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A survey of accepted authors in computer systems conferences
PeerJ Computer Science ( IF 3.5 ) Pub Date : 2020-09-28 , DOI: 10.7717/peerj-cs.299
Eitan Frachtenberg 1 , Noah Koster 1
Affiliation  

Computer Science researchers rely on peer-reviewed conferences to publish their work and to receive feedback. The impact of these peer-reviewed papers on researchers’ careers can hardly be overstated. Yet conference organizers can make inconsistent choices for their review process, even in the same subfield. These choices are rarely reviewed critically, and when they are, the emphasis centers on the effects on the technical program, not the authors. In particular, the effects of conference policies on author experience and diversity are still not well understood. To help address this knowledge gap, this paper presents a cross-sectional study of 56 conferences from one large subfield of computer science, namely computer systems. We introduce a large author survey (n = 918), representing 809 unique papers. The goal of this paper is to expose this data and present an initial analysis of its findings. We primarily focus on quantitative comparisons between different survey questions and comparisons to external information we collected on author demographics, conference policies, and paper statistics. Another focal point of this study is author diversity. We found poor balance in the gender and geographical distributions of authors, but a more balanced spread across sector, experience, and English proficiency. For the most part, women and nonnative English speakers exhibit no differences in their experience of the peer-review process, suggesting no specific evidence of bias against these accepted authors. We also found strong support for author rebuttal to reviewers’ comments, especially among students and less experienced researchers.

中文翻译:

在计算机系统会议上接受作者的调查

计算机科学研究人员依靠经过同行评审的会议来发表他们的工作并获得反馈。这些同行评审论文对研究人员职业的影响很难被夸大。然而,即使在同一子领域中,会议组织者也可能对其审核过程做出不一致的选择。这些选择很少经过严格的审查,而当它们出现时,重点放在对技术程序的影响上,而不是作者。尤其是,会议政策对作者经验和多样性的影响仍然没有被很好地理解。为了帮助解决这一知识鸿沟,本文提出了来自计算机科学的一个大子领域(即计算机系统)的56个会议的横断面研究。我们引入了一个大型作者调查(n = 918),代表809篇独特的论文。本文的目的是公开这些数据并提出对其发现的初步分析。我们主要关注不同调查问题之间的定量比较,以及与我们收集的有关作者人口统计,会议政策和纸张统计数据的外部信息的比较。这项研究的另一个重点是作者多样性。我们发现作者的性别和地域分布之间的平衡不佳,但是跨行业,经验和英语水平的分布更为均衡。在大多数情况下,女性和说英语的人在同行评审过程中的经历没有差异,这表明没有具体证据表明对这些公认的作者有偏见。我们还发现强烈支持作者反驳审稿人的评论,尤其是在学生和经验不足的研究人员中。
更新日期:2020-09-28
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