程序媛优于程序猿？The US researchers analysed nearly 1.4 million users of the open source program-sharing service Github. They found that pull requests - or suggested code changes - made on the service by women were more likely to be accepted than those by men.
美国研究者分析了开源代码库Github 140万用户的数据。他们发现和男性相比，女性发送的“拉请求”（代码更新提议）更容易被接受。
The paper is awaiting peer review. This means the results have yet to be critically appraised by other experts.
文章还需要同行审查。这意味着该研究结果仍然需要其他专家的严格评估。
The researchers, from the computer science departments at Cal Poly, San Luis Obispo, and North Carolina State University, looked at around four million people who logged on to Github on a single day - 1 April 2015.
来自加州州立理工大学-圣路易斯奥比斯波和北卡罗莱纳州立大学科学学院的研究者们在2015年4月1日这一天观察了大约四百万Github登录用户。
Github is an enormous developer community which does not request gender information from its 12 million users. However the team was able to identify whether roughly 1.4m were male or female - either because it was clear from the users’ profiles or because their email addresses could be matched with the Google + social network.
作为一个庞大的社交编程网站，Github不要求其1200万用户提供性别信息。然而有些用户的头像可以清晰地分辨出性别，还有些用户的邮箱和社交网站Google+关联，所以研究团队可以辨别大约140万用户的性别。
The researchers accepted that this was a privacy risk but said they did not intend to publish the raw data. The team found that 78.6% of pull requests made by women were accepted compared with 74.6% of those by men.
研究者承认这样做有侵犯隐私的风险，但是他们并不打算公开原始数据。该团队发现女性发起的拉请求有78.6%被接受了，相比之下，男性的拉请求只有74.6%被接受。
The researchers considered various factors, such as whether women were more likely to be responding to known issues, whether their contributions were shorter in length and so easier to appraise, and which programming language they were using, but they could not find a correlation.
研究者考虑了多方面因素，比如女性是否更倾向于对已知问题作出回应、是否女性的代码比较短所以更容易通过评估、以及他们使用的是哪种编程语言，但是未能找到相关性。
However among users who were not well known within the community, those whose profiles made clear that they were women had a much lower acceptance rate than those whose gender was not obvious.
然而，对于在该社区里不出名的用户来说，头像表明性别的女性的被接受率比性别不明确的低很多。
"For outsiders, we see evidence for gender bias: women’s acceptance rates are 71.8% when they use gender neutral profiles, but drop to 62.5% when their gender is identifiable . There is a similar drop for men, but the effect is not as strong," the paper noted.
文章提到: “对于非会员，我们找到了性别偏见的证据：当女性使用性别不明的头像时，她们的通过率为71.8%，然而当她们的性别可分辨时，这个百分比降到了62.5%。男性的数据也有相似的下降，但是影响没有这么大。 ”
"Women have a higher acceptance rate of pull requests overall, but when they’re outsiders and their gender is identifiable, they have a lower acceptance rate than men. Our results suggest that although women on Github may be more competent overall, bias against them exists nonetheless," the researchers concluded.
研究者总结道：“总体而言，女性的拉请求通过率比较高，但是非会员女性和性别可分辨的女性的通过率比男性低。我们的研究结果表明虽然总体上Github的女性用户编程能力更强，但是码农的世界里存在性别偏见。”
Despite various high profile initiatives, tech firms continue to face challenges in terms of the diversity of their staff, in terms of both gender and ethnicity, particularly in more technical careers.
虽然采取了各种高调举措，科技公司仍然面临着性别和种族等员工多样性带来的挑战，尤其是技术性更强的领域。
Just 16% of Facebook’s tech staff and 18% of Google’s are women according to figures released in 2015. However the researchers’ findings are still encouraging, computer scientist Dr Sue Black OBE told the BBC.
据2015发布的数据，Facebook的技术员工只有16%是女性，Google只有18%。计算机科学家Sue Black 博士（获得英帝国勋章的军官）告诉BBC：研究者发现的这个结果还是很鼓舞人心的。
"I think we are going to see a resurgence of interest from women in not only coding but all sorts of tech-related careers over the next few years," she said. "Knowing that women are great at coding gives strength to the case that it’s better for everyone to have more women working in tech.
她说：“我认为在接下来的几年内，我们将看到女性再一次掀起对包括编程在内的所有技术工作的热情。 对女性优秀的编程能力的认可力证了一个事实：从事技术工作的女性的增多将使所有人受益。 ”
"It was a woman - Ada Lovelace - who came up with the idea of software in the first place, we owe it to her to make sure that we encourage and support women into the software industry," Dr Black added.
“世界上第一个提出软件这一概念的是一名女性—Ada Lovelace，我们把这归功于她，这让我们更加坚信我们应该鼓励和支持女性加入软件产业。”
