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知识的困境：什么样的研究才是”有用”的？

Last week, I attended a theory seminar organized by our college, where I joined professors from the Geography and Planning Department and other doctoral students to discuss several theoretical papers in human geography. Setting aside the specific theories (partly because I didn’t fully grasp them myself…), an intriguing question emerged during the open discussion at the end of the meeting: What constitutes useful knowledge? This question can be further broken down: Useful for whom? How do we evaluate the value of knowledge? Should we only pursue “useful” knowledge? And what does it mean to seek “knowledge for knowledge’s sake”? These questions not only pertain to academic research but are also deeply intertwined with the broader context of our society.

中文

上周参加了学院组织的理论学校，和地理和规划学院老师、其他博士生一起研讨了几篇人文地理领域的理论文献。具体的理论放在一边（当然也是因为我也没太搞懂……），会议末尾的开放讨论环节却引发了一个引人深思的问题：什么是有用的知识？

这个问题可以进一步被分解：知识对谁有用？如何判断知识的价值？我们是否应该只追求“有用”的知识？“为知识而知识”又意味着什么？这些问题不仅关乎学术研究，也与我们整个社会的环境息息相关。

The Dilemma of Knowledge Production

Two years ago, there was a news story about the Stripe founder donating $500 million to establish a research institute for his wife, an assistant professor at Stanford, with plans to recruit 150 researchers. This donation meant she would never have to endure the pain of writing grant applications again!

In many people’s eyes, university research appears to be a stable and respected profession. However, universities do not exist in isolation from society and must face the same tests of the market economy. In companies, we must consider return on investment for our projects, evaluating each one’s ROI and typically pursuing short-term benefits. When this logic infiltrates academia, it can make certain important research extremely difficult to pursue.

With the recent Nobel Prize announcements, some might remember one of last year’s Nobel Prize winners in Physiology/Medicine – Katalin Karikó. She devoted nearly forty years to mRNA research, yet was demoted due to her laboratory’s poor “performance” and repeatedly denied tenure. It wasn’t until the COVID-19 outbreak in 2020, with support from Pfizer, that her team developed the mRNA vaccine that would save millions of lives. Successful stories are always told in retrospect – this historical opportunity transformed Karikó from what others called “the crazy mRNA lady” into a great scientist who persisted in her pursuit and realized her value.

However, not all persistent research will eventually see its day of recognition. Many important research topics are inherently high-risk and might require generations of effort to achieve breakthroughs. But under the current system, research funding tends to favor “safe” projects, and universities, driven by rankings and assessments, tend to pursue quick outputs. This pressure is particularly heavy on young scholars – before securing tenure, they must prove their worth through publication counts and research funding amounts.

A human geography professor mentioned that at a recent university meeting, they said “we need to be bigger, yet smaller; faster, yet slower.” This perfect example of oxymoron aptly summarizes the dilemma facing contemporary academic researchers. I’m not suggesting that universities should be ivory towers detached from reality, or that we should pursue research for research’s sake, knowledge for knowledge’s sake. However, an academic environment overly dominated by market logic will indeed kill off research that requires patience and long-term investment, or limit such research to the hands of a few senior scholars who have already secured stable positions.

知识生产的困境

两年前有这样一则新闻，Stripe创始人为其妻子——一位斯坦福助理教授——捐赠五亿美元建立研究所，计划招募150位科研人员。这笔捐赠让这位教授再也不用遭写项目经费申请的罪了。吃瓜群众们纷纷表示——这样的学术霸总给我来一打好吗！

在很多人眼里，高校研究似乎是一个稳定而受人尊重的职业。然而，高校并非独立于社会之外，同样要面对市场经济的考验。在公司里我们做项目是需要考虑收益率的，每个项目都需要衡量投资回报率，且往往追求短期效益。这种逻辑渗透到学术界后，却让某些重要研究举步维艰。

最近诺贝尔奖颁布，不知道大家还记不记得去年的年诺贝尔生理学/医学类获奖者之一——卡塔林·卡里科(Katalin Karikó)。她潜心研究mRNA近四十年，却因实验室”效益”不佳而被降职，甚至多次被拒绝终身教职。直到2020年新冠疫情爆发，在辉瑞制药的支持下，她的团队开发出拯救千万人生命的mRNA疫苗。成功的故事都是倒叙，有了这一次站在历史舞台上的机会，使得卡塔林从一个其他人口中“疯狂的mRNA女人”，成为了一个坚持自己追求、并实现价值的伟大的科学家。

然而，并非所有执着的研究都能等来认可的那一天。许多重要课题本身就具有高风险性，可能需要几代人的努力才能取得突破。但在当前体制下，科研经费往往倾向于”稳妥”的项目，学校为了评级排名，也倾向于追求快速产出。这种压力对年轻学者尤其沉重——在获得终身教职前，他们必须用论文数量和研究经费额度来证明自己的价值。

有个人文地理的老师说，上次学校开会的时候说“我们要更大、但更小；更快、但更慢”。这个运用矛盾修辞法的完美例句高度概括了当代学术研究者的困境。我并不是认为学校应该是脱离现实的象牙塔，或者为了研究而研究，为了知识而知识(Knowledge for knowledge‘s sake)。但一个过度被市场逻辑统治的学术环境，确实会扼杀那些需要沉下心来做的、有着长期投入的研究，或将这些研究局限于少数已获得稳定地位的资深学者之手。

The Academic Hierarchy of Contempt

Although the dilemmas mentioned above are widespread, the situation varies significantly across different disciplines, with humanities and social sciences being at a greater disadvantage compared to natural sciences. This brings us to an unavoidable issue: some natural scientists, and a portion of the general public, still consider social science to be pseudoscience.

This cognitive disparity has historical roots and is related to how these two fields view the world. Natural science assumes there is only one reality, and research is a process of continuously approaching this “truth” through experiments, emphasizing objectivity, neutrality, reproducibility, and falsifiability. Social science, on the other hand, tends toward relativism, believing that reality is diverse – “there are a thousand Hamlets in a thousand people’s eyes.” Some believe reality cannot exist independently of individuals, while others argue that reality is the result of interaction between the objective world and subjective perception¹.

This difference is even reflected in writing styles. When first learning academic English writing, we’re typically told to use more passive voice, downplaying the researcher’s presence while emphasizing objective facts. For example, we would transform “xxx believes the Earth is round” into “it is believed that the Earth is round” or “experimental results indicate that the Earth is round.” This logic leans toward the natural sciences. However, when you enter a master’s or doctoral program in social sciences, professors will tell you that active voice and the first-person “I” are not only acceptable but encouraged. This is because researchers have their own positionality – our experiences and perceptions influence both research motivations and interpretations. Attempting to obscure this subjectivity with universal truths would be contrary to research ethics.

Disciplines’ different perceptions of how the world is constructed influence their approaches to acquiring knowledge, which can be roughly divided into quantitative and qualitative analysis. In simple terms, quantitative analysis emphasizes testing hypotheses through measurable data, pursuing statistical universality; while qualitative analysis focuses on understanding the meanings and processes behind phenomena through in-depth observation and interviews.

Research methods don’t correspond one-to-one with academic disciplines, but each discipline does have certain tendencies. For instance, social policy, economics, and demography predominantly use quantitative analysis, while sociology, human geography, and anthropology tend to favor qualitative analysis more.

An undeniable reality is that scholars in natural sciences, or social scientists who primarily use quantitative analysis, face fewer questions about the usefulness of their research. In contrast, social scientists conducting qualitative research are often criticized for having small sample sizes, low generalizability, and limited policy implications. On the surface, everyone says there’s no hierarchy among research methods – a good method is one that adequately answers the research question. However, this “whether a cat is black or white, if it catches mice it’s a good cat” argument only holds true if everyone agrees on what constitutes a mouse. When research questions themselves are valued differently, and research outcomes are evaluated based on short-term market logic, how can you say success or failure is merely due to differences in cats’ abilities?

Quantitative analysis begins with developing hypotheses based on existing theories. For example, when analyzing multiple causes of women’s lower income levels using census and socioeconomic data, the factors included in the analysis are often based on findings from previous qualitative research. If studies show that family structure, childcare services, and education levels have an impact, quantitative analysis will then verify the degree of these factors’ influence through modeling, explaining the phenomenon quantitatively through correlations or causal relationships. From this perspective, the two approaches are complementary. If qualitative analysis is criticized for being “criticism for criticism’s sake,” couldn’t quantitative analysis without qualitative input be accused of being “data analysis for data analysis’s sake”?

学科鄙视链

虽然上文谈到的困境是广泛存在的，但在不同学科间的处境却很不平等，人文社科领域比自然科学领域更处于劣势。这就不得不直面一个问题：有一部分自然科学研究者，或者一部分大众仍旧认为社会科学是伪科学。

这种认知差异是有历史渊源的，也和两个领域看待世界的方式有关。自然科学认为现实是唯一的，研究就是通过实验不断接近这个”真相”，强调客观、中立、可重复、可证伪。而社会科学更倾向于相对主义，认为现实是多样的——“一千个人眼中有一千个哈姆莱特”。其中有人认为现实不能脱离个体独立存在，有人认为现实是客观世界和主观认知相互作用的结果¹。

这种差异甚至体现在写作方式上。最初学习学术英文写作时，我们大概率会被告知应该使用更多的被动句式，弱化研究者的存在，而是强调客观事实。例如我们会把“xxx认为地球是圆的”写成“地球被认为是圆的”， 或者“实验研究结果指出地球是圆的”。这个逻辑是偏向自然科学领域的。但当你进入社科领域的硕士或者博士课堂，老师便会告诉你：主动句式和第一人称“我”不仅没有任何问题，还是被鼓励的。因为研究者有着自身的社会位置(Positionality)，我们的经历和认知对于研究动机和解读都是有着影响的，企图用普世的真理去掩盖这些主观性是违背研究伦理的。

学科对于世界构建的认知影响了它们获取知识的途径，这里也可以简单粗暴地分为定量和定性分析。简而言之，定量分析强调通过可测量的数据来检验假设，追求统计意义上的普遍性；而定性分析则致力于通过深入观察和访谈等方式，理解现象背后的意义和过程。

研究方法并不和学科领域一一对应，但是每个学科是有一定的倾向性的，比如社会政策、经济学、人口等领域大多以定量分析为主，而社会学、人文地理、人类学等则做定性分析的更多。

一个难以忽视的现实是，自然科学领域的学者，或者社科领域更多用定量分析的研究者更少地被质疑他们的研究是否有用。对比之下，做定性分析的社科研究者则常常被认为数据量太小、普适性很低、对于政策没有指导意义。表面上大家都说研究方法没有优劣之分，能够充分回答研究问题就是好方法。但这个“黑猫白猫，能抓住耗子就是好猫”论调成立的前提是大家对于耗子的定义是一致的。当研究问题本身就被认为具有不同的重要性，而研究结果的评价也是基于短期的市场逻辑时，你怎么能说成功或失败只是因为猫的能力不同呢？

定量分析的前提是根据现有的理论去提出假说。比如通过人口普查和社会经济数据分析造成女性收入偏低的多重原因，哪些影响因子会被引入到分析中往往是基于之前的定性分析的发现。如果研究表明家庭结构、育儿服务、教育水平等有影响，那么定量分析就会通过模型方式去验证这些因子的影响程度，用相关性或者因果关系去定量地解释这个现象。从这个角度说，二者是相辅相成的。如果说定性分析被抨击是“为了批判而批判”，那么没有了定性分析的定量是不是能被说成是“为了数据分析而数据分析”呢？

Conclusion

During the discussion, I pointed out that many journal articles end with a section on practical implications, but these often lack operability or are overly broad, seemingly written just for the sake of writing. Does their ubiquitous presence suggest that every study is expected to provide specific solutions?

One professor jokingly suggested that perhaps some people just don’t know how to write conclusions, while another pointed out that social science research is often criticized for “critique without offering solutions.” But does criticism itself lack value (setting aside criticism for criticism’s sake)? Or is there no value in comprehensively describing a phenomenon? When we attempt to dismiss all theoretical research with a simple “so what,” what kind of societal values are we defending?

This is an era of exponential information growth, with fewer unexplored territories than hundreds of years ago. Many people jokingly call themselves “academic laborers” or “academic paper patchworkers.” When we criticize this era for lacking innovation, suggesting that current research merely applies new technology to old problems or transplants research from one region to another, shouldn’t we also recognize that academic research, as a profession, faces similar challenges to other sectors of society?

If we need to be “faster, yet slower,” then all types of research deserve support. Whether it’s projects pursuing rapid industrialization or research aimed at slowly exploring our world, all are worthy of attention. Overemphasizing “useful knowledge” actually allows pragmatism and market logic to hijack the knowledge production process.

At the end of the discussion, one professor shared a vivid metaphor: doing research is like putting a letter in a bottle and casting it into the sea. How this letter will be interpreted and used in the future, what impact it will have on the world – all of this is beyond the researcher’s control, because knowledge itself has its own life.

结语

我在讨论的时候提出，在很多期刊文章结尾都会看到一个对于实践的指导章节，但很多写的并没有多少实操性或者过于广泛，多少存在一些为了写而写的嫌疑。他们的普遍存在是否是因为每项研究都被期望给出具体的解决方案？

一个老师打趣说可能那是因为有些人不会写结论（毒舌学者），另一个老师则提出，社科研究常被质疑“只有批判，没有解决方案(critique without offering solutions)”。但是，批判本身没有价值吗（抛开为了批判而批判）？或者能够全面地描述一个现象没有价值吗？当我们企图用一句简单的“所以呢(so what)”去抨击所有的理论研究的时候，我们又成了怎样的社会价值的守护者？

这是一个信息量指数增长的时代，比起几百年前，未被探究的领域越来越少。许多人戏称自己为“学术民工”或者“知网的搬运工”。当我们批评这个时代缺乏创新，认为现有研究不过是把新技术应用于老问题、把一个区域的研究搬移到另一个角落时，我们是否也应该看到，学术研究作为一种职业，正面临着与社会其他行业相似的困境？

如果说我们需要”更快，但更慢”，那么各种类型的研究都应该得到支持。无论是追求快速产业化的项目，还是希望缓慢探究这个世界的研究，都值得被重视。过度强调”有用的知识”，其实是让实用主义和市场逻辑绑架了知识的生产过程。

讨论末尾时，有一位老师说的一个比喻我觉得很生动：他说做研究就像把一封信装进漂流瓶，然后投入海中。这封信未来会如何被解读和运用，会对世界产生怎样的影响，其实都已经超出了研究者的掌控——因为知识本身有着自己的生命。

Footnote:

¹ Although initially there was a significant distinction between realism and relativism, more classifications emerged during their development, which can be arranged on a spectrum – with single reality at one end and multiple realities at the other.