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

Jieying Chen, Karen de Jong, Andreas Poole et al.

As large language models (LLMs) become deeply embedded in digital platforms and decision-making systems, concerns about their political biases have grown. While substantial work has examined social biases such as gender and race, systematic studies of political bias remain limited, despite their direct societal impact. This paper introduces a general methodology for constructing political bias benchmarks by aligning model-generated voting predictions with verified parliamentary voting records. We instantiate this methodology in three national case studies: PoliBiasNL (2,701 Dutch parliamentary motions and votes from 15 political parties), PoliBiasNO (10,584 motions and votes from 9 Norwegian parties), and PoliBiasES (2,480 motions and votes from 10 Spanish parties). Across these benchmarks, we assess ideological tendencies and political entity bias in LLM behavior. As part of our evaluation framework, we also propose a method to visualize the ideology of LLMs and political parties in a shared two-dimensional CHES (Chapel Hill Expert Survey) space by linking their voting-based positions to the CHES dimensions, enabling direct and interpretable comparisons between models and real-world political actors. Our experiments reveal fine-grained ideological distinctions: state-of-the-art LLMs consistently display left-leaning or centrist tendencies, alongside clear negative biases toward right-conservative parties. These findings highlight the value of transparent, cross-national evaluation grounded in real parliamentary behavior for understanding and auditing political bias in modern LLMs.

Yuan Zhang, Laia Castro, Frank Esser et al.

Online political divisions, such as fragmentation or polarization, are a growing global concern that can foster radicalization and hinder democratic cooperation; however, not all divisions are detrimental, some reflect pluralism and healthy diversity of opinion in a democracy. While prior research has predominantly focused on polarization in the United States, there remains a limited body of research on political divides in multiparty systems, and no universal method for comparing fragmentation across countries. Moreover, cross-country comparison is rare. This study first develops a novel measure of structural political fragmentation built on multi-scale community detection and the effective branching factor. Using a dataset of 18,325 political influencers from Brazil, Spain, and the United States, we assess online fragmentation in their Twitter/X co-following networks. We compare the fragmentation of the three countries, as well as the ideological groups within each. We further investigate factors associated with the level of fragmentation in each country. We find that political fragmentation differs across countries and is asymmetric between ideological groups. Brazil is the most fragmented, with higher fragmentation among the left-wing group, while Spain and the United States exhibit similar overall levels, with the left more fragmented in Spain and the right more fragmented in the United States. Additionally, we find that social identity plays a central role in political fragmentation. A strong alignment between ideological and social identities, with minimal overlap between ideologies, tends to promote greater integration and reduce fragmentation. Our findings provide explanations for cross-national and ideological differences in political fragmentation.

Salim Chouaki, Savaiz Nazir, Sandra Siby

YouTube has today become the primary news source for many users, which raises concerns about the role its recommendation algorithm can play in the spread of misinformation and political polarization. Prior work in this area has mainly analyzed how recommendations evolve based on users' watch history within the platform. Nevertheless, recommendations can also depend on off-platform browsing activity that Google collects via trackers on news websites, a factor that has not been considered so far. To fill this gap, we propose a sock-puppet-based experimental framework that automatically interacts with news media articles and then collects YouTube recommendations to measure how cross-site tracking affects the political and misinformation content users see. Moreover, by running our audits in both tracking-permissive and tracking-restrictive browser environments, we assess whether common privacy-focused browsers can protect users from tracking-driven political and misinformation bubbles on YouTube.

Nouar Aldahoul, Hazem Ibrahim, Matteo Varvello et al.

Large Language Models (LLMs) are a transformational technology, fundamentally changing how people obtain information and interact with the world. As people become increasingly reliant on them for an enormous variety of tasks, a body of academic research has developed to examine these models for inherent biases, especially political biases, often finding them small. We challenge this prevailing wisdom. First, by comparing 31 LLMs to legislators, judges, and a nationally representative sample of U.S. voters, we show that LLMs' apparently small overall partisan preference is the net result of offsetting extreme views on specific topics, much like moderate voters. Second, in a randomized experiment, we show that LLMs can promulgate their preferences into political persuasiveness even in information-seeking contexts: voters randomized to discuss political issues with an LLM chatbot are as much as 5 percentage points more likely to express the same preferences as that chatbot. Contrary to expectations, these persuasive effects are not moderated by familiarity with LLMs, news consumption, or interest in politics. LLMs, especially those controlled by private companies or governments, may become a powerful and targeted vector for political influence.

Aishwarya Bandaru, Fabian Bindley, Trevor Bluth et al.

Large language models (LLMs) are increasingly used to simulate social behaviour, yet their political biases and interaction dynamics in debates remain underexplored. We investigate how LLM type and agent gender attributes influence political bias using a structured multi-agent debate framework, by engaging Neutral, Republican, and Democrat American LLM agents in debates on politically sensitive topics. We systematically vary the underlying LLMs, agent genders, and debate formats to examine how model provenance and agent personas influence political bias and attitudes throughout debates. We find that Neutral agents consistently align with Democrats, while Republicans shift closer to the Neutral; gender influences agent attitudes, with agents adapting their opinions when aware of other agents' genders; and contrary to prior research, agents with shared political affiliations can form echo chambers, exhibiting the expected intensification of attitudes as debates progress.

Afrozah Nadeem, Mark Dras, Usman Naseem

Large Language Models (LLMs) increasingly shape public discourse, yet most evaluations of political and economic bias have focused on high-resource, Western languages and contexts. This leaves critical blind spots in low-resource, multilingual regions such as Pakistan, where linguistic identity is closely tied to political, religious, and regional ideologies. We present a systematic evaluation of political bias in 13 state-of-the-art LLMs across five Pakistani languages: Urdu, Punjabi, Sindhi, Pashto, and Balochi. Our framework integrates a culturally adapted Political Compass Test (PCT) with multi-level framing analysis, capturing both ideological stance (economic/social axes) and stylistic framing (content, tone, emphasis). Prompts are aligned with 11 socio-political themes specific to the Pakistani context. Results show that while LLMs predominantly reflect liberal-left orientations consistent with Western training data, they exhibit more authoritarian framing in regional languages, highlighting language-conditioned ideological modulation. We also identify consistent model-specific bias patterns across languages. These findings show the need for culturally grounded, multilingual bias auditing frameworks in global NLP.

Agustina Miguel

El objetivo de este artículo es analizar la conflictividad laboral en Aerolíneas Argentinas (AR) durante la gestión estatal del kirchnerismo (2009-2015) a partir de una experiencia organizativa surgida desde las bases gremiales del sector. En esa dirección, se propone caracterizar las formas de trabajo y organización del colectivo aeronáutico en AR; indagar en el proceso de conformación de la Agrupación Independiente de Trabajadores Aeronáuticos (AITA); y por último, analizar el accionar sindical de la agrupación en la conflictividad laboral en la empresa, focalizando en las reivindicaciones y modalidades de acción desplegadas.

Jusciane da Costa e Silva, Subênia Karine de Medeiros, Késia Kelly Vieira de Castro

O papel da divulgação científica para que a população tenha conhecimento sobre o quanto a Ciência está presente no cotidiano é importante e necessário para a formação de uma sociedade mais consciente. Uma alternativa de construção desses espaços é a realização de ações que divulguem a Ciência, dispostas nos mais diversos lugares, além dos muros das Universidades e das instituições formais de ensino. Locais como parques, praças e teatros, ocupados com uma programação diversificada, que tragam diálogos sobre Ciência. O projeto Ciência no Parque, idealizado e executado por docentes e discentes da Universidade Federal Rural do Semi-Árido (UFERSA), tem como objetivo popularizar o conhecimento sobre Ciência, por meio de metodologias mais interativas, realizando eventos científicos em espaços públicos da cidade de Mossoró/RN. Com potencial reconhecido pela comunidade acadêmica e pela sociedade, novos desafios foram surgindo e houve a necessidade de formação específica de equipes que pudessem atender demandas que fortalecessem a divulgação científica na região, assim, surgiram os grupos de ciência básica, o Brincando Quimicamente e o Física Divertida. Ao participar de vários eventos, os grupos realizaram exposições de experimentos interativos e de baixo custo, relacionados à química, física e robótica, unindo conhecimento, ludicidade e diversão.

Ben Stobaugh, Dhiraj Murthy

We explore the understudied area of social payments to evaluate whether or not we can predict the gender and political affiliation of Venmo users based on the content of their Venmo transactions. Latent attribute detection has been successfully applied in the domain of studying social media. However, there remains a dearth of previous work using data other than Twitter. There is also a continued need for studies which explore mobile payments spaces like Venmo, which remain understudied due to the lack of data access. We hypothesize that using methods similar to latent attribute analysis with Twitter data, machine learning algorithms will be able to predict gender and political affiliation of Venmo users with a moderate degree of accuracy. We collected crowdsourced training data that correlates participants' political views with their public Venmo transaction history through the paid Prolific service. Additionally, we collected 21 million public Venmo transactions from recently active users to use for gender classification. We then ran the collected data through a TF-IDF vectorizer and used that to train a support vector machine (SVM). After hyperparameter training and additional feature engineering, we were able to predict user's gender with a high level of accuracy (.91) and had modest success predicting user's political orientation (.63).

Jean Luiz Neves Abreu

The objective of this work is to present an experience report on the educational actions developed at the Center for Documentation and Research in History (CDHIS) and to expose its relevance in the extension processes of the Federal University of Uberlândia and also in the training of History licentiate degree students. The text was divided in two parts: on the first part we seek to contemplate some aspects of the concept of cultural mediation. The second part deals with the educational actions developed at CDHIS.

Camila Eller Gomes

Levando em consideração o papel que a política pública de extensão universitária representa para produção de mudanças socioculturais relevantes à vida humana civilizada e para construção de uma sociedade mais equitativa, é que se propõe o presente estudo. Um estudo que consiste na avaliação da política de gestão empregada pela Universidade Federal Rural do Rio de Janeiro às ações de extensão universitária por ela implementadas. Para tal, foi utilizada a metodologia de estudo de caso, numa abordagem qualitativa, que a partir da análise de um conjunto de indicadores teve como objetivo compreender se a política de extensão universitária avaliada apresenta procedimentos de gestão sistematizados capazes de institucionalizar e estimular sua plena implementação, de forma a contribuir para o fortalecimento da instituição e para melhoria da qualidade na formação de futuros profissionais. Ao final do estudo chega-se a um diagnóstico da situação observada que permitiu, a partir da identificação de pontos fortes e fracos, oportunidades e ameaças institucionais, elencar um conjunto de recomendações com vistas a reforçar as potencialidades e minimizar as fragilidades observadas.

Ming-Hung Wang, Wei-Yang Chang, Kuan-Hung Kuo et al.

With the increasing popularity of social network services, paradigm-shifting has occurred in political communication. Politicians, candidates, and political organizations establish their fan pages to interact with online citizens. Initially, they publish text-only content on sites; then, they create multimedia content such as photos, images, and videos to approach more people. This paper takes a first look at image-based political propaganda during a national referendum in Taiwan. Unlike elections, a referendum is a vote on policies. We investigated more than 2,000 images posted on Facebook by the two major parties to understand the elements of images and the strategies of political organizations. In addition, we studied the data collection's textual content, objects, and colors. The results suggest the aspects of propaganda materials vary with different political organizations. However, the coloring strategies are similar, using representative colors for consolidation and the opponent's colors for attacks.

Joanna Baran, Michał Kajstura, Maciej Ziółkowski et al.

Every day, the world is flooded by millions of messages and statements posted on Twitter or Facebook. Social media platforms try to protect users' personal data, but there still is a real risk of misuse, including elections manipulation. Did you know, that only 13 posts addressing important or controversial topics for society are enough to predict one's political affiliation with a 0.85 F1-score? To examine this phenomenon, we created a novel universal method of semi-automated political leaning discovery. It relies on a heuristical data annotation procedure, which was evaluated to achieve 0.95 agreement with human annotators (counted as an accuracy metric). We also present POLiTweets - the first publicly open Polish dataset for political affiliation discovery in a multi-party setup, consisting of over 147k tweets from almost 10k Polish-writing users annotated heuristically and almost 40k tweets from 166 users annotated manually as a test set. We used our data to study the aspects of domain shift in the context of topics and the type of content writers - ordinary citizens vs. professional politicians.

Hellen Vivian Moreira dos Anjos, Giuliana de Sá Ferreira Barros, Fernando Barreto Rodrigues

Este artigo traz a experiência da prática libertadora freiriana na concepção do projeto do curso técnico em Vigilância em Saúde integrado ao Ensino Médio, no Instituto Federal de Educação, Ciência e Tecnologia do Norte de Minas Gerais, Câmpus Avançado Janaúba. O objetivo é relatar como a prática pedagógica em Paulo Freire é também práxis educativa, uma vez que, mediada pela história, busca a unidade entre o ser humano e o mundo do qual ele faz parte. Resgatar a ideia da prática pedagógica freiriana relacionada ao conceito de práxis e, em consequência, à Educação Profissional integrada ao Ensino Médio, faz-se imperioso, especialmente nesse contexto em que a negação da condição humana, ou da humanidade, está cada vez mais evidente. A discussão do conceito de práxis foi ancorada em Marx (2002), Losurdo (2015), Vásquez (2011), Manacorda (1996), Semeraro (2005) e, principalmente, Gramsci (1975) e Freire (1987). Em um segundo momento, foi apresentada a experiência pedagógica libertadora freiriana no curso técnico em Vigilância em Saúde no Instituto. Por fim, discorreu-se sobre os princípios metodológicos e organizacionais do curso, dando ênfase à sua estrutura curricular baseada na metodologia dos Temas Geradores.

Martin Saveski, Doug Beeferman, David McClure et al.

We study how political polarization is reflected in the social media posts used by media outlets to promote their content online. In particular, we track the Twitter posts of several media outlets over the course of more than three years (566K tweets), and the engagement with these tweets from other users (104M retweets), modeling the relationship between the tweet text and the political diversity of the audience. We build a tool that integrates our model and helps journalists craft tweets that are engaging to a politically diverse audience, guided by the model predictions. To test the real-world impact of the tool, we partner with the PBS documentary series Frontline and run a series of advertising experiments on Twitter. We find that in seven out of the ten experiments, the tweets selected by our model were indeed engaging to a more politically diverse audience, illustrating the effectiveness of our approach.

Bo Cowgill, Andrea Prat, Tommaso Valletti

We study the link between political influence and industrial concentration. We present a joint model of political influence and market competition: an oligopoly lobbies the government over regulation, and competes in the product market shaped by this influence. We show broad conditions for mergers to increase lobbying, both on the intensive margin and the extensive margin. We combine data on mergers with data on lobbying expenditures and campaign contributions in the US from 1999 to 2017. We document a positive association between mergers and lobbying, both by individual firms and by industry trade associations. Mergers are also associated with extensive margin changes such as the formation of in-house lobbying teams and corporate PACs. We find some evidence for a positive association between mergers and higher campaign contributions.

Ali Hürriyetoğlu, Hristo Tanev, Vanni Zavarella et al.

This workshop is the fourth issue of a series of workshops on automatic extraction of socio-political events from news, organized by the Emerging Market Welfare Project, with the support of the Joint Research Centre of the European Commission and with contributions from many other prominent scholars in this field. The purpose of this series of workshops is to foster research and development of reliable, valid, robust, and practical solutions for automatically detecting descriptions of socio-political events, such as protests, riots, wars and armed conflicts, in text streams. This year workshop contributors make use of the state-of-the-art NLP technologies, such as Deep Learning, Word Embeddings and Transformers and cover a wide range of topics from text classification to news bias detection. Around 40 teams have registered and 15 teams contributed to three tasks that are i) multilingual protest news detection, ii) fine-grained classification of socio-political events, and iii) discovering Black Lives Matter protest events. The workshop also highlights two keynote and four invited talks about various aspects of creating event data sets and multi- and cross-lingual machine learning in few- and zero-shot settings.

Wellington Fernandes de Carvalho, Ludmila Silva Brighenti, Ralph Gruppi Thomé et al.

O Itapecerica é um importante rio do Centro-Oeste de Minas Gerais e vem sofrendo com diversos impactos antrópicos, como poluição e introdução de espécies exóticas. Por isso, ações de educação e conscientização ambiental, visando à valorização e preservação desse ecossistema e das espécies de peixes que o habitam são necessárias. Nesse intuito, elaboramos um guia ilustrado sobre a ictiofauna do rio Itapecerica para ser utilizado como material de apoio para o Ensino Médio. Cada espécie de peixe catalogada e descrita na literatura foi caracterizada quanto aos aspectos alimentares, reprodutivos, morfológicos e ecológicos. O guia traz uma breve descrição de 29 espécies de peixes do rio Itapecerica e da legislação estadual de pesca amadora. O guia foi utilizado como material didático base em palestras ministradas em novembro de 2019 para 330 alunos do Ensino Médio de uma escola da rede pública estadual de Divinópolis, Minas Gerais. Após a realização das palestras, observamos que o guia possibilitou aos alunos ampliarem seus conhecimentos sobre ictiologia, como a importância da preservação dos peixes, a distinção de espécies e também o seu papel no ecossistema. Além disso, propiciou um estreitamento da relação dos alunos com a natureza, contribuindo com algumas demandas da área educacional.

Andrea Andújar , Débora D'Antonio

En este artículo nos proponemos repasar las principales contribuciones que brindan los cruces entre las categorías de clase y género al conocimiento de la historia de la clase trabajadora en el pasado reciente argentino contemplando el lugar de las mujeres. Guían el desarrollo de esta revisión preguntas tales como: ¿cuáles han sido los principales problemas y tópicos que se examinaron?; ¿qué esfuerzos teórico-metodológicos comportó tal empresa? y ¿qué dimensiones y aristas aún permanecen inexploradas?

César Augusto Paro, Grasiele Nespoli, Luanda de Oliveira Lima