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  1. More is Better: English Language Statistics are Biased Toward Addition.Bodo Winter, Martin H. Fischer, Christoph Scheepers & Andriy Myachykov - 2023 - Cognitive Science 47 (4):e13254.
    We have evolved to become who we are, at least in part, due to our general drive to create new things and ideas. When seeking to improve our creations, ideas, or situations, we systematically overlook opportunities to perform subtractive changes. For example, when tasked with giving feedback on an academic paper, reviewers will tend to suggest additional explanations and analyses rather than delete existing ones. Here, we show that this addition bias is systematically reflected in English language statistics along several (...)
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  • Implicit Bias Reflects the Company That Words Keep.David J. Hauser & Norbert Schwarz - 2022 - Frontiers in Psychology 13.
    In everyday language, concepts appear alongside related concepts. Societal biases often emerge in these collocations; e.g., female names collocate with art- related concepts, and African American names collocate with negative concepts. It is unknown whether such collocations merely reflect societal biases or contribute to them. Concepts that are themselves neutral in valence but nevertheless collocate with valenced concepts provide a unique opportunity to address this question. For example, when asked, most people evaluate the concept “cause” as neutral, but “cause” is (...)
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  • The role of valence and arousal for phonological iconicity in the lexicon of German: a cross-validation study using pseudoword ratings.David Schmidtke & Markus Conrad - forthcoming - Cognition and Emotion.
    The notion of sound symbolism receives increasing interest in psycholinguistics. Recent research – including empirical effects of affective phonological iconicity on language processing (Adelman et al., 2018; Conrad et al., 2022) – suggested language codes affective meaning at a basic phonological level using specific phonemes as sublexical markers of emotion. Here, in a series of 8 rating-experiments, we investigate the sensitivity of language users to assumed affectively-iconic systematic distribution patterns of phonemes across the German vocabulary:After computing sublexical-affective-values (SAV) concerning valence (...)
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