Resumo Muito se tem discutido acerca dos fatores que levariam a uma atuação eficiente ou ineficiente do sistema judiciário brasileiro, e uma parte das discussões acadêmicas em relação ao campo de Administração da Justiça diz respeito aos antecedentes de desempenho/produtividade relativos aos tribunais e magistrados. Nesse sentido, o objetivo principal do presente trabalho foi identificar os aspectos determinantes da produtividade dos tribunais de justiça estaduais no Brasil e testar variáveis emergentes que possam auxiliar nesse entendimento. A partir de uma análise da literatura de referência, foram definidas variáveis já consolidadas: carga de trabalho, quantidade de recursos humanos (servidores efetivos e empregados terceirizados); e variáveis emergentes: advogados e conciliadores. A técnica de inferência utilizada foi a Regressão Múltipla com dados em painel. Após o teste e a validação do modelo e dos pressupostos da Regressão foram confirmadas as hipóteses de que a quantidade de advogados, a carga de trabalho e a quantidade de servidores efetivos e empregados terceirizados afetam a produtividade dos tribunais. Por último, os resultados apontam na direção contrária das orientações do Conselho Nacional de Justiça (CNJ); concluiu-se que a quantidade de conciliadores não está relacionada à produtividade dos tribunais de justiça.
The crisis caused by COVID-19 has triggered a series of changes at the global level, resulting in a rapid change in the way social relations are organized. The state is no exception to this complex scenario, and is responsible for making available to citizens the various administrative provisions essential to life in society, one of which is justice. In this context, the aim of the present work is to analyse the institutional response of the judiciary branch in Brazil to the pandemic period of the new coronavirus, contrasting the normative actions taken by the judiciary with the results obtained with these interventions. To that end, at first, the main regulations that have underpinned the conduct, positioning and action of the judiciary since the beginning of the crisis in Brazil, which occurred in March 2020, were collected and analysed in a total of 57 official documents issued by the Brazilian justice authorities. A posteriori, the report "Assessment of the impacts of the pandemic caused by COVID-19 on the court's work processes" was analysed, which includes analyses related to the adoption of rules relevant to issues of administrative management, procedural management and also the perceptions of impacts and difficulties due to the pandemic, as well as the other official documents published by the National Council of Justice -CNJ that provides statistics about the judicial indicators in times of pandemic. The data show a fast and comprehensive performance in the various fields in which justice operates, revealing a concern with health, social, administrative issues, among other aspects. The Judiciary has acted in an administrative unit, based on the regulations of a higher authority or of higher courts.
Maintaining the judiciary requires a high level of budgetary expenditure, but the specifics of this relationship have not yet been fully explored. While several studies have examined the impact of spending on the judiciary through measures related to productivity and performance, none have used machine learning techniques. This study examines the productivity of the court system based on expenditures and other variables using machine learning techniques. In the clustering process Brazilian courts are ranked according to their productivity, while in the neural network step it is verified which characteristics are most relevant at the budgetary level related to judicial productivity for each cluster formed in the first step. The final neural network model supports the results of Pearson’s parametric correlation test, which found no significant correlation between expenditure and productivity. The findings from this study demonstrate the importance of understanding that increasing public budget expenditures alone is not sufficient to improve the efficiency of the judicial system. Instead, other administrative measures are necessary to meet the demands of the Brazilian judiciary and improve service delivery rates. These results offer important theoretical and managerial contributions to the field.
Maintaining the judiciary's power requires a high level of budgetary expenditure, but the specifics of this relationship have yet to be fully explored. Although several studies have analyzed the impact of spending in the judiciary through productivity and performance-related measures, none have employed machine learning techniques. This study examines the productivity of the judiciary based on spending and other variables using machine learning techniques, including clustering and neural networks. The final neural network model supports the results of Pearson's parametric correlation test, which found no significant correlation between expenditure and productivity. This study's findings demonstrate the importance of understanding that increased public budgetary expenditure alone is insufficient for improving the judiciary's efficiency. Instead, other administrative and technical measures are necessary to meet the demands of the Brazilian judiciary and improve service delivery rates. These findings offer important theoretical and managerial contributions to the field.
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