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        La naturalización de las emociones

        Anotaciones a partir de Wittgenstein

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        Author(s)
        Loaiza, Juan
        Collection
        Knowledge Unlatched (KU); KU Open Services
        Number
        104845
        Language
        Spanish
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        Abstract
        En la literatura sobre las emociones una de las teorías con mayor fuerza es la llamada “teoría James-Lange”. En esta obra se intenta hacer una crítica a dicha teoría a partir de algunas observaciones de Wittgenstein sobre el uso de conceptos psicológicos, sacando a la luz dos confusiones gramaticales que surgen en ella. Para ello, se construye primero la categoría de “programa de naturalización de las emociones” que recoge las teorías del Descartes, James y Prinz, siguiendo la metodología de Lakatos. Luego, se identifica como problema central el de la naturalización de la intencionalidad. Para luego exponer algunas herramientas de Wittgenstein para estudiar la gramática de la pregunta por el objeto y la intencionalidad las emociones, mostrando que las respuestas del programa de naturalización no son satisfactorias y no respetan las reglas de ciertos usos del lenguaje.
        URI
        https://library.oapen.org/handle/20.500.12657/44194
        Keywords
        Psychology; Emotions
        DOI
        https://doi.org/10.12804/op9789587387247
        ISBN
        9789587387247
        Publisher
        Editorial Universidad del Rosario
        Publisher website
        https://editorial.urosario.edu.co/
        Publication date and place
        2016
        Grantor
        • Knowledge Unlatched
        Imprint
        Editorial Universidad del Rosario
        Classification
        Psychology: emotions
        Rights
        https://creativecommons.org/licenses/by-nc/4.0/legalcode
        • Harvested from KU

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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