The gender produced by legal discourse in Brazil: Reflections from policy categories of law in Brazil

Este artigo tem como propósito refletir sobre algumas categorias políticas presentes no Direito brasileiro e relativas a normas de gênero, compreendendo o direito enquanto um discurso. Busca-se traçar um delineamento sobre normas de gênero e teoria do reconhecimento, a partir de Judith Butler, passando a refletir o direito como tecnologia de gênero e, finalmente, trazendo algumas categorias relativas às normas de gênero presentes no discurso jurídico brasileiro, especialmente no texto constitucional, em decisões do Supremo Tribunal Federal (STF) e em algumas normativas legais. Assim, localiza-se como o discurso jurídico oculta o sujeito de e também encobre mecanismos de sua própria constituição nas relações de poder, caracterizando limitações das categorias políticas utilizadas no discurso jurídico brasileiro. ____ This article aims to reflect on some political categories present in Brazilian law and related to gender norms, understanding law as a discourse. It seeks to outline a delineation of gender norms and theory of recognition, based on Judith Butler, starting to reflect on law as a technology of gender and, finally, bringing some categories related to gender norms present in Brazilian legal discourse, especially in the constitutional text, in decisions of the Federal Supreme Court (STF) and in some legal regulations. Thus, it is located how the legal discourse hides the subject of and also hides mechanisms of its own constitution in power relations, characterizing limitations of the political categories used in the Brazilian legal discourse.info:eu-repo/semantics/publishedVersio

Towards Comprehensive Foundations of Computational Intelligence

Abstract. Although computational intelligence (CI) covers a vast variety of different methods it still lacks an integrative theory. Several proposals for CI foundations are discussed: computing and cognition as compression, meta-learning as search in the space of data models, (dis)similarity based methods providing a framework for such meta-learning, and a more general approach based on chains of transformations. Many useful transformations that extract information from features are discussed. Heterogeneous adaptive systems are presented as particular example of transformation-based systems, and the goal of learning is redefined to facilitate creation of simpler data models. The need to understand data structures leads to techniques for logical and prototype-based rule extraction, and to generation of multiple alternative models, while the need to increase predictive power of adaptive models leads to committees of competent models. Learning from partial observations is a natural extension towards reasoning based on perceptions, and an approach to intuitive solving of such problems is presented. Throughout the paper neurocognitive inspirations are frequently used and are especially important in modeling of the higher cognitive functions. Promising directions such as liquid and laminar computing are identified and many open problems presented.