Hasil untuk "Labor in politics. Political activity of the working class"

Krishna Sharma, Khemraj Bhatt

Text-based measurement in political research often treats classi6ication disagreement as random noise. We examine this assumption using con6idence-weighted human annotations of 5,000 social media messages by U.S. politicians. We 6ind that political communication is generally highly legible, with mean con6idence exceeding 0.99 across message type, partisan bias, and audience classi6ications. However, systematic variation concentrates in the constituency category, which exhibits a 1.79 percentage point penalty in audience classi6ication con6idence. Given the high baseline of agreement, this penalty represents a sharp relative increase in interpretive uncertainty. Within messages, intent remains clear while audience targeting becomes ambiguous. These patterns persist with politician 6ixed effects, suggesting that measurement error in political text is structured by strategic incentives rather than idiosyncratic coder error.

Jacob Blumenfeld, Santiago M. Roggerone

Entrevista a Hans-Peter Gruber

Pietro Bernardelle, Stefano Civelli, Leon Fröhling et al.

Large language models (LLMs) are increasingly deployed in politically sensitive settings, raising concerns about their potential to encode, amplify, or be steered toward specific ideologies. We investigate how adopting synthetic personas influences ideological expression in LLMs across seven models (7B-70B+ parameters) from multiple families, using the Political Compass Test as a standardized probe. Our analysis reveals four consistent patterns: (i) larger models display broader and more polarized implicit ideological coverage; (ii) susceptibility to explicit ideological cues grows with scale; (iii) models respond more strongly to right-authoritarian than to left-libertarian priming; and (iv) thematic content in persona descriptions induces systematic and predictable ideological shifts, which amplify with size. These findings indicate that both scale and persona content shape LLM political behavior. As such systems enter decision-making, educational, and policy contexts, their latent ideological malleability demands attention to safeguard fairness, transparency, and safety.

Nicole Smith-Vaniz, Harper Lyon, Lorraine Steigner et al.

Large Language Models (LLMs) have become increasingly incorporated into everyday life for many internet users, taking on significant roles as advice givers in the domains of medicine, personal relationships, and even legal matters. The importance of these roles raise questions about how and what responses LLMs make in difficult political and moral domains, especially questions about possible biases. To quantify the nature of potential biases in LLMs, various works have applied Moral Foundations Theory (MFT), a framework that categorizes human moral reasoning into five dimensions: Harm, Fairness, Ingroup Loyalty, Authority, and Purity. Previous research has used the MFT to measure differences in human participants along political, national, and cultural lines. While there has been some analysis of the responses of LLM with respect to political stance in role-playing scenarios, no work so far has directly assessed the moral leanings in the LLM responses, nor have they connected LLM outputs with robust human data. In this paper we analyze the distinctions between LLM MFT responses and existing human research directly, investigating whether commonly available LLM responses demonstrate ideological leanings: either through their inherent responses, straightforward representations of political ideologies, or when responding from the perspectives of constructed human personas. We assess whether LLMs inherently generate responses that align more closely with one political ideology over another, and additionally examine how accurately LLMs can represent ideological perspectives through both explicit prompting and demographic-based role-playing. By systematically analyzing LLM behavior across these conditions and experiments, our study provides insight into the extent of political and demographic dependency in AI-generated responses.

Nathan Junzi Chen

Amidst the rapid normalization of generative artificial intelligence (GAI), intelligent systems have come to dominate political discourse across information media. However, internalized political biases stemming from training data skews, human prejudice, and algorithmic flaws continue to plague this novel technology. This study employs a zero-shot classification approach to evaluate algorithmic political partisanship through a methodical combination of ideological alignment, topicality, response sentiment, and objectivity. A total of 1800 model responses across six mainstream large language models (LLMs) were individually input into four distinct fine-tuned classification algorithms, each responsible for computing one of the aforementioned metrics. The results show an amplified liberal-authoritarian alignment across the six LLMs evaluated, with notable instances of reasoning supersessions and canned refusals. The study subsequently highlights the psychological influences underpinning human-computer interactions and how intrinsic biases can permeate public discourse. The resulting distortion of the political landscape can ultimately manifest as conformity or polarization, depending on the region's pre-existing socio-political structures.

Marie-Therese Sekwenz, Rita Gsenger

The rise of digital platforms has transformed political campaigning, introducing complex regulatory challenges. This paper presents a comprehensive taxonomy for analyzing political content in the EU's digital electoral landscape, aligning with the requirements set forth in new regulations, such as the Digital Services Act. Using a legal doctrinal methodology, we construct a detailed codebook that enables systematic content analysis across user-generated and political ad content to assess compliance with regulatory mandates.

AAVV

Número Completo

Hubert Plisiecki, Paweł Lenartowicz, Maria Flakus et al.

This paper investigates the presence of political bias in emotion inference models used for sentiment analysis (SA) in social science research. Machine learning models often reflect biases in their training data, impacting the validity of their outcomes. While previous research has highlighted gender and race biases, our study focuses on political bias - an underexplored yet pervasive issue that can skew the interpretation of text data across a wide array of studies. We conducted a bias audit on a Polish sentiment analysis model developed in our lab. By analyzing valence predictions for names and sentences involving Polish politicians, we uncovered systematic differences influenced by political affiliations. Our findings indicate that annotations by human raters propagate political biases into the model's predictions. To mitigate this, we pruned the training dataset of texts mentioning these politicians and observed a reduction in bias, though not its complete elimination. Given the significant implications of political bias in SA, our study emphasizes caution in employing these models for social science research. We recommend a critical examination of SA results and propose using lexicon-based systems as a more ideologically neutral alternative. This paper underscores the necessity for ongoing scrutiny and methodological adjustments to ensure the reliability and impartiality of the use of machine learning in academic and applied contexts.

Félix William Medeiros Campos, Daniel Teixeira Maldonado

O objetivo deste estudo foi compreender a cultura das práticas corporais realizadas nas comunidades quilombolas, com a intencionalidade de analisar se essas manifestações culturais fazem parte das aulas de Educação Física Escolar em uma perspectiva da educação popular. A produção de conhecimento acerca da temática foi analisada no catálogo de dissertações e teses da CAPES com as palavras-chave “Práticas Corporais Quilombolas” e “Educação Física Escolar”. O levantamento de dados aconteceu entre os meses de dezembro de 2022 e janeiro de 2023, e onze estudos foram separados para a leitura na íntegra. O material empírico foi submetido à análise de conteúdo e evidenciou-se que poucas pesquisas problematizam as práticas corporais quilombolas na Educação Física Escolar. A demanda maior de trabalhos ainda se dá no campo da educação e com objetos pautados no cotidiano vivido pelos povos quilombolas, como a formação da identidade negra e a sua cultura. As práticas corporais realizadas nessas comunidades demonstram a importância de jogos, brincadeiras, danças e expressões corporais, pois são passados de geração em geração e refletem as concepções culturais da formação dos quilombos em territórios brasileiros. Defendemos que é necessário descolonizar o currículo da Educação Física com projetos político-pedagógicos que tematizem as práticas corporais quilombolas.

Ummya Salma, Md. Fazlul Huq Khan

This study explores the relationship between political stability and inflation in four South Asian countries, employing panel data spanning from 2001 to 2021. To analyze this relationship, the study utilizes the dynamic ordinary least square (DOLS) and fully modified ordinary least square (FMOLS) methods, which account for cross-sectional dependence and slope homogeneity in panel data analysis. The findings consistently reveal that increased political stability is associated with lower inflation, while reduced political stability is linked to higher inflation.

Di Zhou, Yinxian Zhang

The rising popularity of ChatGPT and other AI-powered large language models (LLMs) has led to increasing studies highlighting their susceptibility to mistakes and biases. However, most of these studies focus on models trained on English texts. Taking an innovative approach, this study investigates political biases in GPT's multilingual models. We posed the same question about high-profile political issues in the United States and China to GPT in both English and simplified Chinese, and our analysis of the bilingual responses revealed that GPT's bilingual models' political "knowledge" (content) and the political "attitude" (sentiment) are significantly more inconsistent on political issues in China. The simplified Chinese GPT models not only tended to provide pro-China information but also presented the least negative sentiment towards China's problems, whereas the English GPT was significantly more negative towards China. This disparity may stem from Chinese state censorship and US-China geopolitical tensions, which influence the training corpora of GPT bilingual models. Moreover, both Chinese and English models tended to be less critical towards the issues of "their own" represented by the language used, than the issues of "the other." This suggests that GPT multilingual models could potentially develop a "political identity" and an associated sentiment bias based on their training language. We discussed the implications of our findings for information transmission and communication in an increasingly divided world.

Nathállia Resende de Melo Barbosa, Rodrigo Fonseca Lima, Dayani Galato et al.

Este trabalho busca descrever as ações de promoção à saúde da mulher no âmbito da Atenção Primária à Saúde (APS) em uma Unidade Básica de Saúde (UBS) do Distrito Federal. Trata-se de um estudo observacional transversal desenvolvido por meio de entrevista com médicos e enfermeiros da UBS. Os profissionais de saúde participantes da pesquisa tinham experiência média de cinco anos e seis meses na APS. A maioria referiu abordar ações voltadas à saúde da mulher em suas equipes e diagnosticar frequentemente a candidíase vulvovaginal, principalmente pela demanda espontânea. Como causas principais da doença foram citadas a higiene íntima, o tipo de vestimenta das pacientes e o estresse. A educação em saúde foi exemplificada como conduta frente ao diagnóstico e como ação para redução dos casos. O estudo pôde reforçar a importância das atividades trabalhadas com grupos estratégicos na estratégia saúde da família, a partir de reflexões sobre a educação em saúde e a autonomia da mulher à frente da sua qualidade de vida e bem-estar.

Ketlin Braatz, Antonio Jose Muller

Este artigo propõe uma conexão do entendimento de alteridade por Emmanuel Lévinas com o pensamento de Paulo Freire. Parte de uma reflexão decorrente da disciplina Paulo Freire oferecida em um curso de mestrado em educação. O objetivo é problematizar as ideias dos autores Lévinas e Freire na percepção de alteridade como ponto relevante para a educação. Dialogar sobre alteridade a partir dos estudos desenvolvidos em uma interlocução entre os dois pensadores reforça a importância de versar sobre o que é alteridade, como é vista e sentida em sala de aula, com especial ressonância a uma educação humanizadora.

Raimundo Jorge da Cruz Couto, Anselmo Alencar Colares

O presente artigo discute a eficiência da educação de caráter popular em Juruti, município da Amazônia paraense. Dos anos de 1970 a 1992, freiras Franciscanas de Maristella e padres desenvolveram um projeto no município que englobava assistência à saúde, construção de casas populares em regime de mutirão, incentivo à geração de renda através de artesanato, e atendimento às crianças carentes por meio de creches e pré-escolas. Os envolvidos no projeto eram atuantes em um movimento chamado Comunidades Eclesiais de Base (CEB). A dinâmica das CEB consistia em ligar os ensinamentos bíblicos à necessidade de que as pequenas comunidades lutassem contra a opressão dos grandes fazendeiros e empresários. Em Juruti, contribuíram para o fortalecimento dos pequenos agricultores através do Sindicato dos Trabalhadores Rurais e foram importantes fomentadoras de conflitos contra os grandes latifundiários que, com o intuito de utilizar grandes faixas de terras produtivas como moeda de troca no mercado de exploração madeireira e agrícola, prejudicavam a economia por as manterem inutilizadas. O acirramento dos conflitos e as ameaças constantes de violência culminaram com a saída das freiras da sede do município em 1992.

Kai Xing, Shang Li, Xiaoguang Yang

Using an unbalanced panel data covering 75 countries from 1991 to 2019, we explore how the political risk impacts on food reserve ratio. The empirical findings show that an increasing political risk negatively affect food reserve ratio, and same effects hold for both internal risk and external risk. Moreover, we find that the increasing external or internal risks both negatively affect production and exports, but external risk does not significantly impact on imports and it positively impacts on consumption, while internal risk negatively impacts on imports and consumption. The results suggest that most of governments have difficulty to raise subsequent food reserve ratio in face of an increasing political risk, no matter it is an internal risk or an external risk although the mechanisms behind the impacts are different.

Orestis Papakyriakopoulos, Christelle Tessono, Arvind Narayanan et al.

Online platforms play an increasingly important role in shaping democracy by influencing the distribution of political information to the electorate. In recent years, political campaigns have spent heavily on the platforms' algorithmic tools to target voters with online advertising. While the public interest in understanding how platforms perform the task of shaping the political discourse has never been higher, the efforts of the major platforms to make the necessary disclosures to understand their practices falls woefully short. In this study, we collect and analyze a dataset containing over 800,000 ads and 2.5 million videos about the 2020 U.S. presidential election from Facebook, Google, and TikTok. We conduct the first large scale data analysis of public data to critically evaluate how these platforms amplified or moderated the distribution of political advertisements. We conclude with recommendations for how to improve the disclosures so that the public can hold the platforms and political advertisers accountable.

Gerdus Benade, Nam Ho-Nguyen, J. N. Hooker

Geographical considerations such as contiguity and compactness are necessary elements of political districting in practice. Yet an analysis of the problem without such constraints yields mathematical insights that can inform real-world model construction. In particular, it clarifies the sharp contrast between proportionality and competitiveness and how it might be overcome in a properly formulated objective function. It also reveals serious weaknesses of the much-discussed efficiency gap as a criterion for gerrymandering.

Priscila Lopes, Juliana Nogueira Pontes Nobre, Cláudia Mara Niquini

Este trabalho almeja relatar ações de um projeto de extensão desenvolvido em uma escola pública de educação infantil no município de Diamantina, Minas Gerais. Tendo em vista a importância do brincar no espaço formal de educação, o presente trabalho enquadra-se como um relato de experiência sobre a construção de um parque de pneus em espaços subutilizados de uma escola específica, resultado de um projeto de extensão universitária. Entendemos que ações extensionistas são de suma importância para a sociedade, em especial, para a escola básica. A partir de pneus, madeiras, cordas, entre outros materiais, o parquinho da/na escola emergiu, sendo utilizado no tempo disponível para atividades livres das crianças e em práticas pedagógicas intencionalmente organizadas, como, por exemplo, em práticas pedagógicas vinculadas à manifestação corporal da ginástica. Ainda registramos que o projeto favoreceu ações coletivas e de pertencimento dos membros da comunidade escolar, no qual, a partir do envolvimento e participação dos pais, gestores e crianças, o ambiente escolar tornou-se mais agradável e lúdico, propiciando proposições que estimulam e favorecem o movimento dos escolares.

Mariana Vasconcelos Paranaiba, Gabriela Ferreira de Camargos Rosa, Mariana Hasse et al.

De acordo com as Diretrizes Curriculares Nacionais para o curso de Medicina, compete aos estudantes de medicina conhecer, vivenciar e efetivar as políticas públicas de saúde. Diante disso, nós, três estudantes de medicina da Universidade Federal de Uberlândia (UFU) e 2 coordenadoras, docentes do curso, elaboramos um projeto de extensão, com início em março de 2018 e término em janeiro de 2019. O objetivo foi abordar o conceito de redução de danos, através da educação popular em saúde, em uma escola pública da cidade. Iniciamos o projeto com a pactuação das atividades com a escola escolhida. Optamos por uma escola situada na área central da cidade que oferecia ensino médio noturno, na modalidade regular e também do programa de Educação para Jovens e Adultos. Dentre os diversos temas sugeridos o tópico sexualidade apareceu na maioria dos votos. Foi desenvolvida uma oficina sobre sexualidade em quatro etapas: aquecimento, atividade 1, atividade 2 e feedback. Participaram da oficina 52 estudantes de três turmas diferentes, uma de cada ano do Ensino Médio. Conseguimos, com dificuldade, envolver a maior parte dos participantes, permitindo a participação e exposição de ideias diversas, surgimento de polêmicas e informações enriquecedoras a todo o grupo.

Ying Sheng, Yoni Zohar, Christophe Ringeissen et al.

Algebraic datatypes, and among them lists and trees, have attracted a lot of interest in automated reasoning and Satisfiability Modulo Theories (SMT). Since its latest stable version, the SMT-LIB standard defines a theory of algebraic datatypes, which is currently supported by several mainstream SMT solvers. In this paper, we study this particular theory of datatypes and prove that it is strongly polite, showing also how it can be combined with other arbitrary disjoint theories using polite combination. Our results cover both inductive and finite datatypes, as well as their union. The combination method uses a new, simple, and natural notion of additivity, that enables deducing strong politeness from (weak) politeness.