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Language: search.filters.language.EnglishSubject: search.filters.subject.Shipibo-Konibo

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    Economic knowledge of a group of adults from the Ashaninka and Shipibo-Konibo Indigenous Peoples
    (Universidade Estadual Paulista, 2024-01-08)
    This psychological study explores the level of economic thought among 16 adults from the Shipibo-Konibo and Asháninka Amazonian indigenous groups, in Peru. A constructivist-informed qualitative interview based on the Psychogenesis Model of Economic Thought (Denegri, 1995) was used in this study. Following the Piagetian cognitive stages, this interview proposes a three-level model for the psychogenesis of economic thought to account for the process of construction of explanations of the economic world. The results show the participants' particular modes of using formal logic tools to formulate a systematic understanding of economic processes, which possibly compromise their ability to make adaptive economic decisions and may encourage irrational economic behaviors such as thoughtless consumption and over-indebtedness. None of the participants displayed Level III inferential economic thinking, which requires the use of formal logic to understand economic processes in a systematic way. We discuss the implications of these findings for the development and fulfillment of indigenous people’s rights, especially the right to achieve human development that responds to their own complex cultural characteristics.
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    No data to crawl? Monolingual corpus creation from PDF files of truly low-resource languages in Peru
    (European Language Resources Association (ELRA), 2020)
    We introduce new monolingual corpora for four indigenous and endangered languages from Peru: Shipibo-konibo, Ashaninka, Yanesha and Yine. Given the total absence of these languages in the web, the extraction and processing of texts from PDF files is relevant in a truly low-resource language scenario. Our procedure for monolingual corpus creation considers language-specific and language-agnostic steps, and focuses on educational PDF files with multilingual sentences, noisy pages and low-structured content. Through an evaluation based on language modelling and character-level perplexity on a subset of manually extracted sentences, we determine that our method allows the creation of clean corpora for the four languages, a key resource for natural language processing tasks nowadays.
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