论文标题

部分可观测时空混沌系统的无模型预测

Dynamics of Gender Bias in Computing

论文作者

Misa, Thomas J

论文摘要

计算中的性别偏见是一个艰难的问题,它抵制了数十年的研究。一个障碍是缺乏系统的数据,这些数据可能表明何时在计算中出现性别偏差及其如何变化。本文介绍了一个新的数据集(N = 50,000),重点介绍了一项职业的计算年份(1950-1980),当时美国政府劳动力统计数据很薄或不存在。这个纵向数据集基于来自六个计算机用户组(共享,使用和其他)和ACM会议参与者和成员名册的档案记录,修改了通常持有的猜想,这些猜想是在1960年代或1970年代在计算机科学专业化期间出现的性别偏见,并且有一个“ linear”的性别性别偏见的态度。这样的线性视图还为计算机的“失去”女性的“管道”模型提供了支持。取而代之的是,该数据集揭示了计算中性别偏见的三个不同时期,因此为这些变化的动态邀请了时间上不同的解释。它可以显着修改学术评估和对计算中性别偏见的普遍理解。它还引起人们对计算中多样性的关注。当今CS改革工作的这项研究的结果之一是,数据驱动的认识是,从1980年代中期开始(不在几十年来)的性别偏见的遗产是问题。第二个后果是纠正计算机科学的公众形象:这项研究表明,性别偏见是专业计算的偶然性方面,而不是内在或永久性的。

Gender bias in computing is a hard problem that has resisted decades of research. One obstacle has been the absence of systematic data that might indicate when gender bias emerged in computing and how it has changed. This article presents a new dataset (N=50,000) focusing on formative years of computing as a profession (1950-1980) when U.S. government workforce statistics are thin or non-existent. This longitudinal dataset, based on archival records from six computer user groups (SHARE, USE, and others) and ACM conference attendees and membership rosters, revises commonly held conjectures that gender bias in computing emerged during professionalization of computer science in the 1960s or 1970s and that there was a 'linear' one-time onset of gender bias to the present. Such a linear view also lent support to the "pipeline" model of computing's "losing" women at successive career stages. Instead, this dataset reveals three distinct periods of gender bias in computing and so invites temporally distinct explanations for these changing dynamics. It significantly revises both scholarly assessment and popular understanding about gender bias in computing. It also draws attention to diversity within computing. One consequence of this research for CS reform efforts today is data-driven recognition that legacies of gender bias beginning in the mid-1980s (not in earlier decades) is the problem. A second consequence is correcting the public image of computer science: this research shows that gender bias is a contingent aspect of professional computing, not an intrinsic or permanent one.

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