新概念雙語：研究顯示女性“程序媛”寫的代碼更好

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.

美國研究者分析了開源代碼庫Github 140萬用戶的數(shù)據(jù)。他們發(fā)現(xiàn)和男性相比，女性發(fā)送的“拉請求”(代碼更新提議)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.

文章還需要同行審查。這意味著該研究結(jié)果仍然需要其他老師的嚴格評估。

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.

來自加州州立理工大學-圣路易斯奧比斯波和北卡羅萊納州立大學科學學院的研究者們在2015年4月1日這一天觀察了大約四百萬Github登錄用戶。

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.

作為一個龐大的社交編程網(wǎng)站，Github不要求其1200萬用戶提供性別信息。然而有些用戶的頭像可以清晰地分辨出性別，還有些用戶的郵箱和社交網(wǎng)站Google+關(guān)聯(lián)，所以研究團隊可以辨別大約140萬用戶的性別。

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.

研究者承認這樣做有侵犯隱私的風險，但是他們并不打算公開原始數(shù)據(jù)。該團隊發(fā)現(xiàn)女性發(fā)起的拉請求有78.6%被接受了，相比之下，男性的拉請求只有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.

研究者考慮了多方面因素，比如女性是否更傾向于對已知問題作出回應、是否女性的代碼比較短所以更容易通過評估、以及他們使用的是哪種編程語言，但是未能找到相關(guān)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，對于在該社區(qū)里不出名的用戶來說，頭像表明性別的女性的被接受率比性別不明確的低很多。

"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: “對于非會員，我們找到了性別偏見的證據(jù)：當女性使用性別不明的頭像時，她們的通過率為71.8%，然而當她們的性別可分辨時，這個百分比降到了62.5%。男性的數(shù)據(jù)也有相似的下降，但是影響沒有這么大。 ”

"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.

研究者總結(jié)道：“總體而言，女性的拉請求通過率比較高，但是非會員女性和性別可分辨的女性的通過率比男性低。我們的研究結(jié)果表明雖然總體上Github的女性用戶編程能力更強，但是碼農(nóng)的世界里存在性別偏見。”

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.

雖然采取了各種高調(diào)舉措，科技公司仍然面臨著性別和種族等員工多樣性帶來的挑戰(zhàn)，尤其是技術(shù)性更強的領(lǐng)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.

據(jù)2015發(fā)布的數(shù)據(jù)，F(xiàn)acebook的技術(shù)員工只有16%是女性，Google只有18%。計算機科學家Sue Black 博士(獲得英帝國勛章的軍官)告訴BBC：研究者發(fā)現(xiàn)的這個結(jié)果還是很鼓舞人心的。

"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.

她說：“我認為在接下來的幾年內(nèi)，我們將看到女性再一次掀起對包括編程在內(nèi)的所有技術(shù)工作的熱情。 對女性優(yōu)秀的編程能力的認可力證了一個事實：從事技術(shù)工作的女性的增多將使所有人受益。 ”

"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.

“世界上第一個提出軟件這一概念的是一名女性—Ada Lovelace，我們把這歸功于她，這讓我們更加堅信我們應該鼓勵和支持女性加入軟件產(chǎn)業(yè)。”