Substituir “culpabilidade” por “culpa” é uma necessidade científica no Direito Penal, para sincronizar com teorias da Psicologia, da Psicanálise e da Psiquiatria — que falam da natureza metafísica do conceito, um dado ontológico indemonstrável, insuscetível de ciência. Teorias psicológicas falam do sentimento de culpa ligado à prática de crimes, em que a consciência do fato existe como consciência de culpa — a dimensão consciente do sentimento de culpa —, que pode determinar a confissão do fato e outros efeitos Mas a teoria psicanalítica tem outra explicação: o sentimento de culpa resulta da ação do superego (originário da experiência de Édipo) sobre o ego, a organização coerente dos processos psíquicos para adequar o princípio do prazer ao princípio da realidade, entre outras tarefas. A tese psicanalítica sobre a relação “impulso de punição”/“necessidade de punição” descobriu o criminoso por sentimento de culpa, em que não é o crime que produz o sentimento de culpa, mas o sentimento de culpa que produz o crime. Enfim, a tese comum das ciências psíquicas e sociais é a absoluta incompatibilidade entre culpa e pena, cuja função política é garantir a desigualdade social das sociedades capitalistas.
Criminal law and procedure, Social pathology. Social and public welfare. Criminology
Many outputs of cities scale in universal ways, including infrastructure, crime, and economic activity. Through a mathematical model, this study investigates the interplay between such scaling laws in human organization and governmental allocations of resources, focusing on impacts to migration patterns and social welfare. We find that if superlinear scaling resources of cities -- such as economic and social activity -- are the primary drivers of city dwellers' utility, then cities tend to converge to similar sizes and social welfare through migration. In contrast, if sublinear scaling resources, such as infrastructure, primarily impact utility, then migration tends to lead to megacities and inequity between large and small cities. These findings have implications for policymakers, economists, and political scientists addressing the challenges of equitable and efficient resource allocation.
Decentralized social media platforms like Bluesky Social (Bluesky) have made it possible to publicly disclose some user behaviors with millisecond-level precision. Embracing Bluesky's principles of open-source and open-data, we present the first collection of the temporal dynamics of user-driven social interactions. BlueTempNet integrates multiple types of networks into a single multi-network, including user-to-user interactions (following and blocking users) and user-to-community interactions (creating and joining communities). Communities are user-formed groups in custom Feeds, where users subscribe to posts aligned with their interests. Following Bluesky's public data policy, we collect existing Bluesky Feeds, including the users who liked and generated these Feeds, and provide tools to gather users' social interactions within a date range. This data-collection strategy captures past user behaviors and supports the future data collection of user behavior.
Social media platforms are popular tools for disseminating targeted information during major public events like elections or pandemics. Systematic analysis of the message traffic can provide valuable insights into prevailing opinions and social dynamics among different segments of the population. We are specifically interested in influence spread, and in particular whether more deliberate influence operations can be detected. However, filtering out the essential messages with telltale influence indicators from the extensive and often chaotic social media traffic is a major challenge. In this paper we present a novel approach to extract influence indicators from messages circulating among groups of users discussing particular topics. We build upon the concept of a convo to identify influential authors who are actively promoting some particular agenda around that topic within the group. We focus on two influence indicators: the (control of) agenda and the use of emotional language.
Despite decades of practice and development, social work education in India is still Western-centric. Social work in India is still not well recognised: it does not have an accrediting body or professional recognition within the country. This study gives voice to a sample of social work students regarding some of the challenges they face, including the curriculum, pedagogy, recognition of the profession and the practicum. The study is based on interviews with students from five universities in India and includes concrete recommendations for improving the professional training of social work students.
Social pathology. Social and public welfare. Criminology
As AI systems become increasingly prevalent in various aspects of daily life, gaining a comprehensive understanding of public perception towards these AI systems has become increasingly essential for several reasons such as ethical considerations, user experience, fear, disinformation, regulation, collaboration, and co-creation. In this study, we investigate how mass social media users perceive the recent rise of AI frameworks such as ChatGPT. We collect a total of 33,912 comments in 388 unique subreddits spanning from November 30, 2022 to June 8, 2023 using a list of AI-related keywords. We employ BERTopic to uncover the major themes regarding AI on Reddit. Additionally, we seek to gain deeper insights into public opinion by examining the distribution of topics across different subreddits. We observe that technology-related subreddits predominantly focus on the technical aspects of AI models. On the other hand, non-tech subreddits show greater interest in social issues such as concerns about job replacement or furlough. We leverage zero-shot prompting to analyze the sentiment and perception of AI among individual users. Through a comprehensive sentiment and emotion analysis, we discover that tech-centric communities exhibit greater polarization compared to non-tech communities when discussing AI topics. This research contributes to our broader understanding of public opinion surrounding artificial intelligence.
Data trading has been hindered by privacy concerns associated with user-owned data and the infinite reproducibility of data, making it challenging for data owners to retain exclusive rights over their data once it has been disclosed. Traditional data pricing models relied on uniform pricing or subscription-based models. However, with the development of Privacy-Preserving Computing techniques, the market can now protect the privacy and complete transactions using progressively disclosed information, which creates a technical foundation for generating greater social welfare through data usage. In this study, we propose a novel approach to modeling multi-round data trading with progressively disclosed information using a matchmaking-based Markov Decision Process (MDP) and introduce a Social Welfare-optimized Data Pricing Mechanism (SWDPM) to find optimal pricing strategies. To the best of our knowledge, this is the first study to model multi-round data trading with progressively disclosed information. Numerical experiments demonstrate that the SWDPM can increase social welfare 3 times by up to 54\% in trading feasibility, 43\% in trading efficiency, and 25\% in trading fairness by encouraging better matching of demand and price negotiation among traders.
Substantial evidence on the damaging psychiatric and health-related effects of prolonged solitary confinement has been well-documented in decades of research and civil rights litigation. The emerging ethical dilemma for forensic social work concerns the dual loyalty when social workers are tasked with providing services to clients in restrictive housing. Using Frederic Reamer’s ethical decision-making framework, in concert with the NASW Code of Ethics and the NOFSW Specialty Guidelines on Values and Ethics, the ethical dilemma of dual loyalty in this practice context is explored. Forensic social workers experiencing this unique ethical dilemma are encouraged to consider rational and mindful decision making guided by social work ethical codes and principles of social justice.
Social pathology. Social and public welfare. Criminology
Mariela Contreras, Gracia M. Pineda , Ana Romero
et al.
Introducción: El rol de la mujer en el área científica ha crecido con el paso de los años, pero aún persiste una gran brecha de género en ciencia. Para conocer y manejar esa brecha, es necesario hacer un mapeo de la situación de las mujeres investigadoras en Honduras. Objetivo: Describir la participación y contribuciones de las investigadoras hondureñas en la producción científica nacional según su perfil en Google Académico. Metodología: Se usó Power BI para analizar las variables sexo, institución, índice H, número de citaciones, número de publicaciones, año de la primera publicación, y áreas de investigación registradas en su perfil, utilizando la versión 2 del Ranking de Investigadores Hondureños según su Perfil de Google Académico disponible en https://bit.ly/38s6YuT, el cual es un registro depurado. Resultados: El 35% de todos los perfiles eran de mujeres, 41% vinculadas a las ciencias médicas y de la salud y en su mayoría (92%), afiliadas a universidades. Pese al creciente número de mujeres investigadoras registradas en Google Académico, el crecimiento no es simétrico respecto a los hombres. Solamente el 3.1% de las investigadoras tenía un índice H que supera los dos dígitos. Conclusión: A pesar de los avances, se mantiene la inequidad de género entre investigadores hondureños según la data de Google Académico. Se requiere de políticas públicas e institucionales, para corregir esa brecha.
The idea that social media platforms like Twitter are inhabited by vast numbers of social bots has become widely accepted in recent years. Social bots are assumed to be automated social media accounts operated by malicious actors with the goal of manipulating public opinion. They are credited with the ability to produce content autonomously and to interact with human users. Social bot activity has been reported in many different political contexts, including the U.S. presidential elections, discussions about migration, climate change, and COVID-19. However, the relevant publications either use crude and questionable heuristics to discriminate between supposed social bots and humans or -- in the vast majority of the cases -- fully rely on the output of automatic bot detection tools, most commonly Botometer. In this paper, we point out a fundamental theoretical flaw in the widely-used study design for estimating the prevalence of social bots. Furthermore, we empirically investigate the validity of peer-reviewed Botometer-based studies by closely and systematically inspecting hundreds of accounts that had been counted as social bots. We were unable to find a single social bot. Instead, we found mostly accounts undoubtedly operated by human users, the vast majority of them using Twitter in an inconspicuous and unremarkable fashion without the slightest traces of automation. We conclude that studies claiming to investigate the prevalence, properties, or influence of social bots based on Botometer have, in reality, just investigated false positives and artifacts of this approach.
A number of rules for resolving majority cycles in elections have been proposed in the literature. Recently, Holliday and Pacuit (Journal of Theoretical Politics 33 (2021) 475-524) axiomatically characterized the class of rules refined by one such cycle-resolving rule, dubbed Split Cycle: in each majority cycle, discard the majority preferences with the smallest majority margin. They showed that any rule satisfying five standard axioms plus a weakening of Arrow's Independence of Irrelevant Alternatives (IIA), called Coherent IIA, is refined by Split Cycle. In this paper, we go further and show that Split Cycle is the only rule satisfying the axioms of Holliday and Pacuit together with two additional axioms, which characterize the class of rules that refine Split Cycle: Coherent Defeat and Positive Involvement in Defeat. Coherent Defeat states that any majority preference not occurring in a cycle is retained, while Positive Involvement in Defeat is closely related to the well-known axiom of Positive Involvement (as in J. Perez, Social Choice and Welfare 18 (2001) 601-616). We characterize Split Cycle not only as a collective choice rule but also as a social choice correspondence, over both profiles of linear ballots and profiles of ballots allowing ties.
We study the problem of efficiently and fairly allocating a set of indivisible goods among agents with identical and additive valuations for the goods. The objective is to maximize the Nash social welfare, which is the geometric mean of the agents' valuations. While maximizing the Nash social welfare is NP-hard, a PTAS for this problem is presented by Nguyen and Rothe. The main contribution of this paper is to design a first additive PTAS for this problem, that is, we give a polynomial-time algorithm that maximizes the Nash social welfare within an additive error $\varepsilon v_{\rm max}$, where $\varepsilon$ is an arbitrary positive number and $v_{\rm max}$ is the maximum utility of a good. The approximation performance of our algorithm is better than that of a PTAS. The idea of our algorithm is simple; we apply a preprocessing and then utilize an additive PTAS for the target load balancing problem given recently by Buchem et al. However, a nontrivial amount of work is required to evaluate the additive error of the output.
We present some conditions for social preference transitivity under the majority rule when the individual preferences include cycles. First, our concern is with the restriction on the preference orderings of individuals except those (called cycle members) whose preferences constitute the cycles, but the considered transitivity is, of course, of the society as a whole. In our discussion, the individual preferences are assumed concerned and the cycle members' preferences are assumed as strict orderings. Particularly, for an alternative triple when one cycle is involved and the society is sufficient large (at least 5 individuals in the society), we present a sufficient condition for social transitivity; when two antagonistic cycles are involved and the society has at least 9 individuals, necessary and sufficient conditions are presented which are merely restricted on the preferences of those individuals except the cycle members. Based on the work due to Slutsky (1977) and Gaertner \& Heinecke (1978), we then outline a conceptual $\hat{O}\mbox{-}\hat{I}$ framework of social transitivity in an axiomatic manner. Connections between some already identified conditions and the $\hat{O}\mbox{-}\hat{I}$ framework is examined.
Resumo: Este artigo apresenta alguns dos percursos e dos “achados” investigativos de uma pesquisa* sobre as relações e as condições de trabalho de assistentes sociais no mercado de trabalho. Destaca as tendências em curso para o processamento da ação profissional através da tese da proletarização, que indica a precarização, a informalidade, a intensificação e a terceirização do trabalho - objetivada em níveis salariais baixíssimos, contratos temporários, subcontratações, espaços insalubres, sobrecargas, adoecimentos e humilhações.
Social pathology. Social and public welfare. Criminology
Cristiano Aguiar de Oliveira, Daniele Mendes Silva
As altas taxas de criminalidade que o Brasil apresenta gera inúmeros impactos para a sociedade. Entre esses impactos estão o medo de ser vítima do crime e as mudanças de comportamento dos indivíduos. Neste sentido, este estudo tem o objetivo de avaliar como o medo do crime afeta o consumo de atividades de lazer dos indivíduos, tais como ir a cinemas, shoppings, parques, eventos esportivos, feiras, bares, restaurantes e shows. Para este fim, este estudo utiliza os dados da Pesquisa Nacional de Vitimização do ano de 2012 para estimar um Probit bivariado recursivo, um modelo capaz de lidar com potenciais problemas de endogeneidade. Os resultados indicam que o medo reduz a probabilidade do consumo de lazer na maioria das atividades investigadas, com destaque para eventos esportivos, contudo, foi observado um aumento no consumo de atividades que oferecem mais segurança para os clientes, tais como feiras e shopping centers. O estudo conclui que a criminalidade traz perdas de bem-estar que vão além das perdas econômicas costumeiramente contabilizadas em estudos de custos do crime, pois, não se pode ignorar que o medo do crime é capaz de reduzir a liberdade dos indivíduos e, consequentemente, de trazer perdas até então não observadas para as atividades econômicas.
Social pathology. Social and public welfare. Criminology
We consider linear-quadratic Gaussian (LQG) games in which players have quadratic payoffs that depend on the players' actions and an unknown payoff-relevant state, and signals on the state that follow a Gaussian distribution conditional on the state realization. An information designer decides the fidelity of information revealed to the players in order to maximize the social welfare of the players or reduce the disagreement among players' actions. Leveraging the semi-definiteness of the information design problem, we derive analytical solutions for these objectives under specific LQG games. We show that full information disclosure maximizes social welfare when there is a common payoff-relevant state, when there is strategic substitutability in the actions of players, or when the signals are public. Numerical results show that as strategic substitution increases, the value of the information disclosure increases. When the objective is to induce conformity among players' actions, hiding information is optimal. Lastly, we consider the information design objective that is a weighted combination of social welfare and cohesiveness of players' actions. We obtain an interval for the weights where full information disclosure is optimal under public signals for games with strategic substitutability. Numerical solutions show that the actual interval where full information disclosure is optimal gets close to the analytical interval obtained as substitution increases.
We investigated gender bias in letters of recommendation as a possible cause of the under-representation of women in Experimental Particle Physics (EPP), where about 15% of faculty are female -- well below the 60% level in psychology and sociology. We analyzed 2,206 letters in EPP and these social sciences using standard lexical measures as well as two new measures: author status and an open-ended search for gendered language. In contrast to former studies, women were not depicted as more communal, less agentic, or less standout. Lexical measures revealed few gender differences in either discipline. The open-ended analysis revealed disparities favoring women in social science and men in EPP. However, female EPP candidates were characterized as "brilliant" in nearly three times as many letters as men.