A implementação das sentenças condenatórias proferidas pela corte interamericana de direitos humanos no Brasil

A proposta do presente trabalho é fazer uma análise da prática brasileira em matéria de implementação das sentenças condenatórias proferidas pela Corte Interamericana de Direitos Humanos. Para tanto, parte-se do pressuposto de que, conforme estabelecido na Convenção Americana sobre Direitos Humanos, é dever do Estado garantir meios para adequar sua estrutura interna às obrigações internacionalmente contraídas. Mais que isso, entende-se que, uma vez declarada a responsabilidade internacional do Estado, surge o dever de reparar a violação perpetrada. Nesse sentido, demonstrar-se-á que no Brasil, ainda hoje, não há mecanismos legais ou qualquer outro procedimento claro e robusto para orientar a execução dos julgados. A implementação é casuística, o que dificulta o cumprimento integral e célere das medidas reparatórias estabelecidas na sentença e contribui para perpetuação das violações aos direitos humanos. Contudo, o Brasil ratificou a Convenção Americana e reconheceu a jurisdição contenciosa da Corte. Logo, a não implementação das sentenças é algo a ser combatido. O Estado contraiu para si obrigação de respeitar os direitos e garantias consagradas nos instrumentos internacionais, não pode, por questões internas, se esquivar da adequada proteção e promoção dos direitos humanos. Ao contrário disso, é dever do Estado brasileiro assegurar a efetividade das decisões interamericanas

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Educomunicação e suas áreas de intervenção: Novos paradigmas para o diálogo intercultural

oai:omp.abpeducom.org.br:publicationFormat/1O material aqui divulgado representa, em essência, a contribuição do VII Encontro Brasileiro de Educomunicação ao V Global MIL Week, da UNESCO, ocorrido na ECA/USP, entre 3 e 5 de novembro de 2016. Estamos diante de um conjunto de 104 papers executivos, com uma média de entre 7 e 10 páginas, cada um. Com este rico e abundante material, chegamos ao sétimo e-book publicado pela ABPEducom, em seus seis primeiros anos de existência. A especificidade desta obra é a de trazer as “Áreas de Intervenção” do campo da Educomunicação, colocando-as a serviço de uma meta essencial ao agir educomunicativo: o diálogo intercultural, trabalhado na linha do tema geral do evento internacional: Media and Information Literacy: New Paradigms for Intercultural Dialogue

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost