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      Judging a Book by its Description : Analyzing Gender Stereotypes in the Man Bookers Prize Winning Fiction

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          Abstract

          The presence of gender stereotypes in many aspects of society is a well-known phenomenon. In this paper, we focus on studying and quantifying such stereotypes and bias in the Man Bookers Prize winning fiction. We consider 275 books shortlisted for Man Bookers Prize between 1969 and 2017. The gender bias is analyzed by semantic modeling of book descriptions on Goodreads. This reveals the pervasiveness of gender bias and stereotype in the books on different features like occupation, introductions and actions associated to the characters in the book.

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          WordNet: a lexical database for English

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            The effect of an intervention to break the gender bias habit for faculty at one institution: a cluster randomized, controlled trial.

            Despite sincere commitment to egalitarian, meritocratic principles, subtle gender bias persists, constraining women's opportunities for academic advancement. The authors implemented a pair-matched, single-blind, cluster randomized, controlled study of a gender-bias-habit-changing intervention at a large public university.
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              What’s in a Name: Exposing Gender Bias in Student Ratings of Teaching

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                Author and article information

                Journal
                25 July 2018
                Article
                1807.10615

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                Custom metadata
                arXiv admin note: substantial text overlap with arXiv:1710.04117
                cs.CL cs.AI

                Theoretical computer science, Artificial intelligence

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