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首页> 外文期刊>Journal of the Association for Information Science and Technology >Female librarians and male computer programmers? Gender bias in occupational images on digital media platforms
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Female librarians and male computer programmers? Gender bias in occupational images on digital media platforms

机译：女图书馆员和男性计算机程序员？数字媒体平台职业图像中的性别偏见

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摘要

Media platforms, technological systems, and search engines act as conduits and gatekeepers for all kinds of information. They often influence, reflect, and reinforce gender stereotypes, including those that represent occupations. This study examines the prevalence of gender stereotypes on digital media platforms and considers how human efforts to create and curate messages directly may impact these stereotypes. While gender stereotyping in social media and algorithms has received some examination in the recent literature, its prevalence in different types of platforms (for example, wiki vs. news vs. social network) and under differing conditions (for example, degrees of human- and machine-led content creation and curation) has yet to be studied. This research explores the extent to which stereotypes of certain strongly gendered professions (librarian, nurse, computer programmer, civil engineer) persist and may vary across digital platforms (Twitter, the New York Times online, Wikipedia, and Shutterstock). The results suggest that gender stereotypes are most likely to be challenged when human beings act directly to create and curate content in digital platforms, and that highly algorithmic approaches for curation showed little inclination towards breaking stereotypes. Implications for the more inclusive design and use of digital media platforms, particularly with regard to mediated occupational messaging, are discussed.
机译：媒体平台，技术系统和搜索引擎充当各种信息的导管和门卫。他们经常影响，反思和强化性别刻板印象，包括代表职业的人。本研究探讨了数字媒体平台对性别刻板印象的普遍性，并考虑了人类努力如何直接产生和策划消息可能会影响这些刻板印象。虽然性别在社会媒体和算法定型已经收到了一些检查在最近的文献，它在不同类型的平台（例如，维基新闻主场迎战主场迎战社交网络），并在不同的条件（例如，度人 - 的患病率和机器LED内容创建和策展尚未研究。本研究探讨到一定的强烈性别职业（图书管理员，护士，计算机程序员，土木工程师）的刻板印象仍然存在，可以通过数字平台（微博，纽约时报在线，Wikipedia和存在Shutterstock）变化的程度。结果表明，当人类直接在数字平台上创造和愈合含量时，性别刻板印象最有可能受到挑战，并且高度算法的策择方法表明倾向于破坏刻板印象。讨论了对数字媒体平台的更包容性设计和使用的影响，特别是关于介导的职业消息传递。

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    Vivek K. Singh; Mary Chayko; Raj Inamdar; Diana Floegel;

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    School of Communication and Information Rutgers University New Brunswick New Jersey;

    School of Communication and Information Rutgers University New Brunswick New Jersey;

    School of Communication and Information Rutgers University New Brunswick New Jersey;

    School of Communication and Information Rutgers University New Brunswick New Jersey;

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