During the pandemic, interactions with students had to be from a distance. This got me to think about biases in assessments. In one of the courses, students had to reflect on a technically difficult “Omics” paper, answering questions and giving critical feedback. As individual student-teacher interactions had to be quite minimal, I ended up with a bunch of documents with “faceless” names. In the process of marking different student's valiant efforts I noticed that, unsurprisingly, names still automatically conjured up faces, as names contain information regarding gender and ethnicity. Of course, I try to combat conscious prejudice. But “ay, there's the rub”: only a fool would deny unconscious prejudices. I am far from the first to notice that all kinds of (un)conscious biases pervade our (digital) work environment. Some can be more easily circumvented than others. In the case of my exams, a simple intermediary program removing all personal information and generating a random number, would do the trick.

Could such an intake system also be of use in publishing, as is currently being tried out by some publishing start-ups (or should I say “up-starts”?). One objection might be that there are real benefits to how the system currently operates. Aren't the “top” researchers better known for a reason? Overall, they produce higher quality work, so they should have easier access to widely read journals. Also, lesser known scientists making grandiose claims: should these indeed not be looked at more critically? Thus, it is reasoned, the identity of the people and the institute responsible for the paper just gives another valid criterion to base assessment on. On the other hand, high quality work should be able to stand on its own, and grandiose claims should always be met with skepticism, irrespective of the identity of the claimant.

But maybe we should first ask: is there even a real problem? I am afraid the answer is a qualified yes. Most scientists I have talked with (even the ones it benefits) detect a strong Matthew principle operating in science. Especially junior researchers from lesser known groups should have a better chance of publishing in high impact journals. The higher your scientific status, the easier it becomes to get published in the top journals, giving you a crucial advantage in quickly getting your message out, influencing the future direction of science as well as your career within it. This will lead to both “overrated” and “underrated” articles. The first outcome I consider no big deal, but the second I consider really detrimental to scientific progress. Let me illustrate from indirect personal experience. In the nineties I was working on my PhD, often using Blue Native Gel Electrophoresis (BNE) to characterize mitochondrial respiratory chain complexes, a technique pioneered by Schägger and von Jagow.^[1] Using the same technique in a different research project, I often shared the lab late at night with Leo Nijtmans, who under the supervision of Coby van den Bogert, was doing something I considered revolutionary. He studied the assembly of complex IV, cytochrome-c oxidase, in the presence of inhibitors of either mitochondrial or cytosolic protein synthesis, by metabolic labelling of a human leukemia cell line, followed by BNE, classical SDS-PAGE, and Western blot analysis. This allowed the first ever identification of assembly intermediates of complex IV.^[2] His supervisor who was still building her own research group at the time, became gravely ill and sadly died before the paper was published. Leo and I noticed the tremendous difficulty in getting the paper accepted and, in the end, he had to “settle” for the European Journal of Biochemistry (now the FEBS Journal), which did not have the impact factor we thought the paper deserved. A current Google Scholar citations number approaching 300 (!) rather supports our initial assessment, I would say. Leo would go on to research and describe (in great detail) the biogenesis of the, even more complicated, first respiratory complex, NADH dehydrogenase.^[3] Alas, after contributing a lot to our understanding of the biogenesis of mitochondrial respiration complexes, Leo also died, much too early, in 2018. I sometimes wonder if he would have had an even greater impact if article selection and acceptance would have been more unbiased when he started out.

So, how can we level the playing field? I think the problem is most pronounced with the absolute top-tier journals, so their editorial staffs and reviewers might indeed benefit from procedures and training to root out the detrimental effects of the Matthew principle. Then again, there are some pretty good journals out there that seem to be less afflicted. By submitting to these we could initiate a process of extending, instead of just levelling, the playing field.

在大流行期间，与学生的互动必须远距离进行。这让我开始思考评估中的偏见。在其中一门课程中，学生必须反思技术难度较大的“组学”论文，回答问题并给出批评性反馈。由于个别学生与教师的互动必须非常少，我最终得到了一堆带有“匿名”名字的文件。在给不同学生的英勇努力打分的过程中，我注意到，不出所料，名字仍然会自动让人联想到面孔，因为名字包含有关性别和种族的信息。当然，我试图与有意识的偏见作斗争。但是“哎，问题来了”：只有傻瓜才会否认无意识偏见。我远不是第一个注意到各种（无意识的）偏见弥漫在我们的（数字）工作环境中的。有些比其他的更容易规避。就我的考试而言，一个简单的中间程序会删除所有个人信息并生成一个随机数，就可以解决问题。

这样的引入系统是否也可以用于出版业，正如一些出版初创公司目前正在尝试的那样（或者我应该说“新兴公司”？）。一种反对意见可能是，该系统目前的运作方式确实有好处。难道“顶级”研究人员更出名是有原因的吗？总体而言，他们产生了更高质量的工作，因此他们应该更容易访问广泛阅读的期刊。此外，鲜为人知的科学家提出了宏伟的主张：这些确实不应该更批判地看待吗？因此，可以推论，负责该论文的人和机构的身份只是提供了另一个有效的评估依据。另一方面，高质量的作品应该能够独立存在，无论索赔人的身份如何，浮夸的主张都应该遭到怀疑。

但也许我们应该先问：真的有问题吗？恐怕答案是肯定的。与我交谈过的大多数科学家（即使是那些从中受益的科学家）都发现了在科学中运作的强大马太原理。特别是来自鲜为人知的团体的初级研究人员应该有更好的机会在高影响期刊上发表文章。你的科学地位越高，就越容易在顶级期刊上发表，这让你在快速传播信息、影响科学的未来方向以及你在其中的职业生涯方面具有至关重要的优势。这将导致“被高估”和“被低估”的文章。我认为第一个结果没什么大不了，但我认为第二个结果对科学进步非常不利。让我从间接的个人经验来说明。九十年代我正在攻读博士学位，^{[ 1 ]}在不同的研究项目中使用相同的技术，我经常在深夜与 Leo Nijtmans 共享实验室，他在 Coby van den Bogert 的监督下正在做一些我认为具有革命性的事情。他通过对人类白血病细胞系进行代谢标记，然后进行 BNE、经典 SDS-PAGE 和蛋白质印迹分析，研究了在线粒体或胞质蛋白合成抑制剂存在的情况下，复合体 IV、细胞色素-c 氧化酶的组装。这使得首次鉴定出复合体 IV 的组装中间体。^{[ 2 ]}他的导师当时还在建立自己的研究小组，在论文发表之前病重并不幸去世。Leo 和我注意到让论文被接受的巨大困难，最后，他不得不“安顿”到欧洲生物化学杂志（现在的 FEBS 杂志），该杂志没有我们认为该论文应得的影响因子。我想说，当前的 Google Scholar 引用数接近 300 (!) 更支持我们的初步评估。Leo 将继续研究并（非常详细地）描述更复杂的第一个呼吸复合体 NADH 脱氢酶的生物发生。^{[ 3 ]} 唉，在我们对线粒体呼吸复合物的生物起源的理解做出了很多贡献之后，Leo 也于 2018 年去世，太早了。我有时想知道如果文章选择和接受更公正，他是否会产生更大的影响当他开始的时候。

那么，我们如何才能公平竞争？我认为这个问题在绝对顶级期刊上最为明显，因此他们的编辑人员和审稿人可能确实会从程序和培训中受益，以消除马太原则的不利影响。再说一次，有一些相当不错的期刊似乎受到的影响较小。通过服从这些，我们可以启动一个扩展而不是仅仅平整竞争环境的过程。