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

Bruna Figueiredo Oliveira

Resumo: O objetivo deste artigo é contribuir para as análises da teoria do partido revolucionário presente nos Cadernos do cárcere do pensador italiano Antonio Gramsci, evidenciando sua importância para a construção da hegemonia dos subalternos. Por meio de um estudo bibliográfico, recuperamos os elementos teóricos e político-organizativos capazes de destacar a atualidade e a centralidade do papel do partido nas lutas de classes e sua responsabilidade na formação de uma vontade coletiva capaz de superar a ordem do capital.

Mark Wood, Samantha Keene, Jessamy Gleeson et al.

This study explores the findings from a survey-based questionnaire investigating the prevalence and predictors of student disclosures of crime, violence, and trauma to criminology educators working at Australian and Aotearoa New Zealand universities. Responses show student disclosures are common, with educators receiving an average of three to four disclosures in the preceding two years. While gender did not predict the number of disclosures received, teaching subjects discussing domestic and family/whānau and/or sexual violence increased the likelihood of disclosures. The study’s findings can help inform the development of university interventions, systems, and resources to improve support for students and staff, enhancing classroom and campus safety.

Zhuochao Peng, Jiaxin Xu, Jun Hu et al.

While recent research highlights the potential of social robots to support mood regulation, little is known about how prospective users view their integration into everyday life. To explore this, we conducted an exploratory case study that used a speculative robot concept "Mora" to provoke reflection and facilitate meaningful discussion about using social robots to manage subtle, day-to-day emotional experiences. We focused on the "Sunday Blues," a common dip in mood that occurs at the end of the weekend, as a relatable context in which to explore individuals' insights. Using a video prototype and a co-constructing stories method, we engaged 15 participants in imagining interactions with Mora and discussing their expectations, doubts, and concerns. The study surfaced a range of nuanced reflections around the attributes of social robots like empathy, intervention effectiveness, and ethical boundaries, which we translated into design considerations for future research and development in human-robot interaction.

Emelia May Hughes, Tim Weninger

This study examines the structural dynamics of Truth Social, a politically aligned social media platform, during two major political events: the U.S. Supreme Court's overturning of Roe v. Wade and the FBI's search of Mar-a-Lago. Using a large-scale dataset of user interactions based on re-truths (platform-native reposts), we analyze how the network evolves in relation to fragmentation, polarization, and user influence. Our findings reveal a segmented and ideologically homogenous structure dominated by a small number of central figures. Political events prompt temporary consolidation around shared narratives, followed by rapid returns to fragmented, echo-chambered clusters. Centrality metrics highlight the disproportionate role of key influencers, particularly @realDonaldTrump, in shaping visibility and directing discourse. These results contribute to research on alternative platforms, political communication, and online network behavior, demonstrating how infrastructure and community dynamics together reinforce ideological boundaries and limit cross-cutting engagement.

Fernando de Oliveira Zonta, Amanda Pilon Barsoumian

O presente artigo tem como objetivo analisar a (in)constitucionalidade do artigo 310, §2° do Código de Processo Penal brasileiro, no tocante específico à reincidência como fundamento, por si só, para decretação ou manutenção da prisão processual. A partir da análise da Constituição Federal, da doutrina e da jurisprudência do Supremo Tribunal Federal, conclui-se pela inconstitucionalidade de referido dispositivo, pois viola, dentre outros princípios constitucionais, a presunção de inocência. Outrossim, a partir da análise da jurisprudência da Corte Interamericana de Direitos Humanos, conclui-se pela inconvencionalidade do referido dispositivo, pois denota um resgate do famigerado Direito Penal do autor.

Kanad Shrikar Pardeshi, Itai Shapira, Ariel D. Procaccia et al.

Is it possible to understand or imitate a policy maker's rationale by looking at past decisions they made? We formalize this question as the problem of learning social welfare functions belonging to the well-studied family of power mean functions. We focus on two learning tasks; in the first, the input is vectors of utilities of an action (decision or policy) for individuals in a group and their associated social welfare as judged by a policy maker, whereas in the second, the input is pairwise comparisons between the welfares associated with a given pair of utility vectors. We show that power mean functions are learnable with polynomial sample complexity in both cases, even if the comparisons are social welfare information is noisy. Finally, we design practical algorithms for these tasks and evaluate their performance.

Federico Echenique, Quitzé Valenzuela-Stookey

Harsanyi (1955) showed that the only way to aggregate individual preferences into a social preference which satisfies certain desirable properties is ``utilitarianism'', whereby the social utility function is a weighted average of individual utilities. This representation forms the basis for welfare analysis in most applied work. We argue, however, that welfare analysis based on Harsanyi's version of utilitarianism may overlook important distributional considerations. We therefore introduce a notion of utilitarianism for discrete-choice settings which applies to \textit{social choice functions}, which describe the actions of society, rather than social welfare functions which describe society's preferences (as in Harsanyi). We characterize a representation of utilitarian social choice, and show that it provides a foundation for a family of \textit{distributional welfare measures} based on quantiles of the distribution of individual welfare effects, rather than averages.

Alice Da Fonseca, Peter Lake, Ariana Barrenechea

This project is a collaboration between industry and academia to delve into Finance Social Networks, specifically the Board of Directors of public companies. Knowing the connections between Directors and Executives in different companies can generate powerful stories and meaningful insights on investments. A proof of concept in the form of a Data Visualization tool reveals its strength in investigating corporate governance and sustainability, as well as in the partnership between industry and academic institutions.

Bincy C. C., Lizy P. J., Jasmine Mathew

During the Covid-19 pandemic, domestic violence (DV) in India rose exponentially. Therefore, the poor urban households in Kerala with the highest vulnerability call for urgent investigations and remedial actions. In this context, this study explored the problems of adolescents living with DV in deprived families, their risk factors, and protective factors. Based on the information gathered and the suggestions of social work experts, it further developed a framework for a school-based psychosocial rehabilitation (PSR), endorsing the role of school social workers. This study was conducted in a government-aided high school in the suburbs of Kochi. It gathered data from adolescent victims (n=12) of DV, their mothers (n=12), teachers (n=7), peers (n=30), and school counselor (n=1), subscribing to a generic qualitative inquiry. A theoretical thematic analysis was adopted for analyzing and drawing conclusions from the data. We recommend the PSR framework developed in the light of social support theory for testing and refining.

Natasha Pistre, Benoît Schreck, Marie Grall-Bronnec et al.

Introduction: Despite similarities between compulsive sexual disorder and substance use disorder, the issue whether problematic sexual behavior should be viewed within an addiction framework continues to be a subject of debate with no consensus regarding its conceptualization and diagnosis criteria. Examining the presence of addiction criteria among clinical and no clinical samples in the existing literature could permit to ascertain clinical validity of sex addiction diagnosis and support its overlapping feature with other addictive disorders. The aim of this systematic review was to examine this issue by assessing DSM-5 criteria of substance use disorder among individuals engaged in problematic sexual activity. Methods: Using PRISMA criteria, three databases were comprehensively searched up to April 2022, in order to identify all candidate studies based on broad key words. Resulting studies were then selected if they examined problematic sexual behavior within the framework of DSM-5 addiction criteria. Results: Twenty articles matched the selection criteria and were included in this review. DSM-5 criteria of addictive disorders were found to be highly prevalent among problematic sex users, particularly craving, loss of control over sex use, and negative consequences related to sexual behavior. Exposition to sexual cues was also shown to trigger craving, with an association to problematic use and symptom severity. Conclusions: More studies should been done to assess homogeneously according to the DSM-5 criteria the addiction-like features of problematic sexual behaviors in clinical and no-clinical populations. Furthermore, this work argues for the need of further research to examine the extent to which anti-craving interventions could be effective in improving clinical outcomes.

Erwan Le Merrer, Gilles Tredan, Ali Yesilkanat

Numerous discussions have advocated the presence of a so called rabbit-hole (RH) phenomenon on social media, interested in advanced personalization to their users. This phenomenon is loosely understood as a collapse of mainstream recommendations, in favor of ultra personalized ones that lock users into narrow and specialized feeds. Yet quantitative studies are often ignoring personalization, are of limited scale, and rely on manual tagging to track this collapse. This precludes a precise understanding of the phenomenon based on reproducible observations, and thus the continuous audits of platforms. In this paper, we first tackle the scale issue by proposing a user-sided bot-centric approach that enables large scale data collection, through autoplay walks on recommendations. We then propose a simple theory that explains the appearance of these RHs. While this theory is a simplifying viewpoint on a complex and planet-wide phenomenon, it carries multiple advantages: it can be analytically modeled, and provides a general yet rigorous definition of RHs. We define them as an interplay between i) user interaction with personalization and ii) the attraction strength of certain video categories, which cause users to quickly step apart of mainstream recommendations made to fresh user profiles. We illustrate these concepts by highlighting some RHs found after collecting more than 16 million personalized recommendations on YouTube. A final validation step compares our automatically-identified RHs against manually-identified RHs from a previous research work. Together, those results pave the way for large scale and automated audits of the RH effect in recommendation systems.

Md. Rafiul Biswas, Hazrat Ali, Raian Ali et al.

Background: Vaccination programs are effective only when a significant percentage of people are vaccinated. However, vaccine acceptance varies among communities around the world. Social media usage is arguably one of the factors affecting public attitudes towards vaccines. Objective: This study aims to identify if the social media usages factors can be used to predict attitudes and behavior towards the COVID-19 vaccines among the people in the Arab world. Methods: An online survey was conducted in the Arab countries and 217 Arab people participated in this study. Logistic regression was applied to identify what demographics and social media usage factors predict public attitudes and behavior towards the COVID-19 vaccines. Results: Of the 217 participants, 56.22% of them were willing to accept the vaccine and 41.47% of them were hesitant. This study shows that none of the social media usages factors were significant enough to predict the actual vaccine acceptance behavior. Whereas the analysis showed few of the social media usage factors can predict public attitudes towards the COVID-19 vaccines. For example, frequent social media users were 2.85 times more likely to agree that the risk of COVID-19 is being exaggerated (OR=2.85, 95% CI=0.86-9.45, p=0.046) than infrequent social media users. Whereas participants having more trust in vaccine information shared by their contacts are less likely to agree that decision-makers have verified that vaccines are safe (OR=0.528, 95% CI= 0.276-1.012, p=0.05). Conclusion: The use of social media and information shared on it may affect public attitudes towards COVID-19 vaccines. Therefore, disseminating correct and validated information about COVID-19 and other vaccines on social media is important for increasing public trust and countering the impact of incorrect and misinformation.

Linda Smith

La tarea de examinar los orígenes y el desarrollo del trabajo social está plagada de narrativas en disputa. En Sudáfrica prevalecen los discursos individualistas, liberales, coloniales, masculinos y “blancos”. Desde una perspectiva histórico-dialéctica, en vez de narrar el “progreso” cronológico de la profesión y disciplina, se enfatiza en cómo las dinámicas sociopolíticas y económicas dan forma al trabajo social, que a su vez tiene un papel en la configuración de dichas dinámicas. Se cuestiona la ficción de registros puramente centrados en las ideas de progreso y libertad de elección, y se develan discursos hegemónicos y contrahegemónicos. Se insta a las/os trabajadores sociales a que se comprometan con toda la complejidad de los acontecimientos que surgen de los antagonismos de clase y raza de la sociedad sudafricana. para cautivar la tradición más crítica del trabajo social en América Latina y estimular estudios e intervenciones sociales construidos a partir de la vida concreta de los pueblos latinoamericanos.

P. A. Gloor, A. Fronzetti Colladon, F. Grippa et al.

The purpose of this study is to examine the impact of board member composition and board members' social media presence on the performance of startups. Using multiple sources, we compile a unique dataset of about 500 US-based technology startups. We find that startups with more venture capitalists on the board and whose board members are active on Twitter attract additional funding over the years, though they do not generate additional sales. By contrast, startups which have no venture capitalists on the board and whose board members are not on Twitter show an increased ability to translate assets into sales. Consistent with other research, our results indicate that startups potentially benefit from working with VCs because of the opportunity to access additional funding, although their presence does not necessarily translate into sales growth and operational efficiency. We use a number of control variables, including board gender representation and board members' position in the interlocking directorates' network.

Kamil Raczycki, Marcin Szymański, Yahor Yeliseyenka et al.

Public transport agencies use social media as an essential tool for communicating mobility incidents to passengers. However, while the short term, day-to-day information about transport phenomena is usually posted in social media with low latency, its availability is short term as the content is rarely made an aggregated form. Social media communication of transport phenomena usually lacks GIS annotations as most social media platforms do not allow attaching non-POI GPS coordinates to posts. As a result, the analysis of transport phenomena information is minimal. We collected three years of social media posts of a polish public transport company with user comments. Through exploration, we infer a six-class transport information typology. We successfully build an information type classifier for social media posts, detect stop names in posts, and relate them to GPS coordinates, obtaining a spatial understanding of long-term aggregated phenomena. We show that our approach enables citizen science and use it to analyze the impact of three years of infrastructure incidents on passenger mobility, and the sentiment and reaction scale towards each of the events. All these results are achieved for Polish, an under-resourced language when it comes to spatial language understanding, especially in social media contexts. To improve the situation, we released two of our annotated data sets: social media posts with incident type labels and matched stop names and social media comments with the annotated sentiment. We also opensource the experimental codebase.

Mike E. U. Ligthart, Mark A. Neerincx, Koen V. Hindriks

We present a discovery-based, first version, explicit model of social interaction that provides a basis for measuring the quality of interaction of a human user with a social robot. The two core elements of the social interaction model are engagement and co-regulation. Engagement emphasizes the \textit{qualitative nature} of social interaction and the fact that a user needs to be drawn into the interaction with the robot. Co-regulation emphasizes the interaction process and the fact that a user and a robot need to be acting together. We argue that the quality of social interaction with a robot can be measured in terms of how efficiently engagement and co-regulation are established and maintained during the interaction and how satisfied the user is with the interaction.

Getasew Legas, Habte Belete, Sintayehu Asnakew et al.

Abstract Background Suicidal behavior has a significant contribution to the global burden of disease that affects individuals, families and communities at different age groups. Sadly, up to 75% of suicides in the world occur in low-and- middle income countries which have no adequate resource to prevent it. The aim of this study was to assess suicidal behavior and associated factors among community residents with problematic substance use in South Gondar zone, northwest Ethiopia. Methods Community based cross-sectional survey was conducted by using a suicidal behavior revised questionnaire from January 15 to March 15, 2019. A total of 4035 participants were screened for problematic substance use by using multi stage cluster sampling and 846 participants were positive for problematic substance use then asked for suicidal behavior. Multiple logistic regression analyses used to see adjusted odd rations (AOR). Multilevel binary logistic regression was used to account for the hierarchical structure of the two-level data within individual and districts level. Results The prevalence of suicidal behavior over the last 12 months in problematic substance uses was found to be 41.4% with 95% of confidence interval (CI) (38.2–44.9). Perceived stigma, [AOR = 1.605, 95% CI (1.16–2.23)], family history of suicide [AOR = 3.22, 95% CI (1.46–7.10)], physical illness [AOR = 2.45 95% CI (1.157–3.84)], rural resident [AOR = 1.74, 95% CI (1.16–2.62)], depression [AOR = 4.44, 95% CI (3.15–6.27)] and living alone (AOR = 1.61, 95% CI (1.16–2.24) were risks factors for suicidal behavior. Conclusion Suicidal behavior in problematic substance uses found to be high. Health workers should pay attention to decrease suicidal behavior and to control amendable factors.

Keenan Jones, Jason R. C. Nurse, Shujun Li

The hacktivist group Anonymous is unusual in its public-facing nature. Unlike other cybercriminal groups, which rely on secrecy and privacy for protection, Anonymous is prevalent on the social media site, Twitter. In this paper we re-examine some key findings reported in previous small-scale qualitative studies of the group using a large-scale computational analysis of Anonymous' presence on Twitter. We specifically refer to reports which reject the group's claims of leaderlessness, and indicate a fracturing of the group after the arrests of prominent members in 2011-2013. In our research, we present the first attempts to use machine learning to identify and analyse the presence of a network of over 20,000 Anonymous accounts spanning from 2008-2019 on the Twitter platform. In turn, this research utilises social network analysis (SNA) and centrality measures to examine the distribution of influence within this large network, identifying the presence of a small number of highly influential accounts. Moreover, we present the first study of tweets from some of the identified key influencer accounts and, through the use of topic modelling, demonstrate a similarity in overarching subjects of discussion between these prominent accounts. These findings provide robust, quantitative evidence to support the claims of smaller-scale, qualitative studies of the Anonymous collective.

Amy Kyle Cook, Nicola Worcman

Abstract Background Public opinion polls have consistently shown Americans prefer treatment over arrest policies for opioid users. As the opioid epidemic remains a major health problem in the United States, it is important to determine the type of treatment policies the public would support. Theoretically, government should take into consideration the opinion of its constituents when deciding how to act. As such, the 2018 Virginia Commonwealth Public Policy Poll determined levels of support for the expansion of community-based treatment in one’s community. Results Overall, the results showed 80% of Virginians (n = 788) supported the expansion of community-based treatment centers in their neighborhood, 69% supported the use of housing in their community, while less than half supported the provision of clean needles to IV drug users so they do not use dirty needles that could spread infection. Multivariate analyses revealed education, sex, and political party affiliation are significant factors in predicting support for the expansion of services. Conclusions Given the lack of progress made by the government in reducing the supply and demand of drugs over the course of the war on drugs, it is time to move away from punitive policies to responsible and pragmatic approaches that include the expansion of community-based treatment.

Melissa Velasquez, Mara Flannery, Ryan Badolato et al.

Abstract Background Few studies have documented patient attitudes and experiences with extended-release naltrexone (XR-NTX) opioid relapse prevention in criminal justice settings. This study assessed barriers and facilitators of jail-to-community reentry among adults with opioid use disorder (OUD) treated with XR-NTX, buprenorphine, methadone, and no medications. Methods This qualitative study conducted individual interviews with a purposeful and convenience sample of adults with OUD who were recently released from NYC jails. XR-NTX, no medication, and methadone participants were concurrently enrolled in a large randomized controlled trial evaluating XR-NTX vs. a no medication Enhanced Treatment As Usual (ETAU) condition, or enrolled in a non-randomized quasi-experimental methadone maintenance cohort. Buprenorphine participants were referred from NYC jails to a public hospital office-based buprenorphine program and not enrolled in the parent trial. Interviews were audio recorded, transcribed, independently coded by two researchers, and analyzed per a grounded theory approach adapted to the Social Cognitive Theory framework. The research team reviewed transcripts and coding to reach consensus on emergent themes. Results N = 33 adults with OUD (28 male, 5 female) completed a single individual interview. Purposeful sampling recruited persons leaving jail on XR-NTX (n = 11), no active medication treatment (n = 9), methadone (n = 9), and buprenorphine (n = 4). Emergent themes were: (1) general satisfaction with XR-NTX’s long-acting antagonist effects and control of cravings; (2) “testing” XR-NTX’s blockade with heroin upon reentry was common; (3) early discontinuation of XR-NTX treatment was most common among persons with high self-efficacy and/or heavy exposure to drug use environments and peers; (4) similar satisfaction regarding effects of methadone and buprenorphine maintenance among retained-in-treatment individuals, alongside general dissatisfaction with daily observed dosing requirements and misinformation and stigmas regarding methadone adverse effects; (5) unstable housing, economic insecurity, and exposure to actively using peers were attributed to early termination of treatment and relapse; (6) individual motivation and willpower as central to long-term opioid abstinence and reentry success. Conclusions In the context of more familiar agonist maintenance treatments, XR-NTX relapse prevention during jail-to-community reentry was viewed as a helpful and unique intervention though with important limitations. Commonly described barriers to treatment retention and heroin abstinence included homelessness, economic insecurity, and drug-using peers. Trial registration ClinicalTrials.gov, NCT01999946 (XOR), Registered 03 December 2013, https://clinicaltrials.gov/ct2/show/NCT01999946.