522 research outputs found

    “Think Global, Act Local”: Refocusing Priorities for NHRI Evaluation in the context of the Iberoamerican Defensor del Pueblo.

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    Irreverent Persia

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    Poetry expressing criticism of social, political and cultural life is a vital integral part of Persian literary history. Its principal genres - invective, satire and burlesque - have been very popular with authors in every age. Despite the rich uninterrupted tradition, such texts have been little studied and rarely translated. Their irreverent tones range from subtle irony to crude direct insults, at times involving the use of outrageous and obscene terms. This anthology includes both major and minor poets from the origins of Persian poetry (10th century) up to the age of Jami (15th century), traditionally considered the last great classical Persian poe

    Framing Visual Perception in Terms of Sensorimotor Mapping

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    Two contrasting theories, or variants of them, are predominant in the current debate on visual cognition. The standard inferential theory sees perception as a process involving the role of memory, past experiences and semantic abilities, whereas the direct theory sees perception as a connection between the perceiver and the environment that does not recruit internal information processing. In particular, the direct theory has recently been invoked because it would be able to explain the sensorimotor coupling of perception and action in humans and animals without relying on controversial notions such as those of conceptualization and propositional information. This paper aims to show that even an inferential theory of perception has enough resources to account for sensorimotor processes without necessarily involving high level cognitive functions. My claim is that there are genuine instances of sensorimotor inferential processing that do not rely on conceptual structures and propositional knowledge. Several theoretical and empirical arguments are provided to support this statement

    Dynamic Human Reliability Assessment enhanced with Bayesian Networks; a Comparison with Classical Approaches

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