Science shows that women are better when the programmer can code: male agricultural source: Fried Eggs U.S. researchers analyzed open source project sharing service Github about 1 million 400 thousand user data. They found that women’s request code had a higher rate of pass through than men. The study is waiting for peer review. This means that the results are yet to be commented on by other experts. These from the California Polytechnic State University and North Carolina State University researchers, from April 1, 2015 4 million in the user login Github from 1 million 400 thousand users. Github is a huge developer community and does not require its 12 million users to fill in gender information. But the team is still able to distinguish them from the 1 million 400 thousand men’s sex, because the user data or their e-mail address can reveal traces. The researchers also acknowledge that there is privacy risk, so they do not intend to publish raw data. The team found that women’s request code had a combined acceptance rate of 78.6%, compared with 74.6% for males. The researchers consider a variety of factors, such as women know the possibility of some problems is higher, their contribution is shorter or they do the task easier and they use the programming language and so on, but the researchers found no correlation. However, those not known in the Github community of people, gender data show that he is put forward women who request code through the merger rate than those who are not obvious gender is much lower. Gender bias from an outsider’s perspective, we see the traces of gender bias: when women gender neutral data, they request code with the pass rate of 71.8%, but once they show that they are women, they immediately fell to 62.5% pass rate. Men’s passing rates also showed a similar decline, but not so obvious. Overall, women request code merging through higher rate than men, but when they become outsiders and their sex can be identified, their pass rate is lower than men. The researchers concluded: "our results show that although women in Github are generally more competent, they still encounter gender bias." Although there are high-profile initiatives, technology companies are still faced with the problem of employee diversity (in terms of gender and ethnicity). According to 2015 data, only 16% of Facebook technicians are women, and Google is only 18%. Sue Black OBE, a computer scientist, says that even so, the results are encouraging. She said: "I think these women showed interest in programming in the recovery, in the next few years, women will gradually interested in other technical related occupation. Knowing that women are good at programming will allow more women to work in the field of technology. Ada Lovelace, a woman who started the concept of software, is also a woman who knows this to better encourage and support women into the software industry."

科学表明女性更适合当程序员:男码农情何以堪   文章来源:煎蛋   美国的研究人员分析了开源项目共享服务Github里约140万用户的资料。他们发现女性提出的请求代码合并通过率比男性更高。该研究正在等待同行评议。这意味着这一结果尚有待其他专家点评。   这些来自加州州立理工大学和北卡罗莱纳州立大学的研究人员们,从2015年4月1日登入Github中的400万名用户中抽取了140万名用户。Github是一个庞大的开发者社区,并不要求其1200万用户填写性别信息。   不过该团队依旧能够辨别他们抽取的这140万人的性别,因为用户资料或者他们的邮箱地址都能透露蛛丝马迹。研究人员们也承认这有隐私风险,因此他们并不打算公布原始数据。   该团队发现女性提出的请求代码合并接受率为78.6%,而男性提出来的仅74.6%。研究人员们考虑了各种因素,比如女知道某些问题的可能性是否更高,她们贡献的代码更短或者她们做的任务更容易以及她们使用的编程语言等等,但研究人员没有找到相关联系。   然而那些在Github社区里并不出名的人中,性别资料显示自己是女性的人提出的请求代码合并通过率比那些性别不明显的人低得多。   性别偏见   从局外人的角度来看,我们看到了性别偏见的痕迹:当女性的性别资料中立的时候,她们提出的请求代码合并通过率为71.8%,可一旦她们表明自己是女性,她们的通过率立刻降至62.5%。男性的通过率也有相似的下降,但并没有这么明显。   总体来看女性提出的请求代码合并通过率比男性更高,可当她们成为外来者且她们的性别可被鉴定出来的时候,她们的通过率比男性低。研究人员们总结道:“我们的结果表明虽然Github里的女性总体来说更能干,但她们还是会遇到性别偏见。”   虽然有各种高调的倡议,但科技公司依旧面临着员工多样性的问题(从性别和种族这方面来看)。根据2015年的数据,脸书的技术人员里仅16%为女性,谷歌仅18%。   计算机科学家Sue Black OBE博士表示,即便如此这一结果依旧令人鼓舞。她说:“我认为这些表明女性对编程的兴趣在复苏,在接下来的几年时间里,女性也会慢慢对其它与技术相关的职业感兴趣。知道女性擅长编程,会让更多女性进入科技领域工作。最开始提出软件概念的Ada Lovelace也是一名女性,知道这一点才能更好地鼓励并支持女性进入软件行业。”相关的主题文章: