users within a short time, and are growing fast at an accelerated rate. However, little is known about how these social commerce develop as a blend of social relationship and economic transactions. In this paper we present the first measurement study on the full-scale data of Beidian, one of the fastest growing social commerce sites in China, which involves 11.8 million users. We first analyzed the topological structure of the Beidian platform and highlighted its decentralized nature. We then studied the site's rapid growth and its growth mechanism via invitation cascade. Finally, we investigated purchasing behavior on Beidian, where we focused on user proximity and loyalty, which contributes to the site's high conversion rate. As the consequences of interactions between strong ties and economic logics, emerging social commerce demonstrates significant property deviations from all known social networks and E-Commerce in terms of network structure, dynamics and user behavior. To the best of our knowledge, this work is the first quantitative study on the network characteristics and dynamics of emerging social commerce platforms.

Nan Xi, Di Ma, Marcus Liou et al.

In this paper, we seek to understand how politicians use images to express ideological rhetoric through Facebook images posted by members of the U.S. House and Senate. In the era of social media, politics has become saturated with imagery, a potent and emotionally salient form of political rhetoric which has been used by politicians and political organizations to influence public sentiment and voting behavior for well over a century. To date, however, little is known about how images are used as political rhetoric. Using deep learning techniques to automatically predict Republican or Democratic party affiliation solely from the Facebook photographs of the members of the 114th U.S. Congress, we demonstrate that predicted class probabilities from our model function as an accurate proxy of the political ideology of images along a left-right (liberal-conservative) dimension. After controlling for the gender and race of politicians, our method achieves an accuracy of 59.28% from single photographs and 82.35% when aggregating scores from multiple photographs (up to 150) of the same person. To better understand image content distinguishing liberal from conservative images, we also perform in-depth content analyses of the photographs. Our findings suggest that conservatives tend to use more images supporting status quo political institutions and hierarchy maintenance, featuring individuals from dominant social groups, and displaying greater happiness than liberals.

Salvatore Giorgi, Veronica Lynn, Keshav Gupta et al.

Social media is increasingly used for large-scale population predictions, such as estimating community health statistics. However, social media users are not typically a representative sample of the intended population -- a "selection bias". Within the social sciences, such a bias is typically addressed with restratification techniques, where observations are reweighted according to how under- or over-sampled their socio-demographic groups are. Yet, restratifaction is rarely evaluated for improving prediction. In this two-part study, we first evaluate standard, "out-of-the-box" restratification techniques, finding they provide no improvement and often even degraded prediction accuracies across four tasks of esimating U.S. county population health statistics from Twitter. The core reasons for degraded performance seem to be tied to their reliance on either sparse or shrunken estimates of each population's socio-demographics. In the second part of our study, we develop and evaluate Robust Poststratification, which consists of three methods to address these problems: (1) estimator redistribution to account for shrinking, as well as (2) adaptive binning and (3) informed smoothing to handle sparse socio-demographic estimates. We show that each of these methods leads to significant improvement in prediction accuracies over the standard restratification approaches. Taken together, Robust Poststratification enables state-of-the-art prediction accuracies, yielding a 53.0% increase in variance explained (R^2) in the case of surveyed life satisfaction, and a 17.8% average increase across all tasks.

Markus Enenkel, Sofia Martinez Saenz, Denyse S. Dookie et al.

Social media are more than just a one-way communication channel. Data can be collected, analyzed and contextualized to support disaster risk management. However, disaster management agencies typically use such added-value information to support only their own decisions. A feedback loop between contextualized information and data suppliers would result in various advantages. First, it could facilitate the near real-time communication of early warnings derived from social media, linked to other sources of information. Second, it could support the staff of aid organizations during response operations. Based on the example of Hurricanes Harvey and Irma we show how filtered, geolocated Tweets can be used for rapid damage assessment. We claim that the next generation of big data analyses will have to generate actionable information resulting from the application of advanced analytical techniques. These applications could include the provision of social media-based training data for algorithms designed to forecast actual cyclone impacts or new socio-economic validation metrics for seasonal climate forecasts.