Publications

This chapter offers an actor-centred map of Chile’s executive triangle (ET) that comprises executive politicians, advisers, and top bureaucrats. We rely on a July 2024 snapshot of 272 posts. First, we address the structure and composition of the executive triangle, considering the Chilean institutional architecture, before examining levels of data transparency. Subsequently, we analyse demographic features, education, careers and political experience. The ET shows a balanced apex of politicians and advisers above a larger administrative cohort of ministerial division heads. We detect a top-heavy parity in which women reach equal representation or better in the most visible posts yet remain underrepresented in operational roles. Credentials are exceptional and internationally oriented, and career trajectories tend to be role-specific. Finally, politicisation is highest among politicians, moderate for advisers, and limited for bureaucrats.

This study examines audience-media relations in the context of protest coverage, testing how dynamics of news media amplification and contestation in social media compare between legacy and alternative media. Empirically, we use difference-in-differences models to analyse the effects of the 2019 Chilean protests and a subsequent political agreement on audience-media interactions. Additionally, we probe such interactions as spaces for the expression of negative emotions, directed to media outlets as toxic replies. To this end, we apply pre-trained machine learning models to identify toxicity in user comments. Our dataset includes over 21 million posts mentioning 22 Chilean news organisations during a six-month period spanning three months before and after the protests. The findings show overall increased interactions with both media types after the outbreak of the protests, with distinct patterns of response: alternative media was more amplified while legacy media was more contested, reflecting on broader patterns of public media criticism. These results underscore the audience-media dynamic as a foundational element in how protests are portrayed and collectively interpreted.

Os regimes democráticos contemporâneos têm enfrentado uma crise de legitimidade que compromete a credibilidade dos intervenientes políticos. Em particular, os órgãos governativos, em virtude da sua importância na execução de propostas políticas, têm sido alvo de um escrutínio público mais intenso pelo eleitorado. Tal fenómeno, embora transversal, tem efeitos significativos na política portuguesa e, mais concretamente, na ação dos governos nacionais, moldando a composição dos lugares ministeriais. Por isso, de forma paralela à crise de legitimidade, os ministros «independentes» e/ou «tecnocratas» têm assumido, crescentemente, o papel de protagonistas na governação, emergindo, em certa medida, como solução para a desconfiança sobre a atividade política e para a perceção de incompetência dos executivos na promoção do bem público. Daqui decorre uma questão: será que a governação num paradigma democrático, tida como fonte de legitimidade, é moldada pelas características dos ministros — nomeadamente pela sua experiência política e pelas suas competências técnicas?

This article examines the multifaceted nature of the rule of law. It primarily shows a way to measure how the meaning of the rule of law differs across countries, or across different contexts more generally, by analyzing parliamentary discourse on the rule of law. The findings point to a convergence in the conceptualization of the rule of law across diverse legal traditions despite *ex ante* differences between common law, French, German, and postsocialist legal traditions. The article also proposes a principled approach for deriving weights for rule-of-law indicators in order to assess the sensitivity of country rankings with respect to the adherence to rule-of-law principles.

The same dataset can be analysed in different justifiable ways to answer the same research question, potentially challenging the robustness of empirical science. In this crowd initiative, we investigated the degree to which research findings in the social and behavioural sciences are contingent on analysts’ choices. We examined a stratified random sample of 100 studies published between 2009 and 2018, in which, for one claim per study, at least five reanalysts independently reanalysed the original data. The statistical appropriateness of the reanalyses was assessed in peer evaluations, and the robustness indicators were inspected along a range of research characteristics and study designs. We found that 34% of the independent reanalyses yielded the same result (within a tolerance region of +/-0.05 Cohen’s *d*) as the original report; with a four times broader tolerance region, this indicator increased to 57%. Of the reanalyses conducted, 74% reached the same conclusion as the original investigation, 24% yielded no effects or inconclusive results and 2% reported the opposite effect. This exploratory study indicates that the common single-path analyses in social and behavioural research should not be simply assumed to be robust to alternative analyses. Therefore, we recommend the development and use of practices to explore and communicate this neglected source of uncertainty.

This paper describes the creation of a novel dataset on ministerial turnover and resignation calls in 12 presidential cabinets in Latin America from the mid-1970s to the early 2020s. The indicators on resignation calls and reallocations of cabinet members are entirely novel. Both constitute a relevant empirical contribution not only to the study of political dynamics in presidential systems and cabinet politics but also to public opinion and public policy topics. We focus on the creation of the dataset using optical recognition algorithms on press report archives together with machine learning models. The models permitted the training of ensemble semi-supervised classifiers over a period of almost 50 years. Subsequently, we provide a number of measurement validity checks to cross-validate the dataset by comparing it with similar existing data and an exploratory analysis.

How do ministerial terminations affect presidential approval? Presidents face unexpected challenges related to stochastic events such as scandals, policy failures, or economic crises. We argue that the termination of ministers who have received calls for their resignation presents an opportunity for the president to send signals to the electorate in the expectation of a corrective effect on popularity through a blame-shifting dynamic. The central argument is that this dynamic occurs only in coalition governments where political responsibility may be more easily attributed to the coalition’s different parties and factions, weakening personalization centered on the president and facilitating blame shifting and the corrective effect. The expectation of a corrective effect on approval is tested using instrumental variables (IV) regressions applied to novel data on ministerial terminations and resignation calls in 124 governments in 12 presidential democracies. The data were gathered by combining data mining, machine-learning techniques, and survey marginal time series based on the dyad ratios algorithm for approval. The main findings support the expectation that individual terminations of tainted ministers generate a corrective effect of nine points on presidential approval in coalition governments, which decreases in the medium and long term.

El presente documento corresponde al informe final del “Estudio de análisis de uso del tiempo y relación con perfiles de participación cultural”, contratado por el Departamento de Estudios de la Subsecretaría de las Culturas y de las Artes. El objetivo general del estudio es analizar y contextualizar la Encuesta Nacional de Uso del Tiempo (II ENUT 2023) en relación con la Encuesta Nacional de Participación Cultural y Comportamiento Lector (ENPCCL 2024), con el fin de caracterizar perfiles de uso del tiempo de distintos grupos de interés para las políticas culturales.

The rule of law is a foundational concept of state governance, admired for its ideals but also subject to significant controversy, particularly concerning its precise definition. Given the complexity of this evolving field, both in theory and practice, our article analyzes the existing academic literature on the rule of law. First and foremost, it aims to tackle the research question of what the thematic focus is within the rule of law literature. To accomplish this, the article extracts data from the Web of Science (WoS) and employs a bibliometric analysis that includes topic modeling and network analysis techniques. The article likewise presents a rich description of the field by elucidating its intellectual structure and identifying, among other aspects, key sources, references, and influential authors. This article serves as an invaluable resource for those who are new to the field of the rule of law, providing a concise and comprehensive overview of its complex landscape.

Large Language Models (LLMs) offer promising avenues for methodological and applied innovations in survey research by using synthetic respondents to emulate human answers and behaviour, potentially mitigating measurement and representation errors. However, the extent to which LLMs recover aggregate item distributions remains uncertain and downstream applications risk reproducing social stereotypes and biases inherited from training data. We evaluate the reliability of LLM-generated synthetic survey responses against ground-truth human responses from a Chilean public opinion probabilistic survey. Specifically, we benchmark 128 prompt-model-question triplets, generating 189,696 synthetic profiles, and pool performance metrics (i.e., accuracy, precision, recall, and F1-score) in a meta-analysis across 128 question-subsample pairs to test for biases along key sociodemographic dimensions. The evaluation spans OpenAI’s GPT family and o-series reasoning models, as well as Llama and Qwen checkpoints. Three results stand out. First, synthetic responses achieve excellent performance on trust items (F1-score and accuracy > 0.90). Second, GPT-4o, GPT-4o-mini and Llama 4 Maverick perform comparably on this task. Third, synthetic-human alignment is highest among respondents aged 45-59. Overall, LLM-based synthetic samples approximate responses from a probabilistic sample, though with substantial item-level heterogeneity. Capturing the full nuance of public opinion remains challenging and requires careful calibration and additional distributional tests to ensure algorithmic fidelity and reduce errors.