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      Cultural cartography with word embeddings

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      Poetics
      Elsevier BV

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          Indexing by latent semantic analysis

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            The Diversity–Innovation Paradox in Science

            Prior work finds a diversity paradox: Diversity breeds innovation, yet underrepresented groups that diversify organizations have less successful careers within them. Does the diversity paradox hold for scientists as well? We study this by utilizing a near-complete population of ∼1.2 million US doctoral recipients from 1977 to 2015 and following their careers into publishing and faculty positions. We use text analysis and machine learning to answer a series of questions: How do we detect scientific innovations? Are underrepresented groups more likely to generate scientific innovations? And are the innovations of underrepresented groups adopted and rewarded? Our analyses show that underrepresented groups produce higher rates of scientific novelty. However, their novel contributions are devalued and discounted: For example, novel contributions by gender and racial minorities are taken up by other scholars at lower rates than novel contributions by gender and racial majorities, and equally impactful contributions of gender and racial minorities are less likely to result in successful scientific careers than for majority groups. These results suggest there may be unwarranted reproduction of stratification in academic careers that discounts diversity’s role in innovation and partly explains the underrepresentation of some groups in academia.
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              A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge.

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Poetics
                Poetics
                Elsevier BV
                0304422X
                May 2021
                May 2021
                : 101567
                Article
                10.1016/j.poetic.2021.101567
                9b474cff-82d6-4760-a44b-ab638659433a
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

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