Constraints on the lexicons of human languages have cognitive roots present in baboons (Papio papio)

Emmanuel Chemla, Isabelle Dautriche, Brian Buccola, Joël Fagot
<span title="2019-07-09">2019</span> <i title="Proceedings of the National Academy of Sciences"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nvtuoas5pbdsllkntnhizy4f4q" style="color: black;">Proceedings of the National Academy of Sciences of the United States of America</a> </i> &nbsp;
Using a pattern extraction task, we show that baboons, like humans, have a learning bias that helps them discover connected patterns more easily than disconnected ones—i.e., they favor rules like "contains between 40% and 80% red" over rules like "contains around 30% red or 100% red." The task was made as similar as possible to a task previously run on humans, which was argued to reveal a bias that is responsible for shaping the lexicons of human languages, both content words (nouns and
more &raquo; ... es) and logical words (quantifiers). The current baboon result thus suggests that the cognitive roots responsible for regularities across the content and logical lexicons of human languages are present in a similar form in other species.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1073/pnas.1907023116">doi:10.1073/pnas.1907023116</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/a2ztlakwz5cv5jhqre5j2gxrsa">fatcat:a2ztlakwz5cv5jhqre5j2gxrsa</a> </span>
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