我花了二十年时间,在错误的领域里变得精通。
I Spent Twenty Years Becoming Good at the Wrong Game

原始链接: https://savvynormie.com/i-spent-twenty-years-becoming-good-at-the-wrong-game/

在获得俄罗斯最高学术学位后,作者意识到自己长期以来的职业生涯建立在虚假的智识基础之上。其研究依赖于灵活且不可证伪的理论框架,这些框架通过追求复杂性而非实质内容,充当了掩盖工作缺乏严谨性的防御机制。尽管享有声望,作者却感到被一个推崇晦涩成果胜过实际贡献的体制所困。 作者意识到自己的学术道路是“架错了大楼的梯子”,从而陷入了目标危机。2024年,41岁的他们放弃了既定的职业生涯,转型成为计算语言学领域的一名初学者。这一转变让他们得以拥抱一个“现实说了算”的领域——在那里,代码要么运行正常,要么报错失败,数据能够反驳假设。 作者放弃了被操纵的体制所提供的安全感,转而投向充满不确定性的新路径。如今,他们将可迁移技能和切实的成果置于抽象的赞誉之上。在准备离开俄罗斯之际,作者得出结论:职业上的困难并不等同于价值,这往往只是游戏规则存在缺陷的征兆。

这场 Hacker News 讨论聚焦于一位博主的反思:他花费二十年时间追求学术生涯(主攻社会理论),最终却意识到自己“爬错了梯子”。 讨论帖中的核心主题包括: * **学术界的沉没成本:** 许多评论者分享了他们攻读博士或接受专业培训的个人经历,却在事后发现这些技能缺乏市场价值或无法带来个人满足感。参与者认为,学术界往往更看重智识上的“废话”,而非可证伪、有实际用途的成果。 * **职业与生活:** 讨论中出现了一个核心争议:职业究竟应该是意义的来源,还是仅为支持业余爱好、家庭和个人兴趣而采取的务实手段?一些用户指出,现代的“事业心”往往让人忽视了充实生活的真正目标。 * **对结构的幻灭:** 讨论者指出,年轻人往往在尚未成熟到理解权衡利弊之前,就被迫投身于长期的职业道路。 * **对可证伪性的需求:** 作者和评论者强调,转向软件工程等领域提供了一种令人耳目一新的现实检验:代码要么能运行,要么不能,这种清晰的反馈机制是抽象的学术工作所缺乏的。
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原文

In February 2024, I defended my second dissertation and earned the highest academic degree Russia awards. By June, I knew I wanted out. Out of this kind of research, out of this academic system and out of this country.

Russia has two successive research degrees: the Candidate of Sciences, roughly equivalent to a PhD, and the Doctor of Sciences, a later, higher doctorate. I earned both. You do not need to remember the titles. The point is that I had cleared both major levels of the game before finally admitting that I no longer wanted the life attached to its prize.

This was not an impulsive post-defense crash. The crisis had been building for years -- years spent grinding, adding complexity, and taking all sorts of detours instead of grabbing myself by the balls and admitting that I was climbing a ladder propped against the wrong building.

An academic career is supposedly built around research. The problem with my research was that I could no longer explain, without hiding behind academic vocabulary, what I was actually doing, what my findings were, or whether they were valid at all.

Much of my research began with a large claim about society (e.g., "consumer culture constructs identities") and I then searched texts for language that could illustrate that claim. Because almost any passage could be interpreted that way through a sufficiently flexible framework (and enough imagination), it was difficult to say what evidence would prove the claim wrong.

I know this bothered me on some level. But instead of addressing that, I kept adding one theoretical layer on top of another. Identity, values, ideology, post-modernity; critical discourse analysis, rhetoric, persuasion, functional grammar, genre analysis, sociolinguistics, metapragmatics. At least in my hands, each new framework became another way to support a conclusion I had largely reached in advance. The vocabulary grew more sophisticated; the basic procedure changed much less than I wanted to admit. The methodology remained eclectic, the analysis increasingly esoteric, and the claims difficult to test.

You may never have defended a dissertation or cited Foucault to support a claim. But you may know the move: when a project or career no longer survives a basic question, you respond by making it more elaborate. Complexity becomes a way to postpone the verdict.

What I needed was not more frameworks to make unconstrained interpretations sound more substantial. I needed methods with clearer procedures, evidence requirements, and failure conditions. Continuing as I had was safe. The next move was clear, whereas doing something different(ly) would have made me a beginner.

The system rewarded this work just enough to make it difficult to leave. On paper, I kept progressing. The route to another degree was formal and predictable; submitting my work to more selective international journals, where reviewers could simply reject it, was not. I published articles, but these were in Russian journals where rejection was unlikely. I chose the safe scoreboard I knew how to win.

The painful part was that the credentials I had become so good at earning carried little weight outside Russia -- and I had wanted to leave the country for as long as I could remember. There were real constraints, but much of what kept me there was plain fear. Either way, I stayed.

In the summer of 2024, I knew something had to give. I started questioning everything and discarding what I thought was not working or getting in the way. I burned the bound copy of my second dissertation. I eventually deleted most of the research notes I had accumulated during that period.

In the fall of 2024, at 41, I enrolled in a course in computational linguistics and natural language processing and became a complete beginner. I had no coding experience. I had no idea what a p-value was or why the hell anyone would take the logarithm of a number.

For the past few months, I have been back at work on a project that makes much more sense to me. I don’t yet know whether this will become the right game. But it has one property much of my previous work lacked: reality gets a vote. Code fails. The parsers disagree. And the data can refuse the story I want to tell.

In this project and elsewhere, I am now trying to judge work by what survives outside its own scoreboard: a transferable skill, a finished artifact, a reader, a useful result, an opportunity -- perhaps even a little more freedom.

As I write this, I am looking around an apartment that gets emptier every day. My fiancée and I have been getting rid of our belongings. Yesterday, we booked one-way tickets for a flight that leaves in a few weeks. I don’t know where we will be six months from now.

Twenty years in the wrong game taught me that difficulty is not evidence of value. It only proves that the game is difficult.

Originally published: 2026-08-19

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