Why Most Academic Research is Fake
In this essay, I will argue that most academic research is fake. The modern academy is not a reliable source of knowledge. Instead, it produces the pretense of knowledge.
Academic research can be fake in different ways. It can simply be false. It can be emotionally manipulative propaganda masquerading as knowledge. It can be irrelevant or meaningless.
These are the main causes of fake research:
- Ideological Bias
- Perverse Incentives
- Social Circularity
- Naive/Fake Empiricism
I’ll describe each and explain how it causes fake research.
Ideological bias is a huge problem in the academy. The vast majority of professors are left-wing, so the academy has a big political bias. Certain fields, such as “gender studies” and “ethnic studies” are dedicated entirely and unapologetically to left-wing political advocacy. Other fields, such as sociology and communications, are mostly advocacy and blur the line between inquiry and advocacy. Advocacy research is propaganda masquerading as knowledge.
Ideological bias affects research in the following ways:
- Ideological assumptions are part of the conceptual framework of research programs.
- Researchers are motivated by an ideological agenda. They act as advocates, rather than truth-seekers.
- Published research is filtered through the ideological biases of reviewers and publishers.
- People are selected for academic positions based on their agreement with ideology
These factors interact, of course.
The “blank slate” view of human nature is an important ideological assumption that affects most social science research. It is assumed that any difference in outcomes between demographics or even individuals must be due to some difference in their environments.
This assumption is often seen in the interpretation of statistics. For example, a social scientist might observe that crime and poverty are correlated, and infer that poverty causes crime. This ignores the possibility that both crime and poverty are caused by genetic factors.
Dogmatic framing assumptions render most social science research dubious.
The blank slate view of human nature is typically associated with a left-wing “social justice” agenda. Social justice advocates generally interpret observed differences between demographics as evidence of social injustice — at least when it suits their political agenda to do so. Genetic explanations are dismissed on the grounds that they are “hate speech”.
This is dogmatic and circular. It starts with the dogmatic assumption that systemic racism and sexism exist. Race and sex differences in outcomes are then “explained” as due to systemic racism and sexism. Alternative explanations, such as genetic explanations, are rejected on the grounds that they are “hate speech” used to justify systemic racism and sexism.
This circular reasoning protects the social justice ideology from falsification. Of course, this is dishonest advocacy, not science.
The moralistic fallacy is another type of ideological bias, which affects many fields. It is the tacit assumption that nature conforms to our moral values, or in other words that nature is “good”. The “noble savage” myth is one instance of this fallacy. The noble human, noble hominid and noble chimp are other examples.
The moralistic fallacy is often found in biology, especially in the interpretation of animal behavior. Biologists have a tendency to see altruism where it does not exist. It is also common in anthropology. Margaret Mead’s Coming of Age in Samoa is a well-known example.
Academic research does not serve the need of society for knowledge. Instead, it mostly serves the need of academics to justify their existence.
Knowledge comes from human creativity. The generation of knowledge cannot be reduced to a routine. But the modern academy is based on the idea that professors should do research as a routine activity, and routinely publish their results. The “publish or perish” incentive produces research for the sake of research, not for the sake of expanding knowledge.
Research programs succeed or fail based on their ability to generate papers and theses, not knowledge. To succeed, they must generate lots of little problems for academics to solve. Academic research is mostly about solving little fake problems. Big important problems tend to be ignored and/or settled by assumption.
This process generates the pretense of knowledge, in the form of a “vast literature”. The vast literature is then used to justify the importance of the field. This is another circularity. A research field is its own justification.
The academic vanity press exists to satisfy the demand for publication. Most journals publish research that is produced and consumed exclusively by academics. Not only do journals get free material from academic research, they often charge academics a fee to be published. Academic researchers pay for validation with labor and publication fees.
Publishing creates the pretense that research is meaningful, because it seems to be meeting a demand, but in fact the demand is coming from the writers, not the readers. Academics want to publish their research far more than anyone else wants to read it.
The need to acquire funding also creates incentives that are not aligned with the pursuit of knowledge. This affects different fields in different ways. In some fields, such as medicine, it may distort research to favor the economic interests of corporations, such as drug companies. In other fields, it imposes political correctness and protects status quo beliefs.
Credentials and tenure also create perverse incentives. They are granted by the academy as an institution, based on the judgment of already credentialed and tenured academics. There is an obvious circularity involved. To get credentials, you must get the support of those with credentials. To get tenure, you must get the support of those with tenure.
This creates a conformity bias. To get ahead, students and professors must conform to the beliefs of those above them in the academic hierarchy. After many years, a professor may get tenure, and this supposedly liberates him to speak his mind. By that point in his career, however, he will be deeply invested in a body of work. He will not find it easy to publicly change his opinions. Thus, the hierarchical nature of academia tends to maintain the status quo.
There is a strong incentive to confirm existing research, rather than challenge it. A lot of research is just the pointless extension of existing research.
The easiest way to get a paper published is to extend an existing research paper by a well-connected professor. The professor will of course be delighted that someone bothered to read and extend his work. The more his work is cited, the more it will be treated as credible and important, and the more status he will have within the academy. He or someone within his research program will likely be chosen to review the paper, and naturally there is a strong bias toward “friendly” research and against “unfriendly” research. Even if the reviewer tries to be impartial, it is easier to understand and agree with someone who has the same beliefs.
So, academic research tends to grow into a dense web of (mostly useless) research that supports other research.
Again, note the circularity. Attempts to overturn important nodes in this network are met with hostility by researchers who are invested in the existing network as a source of status. That’s why it often takes a generation or more to overturn a stupid academic field, such as Freudian psychology. Once in existence, those networks are self-justifying and self-perpetuating.
The academy isn’t purely conformist. There are debates over questions of truth. But such debates are also power struggles. Academic research is best understood as a social game that includes both cooperation and competition. In that game, the truth is a means to an end, not an end in itself.
Academia is circular. Professors confer academic credentials, thereby creating new professors. Professors grant tenure to other academics. Professors decide what constitutes good research. Academic research is almost exclusively written for and read by academics. This circularity makes academic research into a social game that is detached from reality.
Academic research often has a special language of jargon, notations and tropes. It also typically has a set of canonical texts that are treated almost as religious scriptures. To participate in a research field, one must learn its special language and its sacred texts. This special knowledge is used to signal in-group status and exclude outsiders. Academic language often resembles the arcane incantations of a religious cult, because that’s essentially what it is. A research field is like a little cult.
Obscurantism protects academic research from criticism by outsiders, because the insiders can always claim that an outsider critic is lacking the special knowledge necessary to understand the field. That is why academic fields as bizarre and useless as Marxist social theory and Freudian psychology can exist for decades.
A research program often begins as a sincere attempt to understand reality, but it tends to degenerate into a vacuous circle as it expands. It becomes a language game in which the participants are just signaling to each other. The language game is detached from reality and self-referential. This happens even in supposedly empirical fields, because empirical problems and solutions are defined by researchers, not by nature.
Research can be fake because it is irrelevant, regardless of its truth. Most academic research is fake in that way. Instead of generating knowledge that is useful to humanity in general, the academy generates a pretense of knowledge that is useful to the academy. The huge volume of published material makes it seem that the academy is generating knowledge. It justifies the existence of the academy. It justifies its public funding. It justifies the careers and status of professors. But this justification is circular.
Academics invent problems to work on, agree with each other that these problems are important, generate solutions to their contrived problems, evaluate whether they have solved the problems, and award each other status-tokens for success in this game.
Peer review is one of the processes that supposedly makes academic research reliable, but peer review is circular and limited. Peer review can catch random errors, but it does not correct systematic errors caused by ideological biases or biases of human intuition. Instead of being corrected by peer review, errors can be amplified and perpetuated by social circularity. Errors that support the general beliefs of a field will not only pass peer review; they will often be promoted as important findings.
Most empirical research is dubious, because of biases built into the research and publication process.
The social sciences have adopted a form of empirical research that consists of looking for statistically significant correlations between variables in a complex system. This type of empiricism is of dubious value for understanding reality, but it lends itself to the mass production of research findings, and so it is popular in certain fields. There are some big problems with this type of research.
The naive application of frequentist statistics is one of the problems. The notions of “statistical significance” and “hypothesis testing” are problematic to begin with, and they are much more problematic in academic research. Statistical significance is perspective dependent. A result that is statistically significant from the researcher’s perspective might not be statistically significant from the perspective of a journal reader. In fact, the notion of statistical significance becomes meaningless in this context.
For example, journals have a bias in favor of “positive” results (rejecting the null hypothesis) and against “negative” results (accepting the null hypothesis). This creates a statistical bias that invalidates the statistical significance of results that have been published in a journal. As a consequence, academic literature is full of false positives that cannot be replicated. The same problem exists for ideological biases. Once “statistically significant” results have been filtered through an ideological publication bias, they lose their statistical significance.
Empirical research can also be faked and misrepresented in various ways. P-hacking is an example of how researchers can statistically hack the data to get what they want. Such biases are largely responsible for the replication crisis in academic research.
The entire frequentist paradigm in statistics should be discarded, but that’s a topic for another essay.
Another common problem with empirical research is relying on intuition and ideology to infer causation, without considering alternative explanations. For example, a statistical association between crime and poverty might be presented as “obvious” evidence that poverty causes crime, without considering the alternative explanation that genes might affect both crime and poverty.
Naive empiricism is often associated with a tacit appeal to authority: the ultimate authority of nature itself. Empirical results are often presented as indisputable facts. This is naive, because empiricism is not free of assumptions and biases. Observation depends on theory, and all statistical interpretations involve assumptions and biases. Empirical research is not a direct transfer of knowledge from nature to our minds.
I’m not saying that data should be ignored. Large data sets collected by reliable sources are extremely valuable as evidence. Simple statistics calculated on such data, without cherry-picking, can be used to evaluate theories. Statistical relationships that have been replicated many times in many contexts are a good form of evidence. So are direct experiments if they can be replicated. Be empirical, but don’t be naive about empiricism.
Not all academic research is fake, but the overall academic enterprise is a fraud. The appropriate attitude toward academic research is extreme skepticism. Don’t trust academic experts. Don’t accept academic citations as arguments. If you can’t verify academic research for yourself, ignore it. The academy is not a trustworthy source of knowledge.