How the Sciences Became Bullshit: Academic and Replication Crises
The decline in scientific productivity is due to complex social and technical factors that have resulted in a feminized academia and 'play-it-safe' research
"The Modern Sciences are a Shit Show"
This statement is a controversial public statement in academia and the sciences. In private, however, most academics will be quietly nodding their heads in agreement. The sciences (and academia as a whole) are hot dumpster fires right now. Few people can speak about it intelligently either. Academics that recognize the problem find it difficult to speak out as they become subjects of their own derision. Simultaneously, university and national lab administrations don’t appreciate uppity faculty or researchers. Money flows from the political and media classes to scientists, not the other way around… and those classes don’t like it when their researchers loudly shout about how the sciences are going to hell.
Perverse incentives have led to god awful research practices while a reduction of return-on-investment has dramatically increased costs and slowed innovation.
Breakthrough Disruptive Innovation: a radical new development that produces social or industrial products that alter quality of life or lifestyles.
Iterative Research Results: research based on previous work that produces a minimal effect on economic or social development and does not significantly alter quality of life or lifestyles.
The End of Disruptive Innovation
At the beginning of the industrial revolution, the first coal powered steam-engine was implemented in the 18th century to pump water out of a coal mine in Britain. Doing so required an understanding of fundamental forces that had only recently been created in physics and engineering: The concept of a vacuum, the concept of pressure, methods for creating a vacuum and a pressurized cylinder. This brilliant innovation allowed miners to mine further and deeper into the coal seam than previously possible. The first important question posed is this: why was the first implementation of a steam engine at a coal mine?
Efficiency. Calculations performed at the time, and later, indicated the net efficiency of this first-of-its kind disruptive innovation was a grand total of 0.7%. That is, for every 500 BTUs of energy input, 1.4 BTUs of energy were actually converted to useful kinetic action pumping water. The mouth of a coal mine was the only place in the world where fuel to power the engine was cheaper than a dozen horses doing it instead. The industrial revolution not only waited for us to understand the concepts of vacuum and cylinder pressure, it waited for a time and place where it would be worth it to begin commercial innovation.
Engines got more efficient pretty quickly over the next 300 years due to disruptive improvements in metallurgy, mechanical design, precision engineering, and digital controllers and modeling.
In the 21st century, the efficiency of a modern steam turbine (same principle, but to generate electricity) is in the range of 50%. That’s about 80x higher than the first steam engine. Brilliant innovations took place to make that happen. Increased energy efficiencies made it economical to ship coal from the coal mine to first steam locomotives, then coal power plants. Atomic energy, solar, the electric grid and the internet all came into existence because some one finally found a good spot to test out a coal-powered steam engine back in 1702.
It was the dramatic improvements in efficiency and continued disruptive innovations that created the modern world; not a Hegelian march toward scientific progress and development, but millions of scientists over generations developing disruptive ideas.
Atomic energy and the internal combustion engine. The telegraphs and radar, steam locomotives and advanced smelting, micro-transistors and digital communications, metallurgical flotation, genetic engineering and the Green Revolution. One will note something about those innovations: they took place between the years 1800 and 2000. The genetically engineered green revolution that fed the world occurred in the 1970s.
Over the last half-century, research has become less innovative. Not new breakthroughs, but iterations on old ideas. Not a new types of engine, but smaller more efficient engines. Not a new type of battery or material, but a slightly improved metallurgical method. Not disruptive innovation; scientific iteration. The wave we’ve been riding for the last 300 years has slowed dramatically.
Research has evolved; it is less about changing the world and more about retaining government grant funding. Scholars aren’t building a future any more, they’re preserving the present. Over the last 30 to 50 years there has been a fundamental change in the nature of the sciences. Academia has ceased to be a place for the eccentric autist delving deep in the esoteric limits of human knowledge and become a government funded program that exists to justify itself existing.
The perfect confluence of conditions that led to the industrial revolution created a window that’s now closing. Human development could well see a stagnant technological future far from the idealized visions of Heinlein or Asimov.
The Replication Crisis, Destruction of the Sciences
The Replication Crisis is a tacitly acknowledged disaster. It’s not often spoken of in mixed company because around half of scholars are aware that they’ve contributed to the problem. The issue is that retaining funding and employment requires results, even if some of those results are questionable.
Briefly, the replication crisis was the result of a study published in 2016 by tracking the work of over 1500 scholars. The study described the absolute state of the modern sciences: the majority of published research results failed replication. That is to say, when the same experiment was performed in the same way by another group of researchers, the results were different. The results therefore failed replication.
Nearly 70% of all published scientific articles examined across numerous disciplines failed replication. The indication is that the majority of scientifically produced academic articles are either not true or only tacitly true and difficult to verify. Replication consistency was different between disciplines. Among the “hard” sciences, the replication failure rate was around 50%, while among the “soft” sciences like sociology, the replication failure rate exceeded 85%.
What that effectively means is that, just because some one can cite the results of a scientific experiment, does not mean those results are true. There are multiple reasons for this crisis. One is that scientists are disincentivized from performing replication studies of their own. Far better to produce novel results than confirm results another lab has already produced. Of course, that means bad data is rarely checked to make sure it’s true. When it is checked, entire academic careers can crack apart. The publication incentives have produced mountains of academic papers as scholars attempt to one-up each other in producing novelty while failing to verify the first principles (previous publications) they’re working from.
A lot of time and money has been wasted trying to produce new results based on the false premises of inaccurate publications.
To the individual, these incentives are abstract, but to the sciences as a whole, they’re disastrous. The modern sciences have gone so far up their own asses that their results are bullshit. Many scholars aren’t properly honest, and they’re prone to miscalculation and exaggeration. We live at a time where “believe in the science” is a religious conviction; an act of faith because the sciences do not believe in themselves.
There are a number of fundamental psychological, sociological and technical challenges contributing to the ongoing and worsening crisis in scientific research in the 21st century.
Diminishing Return on Investment
It’s clearly observable that the number of researchers/institutions required to develop a single breakthrough innovation is growing. If 50 years ago it took 10 scholars to produce radical innovation, then today it requires 80. The return on investment is shrinking with each passing year. The pressure to produce novel research remains high, but the capacity of an individual scholar to actually do so appears to diminish over time. J. Huebner noted this in a paper discussing technological forecasting, a deterioration in innovative events per year is shown below.
Technological Forecasting & Social Change, J. Huebner: advances per year by population
A reason for stagnation is that, with regards to research, the “low-hanging-fruit” have already been picked. Relatively simple and easily-observable phenomena were the first catalogued: metallurgical chemistry, gravity, electromagnetism. These phenomena can be studied with simple tools and while using (relatively) basic mathematics. Delving into the realm of quantum mechanics requires a leap in technical complexity for both the tools and mathematics.
Ultimately, there appears to be a state of diminishing returns in all technological sciences as they mature. Biology as an emergent system required trial and error to produce useful data. Thus, it took longer for the biological sciences to mature.
More mature disciplines require more time, resources and scholarly energy is to produce the next development. At each level, producing new novel results gets harder. Many modern “innovations” are built on ideas and scholarly publications that existed more than 25 years ago. Even the latest digital advent, machine-learning models, sits atop systems designed prior to the year 2000 (though running on faster hardware).
Due to diminishing returns, the sciences have become iterative rather than innovative. As the low-hanging fruit for innovation has all been plucked, developing innovative breakthroughs became unlikely even for brilliant laboratories. Thus the rate of development per-capita has slowed. Stagnation has been masked by a continual increase in the number of scholars, but a civilization of scientists can’t function without tradesmen and carpenters.
There are still breakthrough innovations, but the number of breakthroughs per scholar is deteriorating even as the total number of scholars continues to rise.
Trends have shown a declining ratio of patents and breakthrough papers to the number of researchers required to achieve them since the 1940s. This trend was first noted by Machlup in 1962 and has continued across all disciplines. For every major success of the sciences, future research must be conducted on more difficult and narrower topics. It is estimated that the equivalent cost for discovering penicillin was around $20,000 (inflation-equivalent) while new pharmaceuticals cost hundreds of millions to enter the marketplace. As individual fields are better understood, research topics become narrower, ask more difficult questions and become more expensive.
Adding more researchers has diminishing returns as once the brilliant scholars are all working, the pool can only expand to the B-tier and C-tier scholars. In addition to simple diminishing returns, however, scientific research and academia have far larger problems. The cost and size of research teams to maintain the same rate of development can be shouldered. The collapse of scientific research into bullshit can’t.
The Bureaucratization of Research Grants: Publish or Perish
A paper was published on the game theory of academic publication by Besancenot and Vranceanu: To a non-expert managerial bureaucrat, number of publications and citations is an easier barometer to measure than quality of research. Thus, scholars are incentivized to publish minor research as quickly as possible rather than dedicate years (or decades) to innovative breakthrough research. The incentive is to perform simple iterative research that can be done quickly and justify publication. The rewards of breakthrough innovation are high, but the probability of advanced research producing results remains low: hence iteration is preferred.
Lower-skilled scholars know how they game is played. They likewise publish as quickly as possible to maximize total publications. Therefore, even highly skilled scholars are incentivized to perform minimalist research to pump out papers even more quickly. The goal isn’t to do better research, it’s to publish more papers; meaning minimal focus on long-term breakthroughs. Scholarly research has become an arms race and the result is an enormous amount of literature with little substance.
Academic journals receive gigantic piles of potential academic articles. The (mostly volunteer) editors are asked to review far more papers than they can handle. Thus, research will often be published in significant academic journals without having gone through true peer review… but it doesn’t matter, because the scholar has now another citation to their name. When applying for a faculty position, that’ll be noted as a positive regardless of the quality of the work. Sabine on youtube has reviewed a number of these BS articles that have shown up as academic publications.
With India and China now entering the fray, maintaining even fewer academic scruples than Western scholars, the glut of scientific-BS has become entirely unmanageable. Catching the attention of the media with an outlier headline is more likely to land you a job than performing a dozen critical replication studies.
In short, the optimal investigation is low-effort research that will return sufficient data to justify publication, but little more: bullshit research.
There are tricks that academics and scholars use to maximize publication likelihood and status. All of them require an understanding of statistics or academia to spot:
Artificial H-index inflation. “H-index”, is a metric used by bureaucrats to identify the quality of a scholar. The index may be inflated by citing your friends papers even if they’re irrelevant to the topic and having them do the same to yours. Indian and Chinese scholars have figured out that by citing one another’s publications to excess, they can artificially raise their H-indices.
Cut the paper into parts. Why publish 1 high quality paper, when you can break it into 3 or 4 lesser papers? Additionally, the papers can reference one another. So now you have increased both your visible literature output, and the number of citations you’ve received by citing your own work. What you haven’t done is improved the quality of academic scholarship.
P-hack your data. Common among the social sciences, these are statistical techniques to create ‘valid’ results from faulty data. A valid result in the sciences generally requires a confidence-interval of at least 95% (that is, there’s only a 5% likelihood that such results occurred randomly). To publish, you need need a good confidence interval. Scholars can: a) take data across time until they hit that value and then immediately stop taking data (lest they lose that critical confidence interval), or b) take random bulk data and look for random cross-correlations that meet the 95% confidence threshold. Then publish those as if that specific correlation was the target of study all along (psych/sociology types do this a lot).
False promotion of novelty. In high-impact journals, novelty is often required. That’s one reason replication studies are so unpopular. Rather than actually performing novel research (that would be risky) scientists will just claim novelty in their research. “Here’s a novel protein that’s never been made before” while that may be true, the scholar is certainly aware that it’s just one of a large family of proteins the production technique for which is well understood. That specific one hasn’t been made before though. At least not in publication. Probably.
Pay for Publications. There are many scientific journals that will gladly publish half-baked research for a fee. They’ll claim that the results are peer-reviewed but get very cagey about who exactly those peer-reviewers are. Paid publications are a great way to pay-to-win the scientific scholar game by pumping up your numbers with whatever garbage you feel like putting out.
Outright Data falsification. If you can’t be bothered to come up with good data, just make some up! Apparently this has been happening more than people thought. Upwards of 30% of neuroscience publications, according to a 2023 article in Science, contain falsified data. New tools have allowed individuals to use AI to examine scientific articles in-bulk. The results are appalling for the natural sciences, and it’s probably going to lead to a slow (but very long-term) cultural backlash to the cushy positions offered professors. As few people perform replication studies (not novel enough, see above), it’s been easy to get away with falsified data for decades. Only the most headline publications are likely to be checked, so as long as you’re just doing iterative research, that hasn’t been much of a risk until now. This video is particularly poignant on the widespread nature of academic fraud as described by the youtuber Sabine Hossenfelder.
Academia is an orthodox church where adhering to its theological dogma and publishing frequently is rewarded. Venturing forth to uncover new corners of the cosmos is punished, as doing so takes time and produces few results on paper; results not valued by an unskilled bureaucratic Dean of Faculty Affairs. The goal of most modern academics is to maintain a position of economic and cultural relevance… They’re not incentivized to perform harrowing ground-breaking research. Gone are the days of social rejection, crazy ideas and misunderstood genius. Academia has been sanitized by its own incentive structure. The young and brilliant are aware that this isn’t a place for them to forge a new path. Which brings us to our next point…
The Feminization of Academia: Bureaucratized Bloat
has written a pair of brilliant articles on this topic specifically[Academia is Women’s Work and Crumbling of the DEIvory Tower]. has a similar piece [The Great Feminization of the American University]. Finally, the piece [Why aren't we talking about the real reason male college enrollment is dropping?] by , is highly relevant here. I would recommend examining them, but will provide a summary.The academic system no longer serves the needs of male students in most cases. Outside specific STEM fields, the academic system is generally run by a majority female administrative staff, with a majority female bureaucracy and a majority female faculty in the interests of a majority female student body.
And the consequences, Mac Donald argues, are troubling. “Female students and administrators often exist in a co-dependent relationship, united by the concepts of victim identity and of trauma,” she writes. “For university females, there is not, apparently, strength in numbers. The more females’ ranks increase, the more we hear about a mass nervous breakdown on campus.”
Excerpt from The Great Feminiazation of American University
The (average) female psychological incentive is status-seeking rather than truth-seeking. While the occasional female physicist may be brilliant, the majority of those with academic accolades aren’t. They’re not there to perform cutting-edge research, rather many went into academia for the status it represented, a cultural hold-over. Competition for status via female dramatics encourage bureaucracy growth. The bureaucracy bloats from what is initially required for conflict resolution between traditional autistic scholars. Now it’s also needed for conflict resolution between female faculty and male-female faculty disputes.
… and once you have a big bureaucracy it starts growing to justify itself.
Not only does the university need a Dean and Chancellor, it also now needs an assistant-dean-of-faculty-affairs to oversee the department-dean-of-diversity-and-equity to maintain a balance between an angry member of the faculty and the departmental-laboratory-oversight-director. Universities spend hundreds of thousands of dollars on positions like this.
Research institutions have crossed a threshold where women now make up the majority of academics in most subjects, and the significant majority of graduates. This has caused fundamental changes in the nature of academia and scientific research. Academia has mostly become a feminine institution driven by feminine incentives. A desire to fit-in, a desire for a consistent paycheck, and a desire to maintain the existing cultural paradigm at the expense of revolutionary research.
For every 1% increase in the proportion of women in the student body, 1.7 fewer men applied. One more woman applying was a greater deterrent than $1000 in extra tuition!
Excerpt from Why aren't we talking about the real reason male college enrollment is dropping?
The result has been a male-flight from academic positions, universities, and similar institutions. Academia has seen an abandonment of results-driven research in favor of status-driven hierarchies. It was noted in the essay Academia is Women’s Work that once a social institution gains the status of “women’s work” men generally don’t want to be involved in it any more. This occurrence has happened to psychology, sociology, nursing, and other disciplines. Evidence suggests that it tends to occur when an institution becomes roughly 60% female… after which over the next decade or two it often becomes over 85% female or more.
Male workspaces are dominated by fierce competition while female workspaces are generally dominated by consensus. The status afforded a particular vocation is gendered as competitive vocations confer a higher status. Masculine disciplines retain status as a byproduct of being culturally masculine, not due to the discipline itself. Thus, academia is attaining the reputation of a low-status vocation with pay structures to match. Consider the difference between the austere status of a professor of psychology in 1920 and the public vision of an average psych professor now, 100 years later: a wise old man with a pipe and a beard vs. a late-30’s woman in a hall lit by cheap fluorescent lights.
Outside the occasional hard science field, men are now generally disinterested. Of the remaining STEM fields that are majority male, you can guess that university leaders are not treasuring the researchers. Instead, even more propaganda and DEI programs are added to “get more women into chemistry and mathematics.”
Over the long-term, DEI efforts have generally been successful. Young men don’t want to be in an institution that doesn’t want them and derides their competition and hard work. Thus even the hard STEM settings are accruing social baggage. Even interested autists are disinclined to attendance. Universities as a whole have become decidedly feminine institutions in the public eye.
Men are exiting: Reduced applications, reduced participation, and a reduced desire to adhere to its strict socially enforced rules. Young men are taking their competitive and truth-seeking natures with them as they exit. The American Universities are slowly transforming into finishing-schools; pillars to confer social status rather than competency.
All of that is leading to further technical and innovative stagnation. Men and women simply behave differently in the sciences with regards to radical innovation as shown by the Nobel prize gender gap.
Bullshit Research and Bullshit Degrees
There once was a time where having a Bachelor’s degree would land you a reasonable job. Those days are long over. We live in a time where having a Masters degree or a PhD nets you the same consideration that a bachelor’s degree once did. Those individuals who have already gotten their degree are often subject to the sunk-cost fallacy and decide the best way forward is through. They go on to get an MS, and then a PhD. There are a lot of people with PhDs running around who shouldn’t have needed PhDs merely to seek employment.
There was a time in the 80s and 90s where Universities would hire faculty who only had an MS. There’s so many PhDs running around now though, that requiring one is entirely reasonable on behalf of the bureaucrats that actually manage those things. More qualifications must mean that it’s a better candidate, right?
According to an article by Forbes, there are now more people with PhD’s than ever before. Additionally, the number of scientists per capita has increased dramatically while simultaneously the return-on-investment for innovation has decreased dramatically. Unesco has an estimate of scientists-per-capita from 1996 to 2018 and the results are striking.
All of these new academics seeking PhDs has created a lot of research glut. Some graduate students even self-fund (once an unheard of vanity project) and many consume institutional research dollars from NGOs, Charities, and government agencies. Most MS degrees and nearly all PhDs require that at some point the candidate publish at least one scientific paper. This creates a further glut in the publication process. Students just trying to get their damn degree so they can get a job now publish novel results in high-impact journals and unashamedly do so with shoddy data. They care more about the slip of paper indicating employability than they care about the quality of their austere scientific publication.
Hence the replication crisis is that much worse. Institutions have soaked up public funds so every one can “go to college” to get their BS. Now, to get noticed, an MS is needed. That means more research projects. Hopefully with that MS, they can go out into the workforce and get one of those bullshit jobs as described here on youtube.
DEI in Academia and National Laboratories
Bullshit research. Replication crisis. A glut of new researchers. A status-seeking academia where ideas that rock the boat are highly disincentivized. It’s amazing that the sciences are doing as well as they are.
So let’s discuss Diversity Equity and Inclusion (DEI): How to discriminate against your most productive demographics.
Most universities provide trainings to their hiring committees to clarify to committees that if they hire some one, a significant criteria should be that the candidate isn’t a white man. There are so many clear instances of this that it isn’t necessary to cite, but here’s a citation from the University of Colorado Boulder anyway.
Then, in addition to career suppression, there’s the fact that a lot of white guys are well aware of it. The aforementioned Forbes Article states:
The demography of doctoral degree recipients has changed considerably over the years. For example,
Women earned 47% of all research doctorates conferred in 2022, a 10 percentage point increase from 1992 but only a 1.7 percentage point increase since 2002.
The number of white recipients has declined from 26,982 in 2012 to 26,879 in 2022.
In contrast, nonwhite recipients have increased over that same 10-year period, with Blacks/AfricanAmericans up 34%, Hispanic/Latinos increasing 50.8%, Asians up 12.6%, and recipients identifying as more than one race increasing 53.7%.
While the number of U.S, citizens and permanent residents earning doctorates increased by 7.1% between 2012 and 2022, the number of doctoral recipients who held temporary visas during their graduate studies increased by more than four times that rate (32.8%). As a result, temporary visa holders comprised 34% of doctoral recipients in 2022, up from 29% ten years earlier.
While the number of people with PhDs has grown dramatically, the number of white people (especially white men) attaining a PhD has decreased. White men have a much higher bar-of-entry to engage in the academic process than a disabled-black-intergender-gay-Muslim. Nearly a third of those who attain post-graduate education in the United States are non-citizens.
White men know they are not wanted in academia, and many are leaving. National laboratories and research institutes are staffed by HR executives who despise white men and are looking for any excuse not-to-hire-one. I’ve been informed as such in person by individuals who work at such institutions. To paraphrase a source who shall remain anonymous for the sake of his own employment:
It’s crazy man, if we get one [a white] guy that we want to hire, we have to fight like hell to get him into the position. It’s really hard to push that through HR.
-Anonymous employee at a national institution
New DEI hires are well aware of how the game works and how to play it. Many are more interested in a US visa than doing good research. It’s notable that many Chinese and Indian scholars will shamelessly inflate their H-indices through cross-citation. Many foreign scholars will gladly P-hack data. Many scholars simply falsify data. Executive deans will be hired because they’re qualified black women, not because they have the slightest idea how to do the job. The DEIvory Tower article discusses that problem in specific.
Competent dedicated scholars are exiting the sciences because they perform data analysis for a living. The analysis suggests that their likelihood of becoming employed doing what they love is far lower than their probability of being told to get lost due to their race. Even if hired, their probability of performing ground-breaking research is lower than their probability of getting caught up in race-baiting drama initiated by a midwit manager at a public institution.
Even working at institutions like this can become detrimental to ones career. The hard sciences are partially insulated, but there are nearly always two or three faculty members with lawsuits against their institution at any given time: discrimination, racism, sexism, pick your poison.
Academia is propped up by government funding that continues out of sheer inertia. DEI has transformed the national science foundation and other institutions into hollowed out shells. Funding favors vanity projects like exploring the social implications of non-normative gender instead of actually developing technical innovation. People are done.
Over the last few decades a pestilential symbiosis has formed between the populations flooding into Western countries from the third world and the West’s homegrown managerial class. Managerialists like telling people what to do (and what not to do), and they also like taking things that aren’t theirs. Nationalization, expropriation, taxation, and other forms of legalized theft (such as the compliance costs imposed to deal with unnecessary regulations, and the consultancy grifts that arise from this) are their economic bread and butter. The managerialists long ago discovered that the populations of the global south are generally quite a bit more docile than white people: they might sometimes be more inclined to the kind of petty crime that emerges from poor impulse control and low intelligence, but they’re a lot less likely to demand that their rights to speech, property, and self-defence be respected, because they come from cultures in which they’re accustomed to the village elders or the Imam or the Brahmin or the Caudillo or whoever telling them what to do, and doing it, no questions asked. The brown and black people, meanwhile, are quite happy to become client groups in exchange for ethnic set-asides and various forms of wealth transfer ... which are obtained almost entirely at the expense of white men.
Excerpt from The WHIMS of Mars by
Disillusioned Scientists and Public Rejection
As one might imagine, there’s a growing group of intelligent individuals that have become entirely disillusioned with the academic system. Many have been rejected by academia before they even had the opportunity to participate. For those who have achieved the lauded PhD status, they did so due to a deep personal interest in research and a desire to seek truth. They did not aspire to one day become glorified grant writers constantly fretting over their H-index and engaging in departmental drama.
Brilliant young men, often white young men, have found themselves in a position where even achieving the rank of faculty comes with more burdens than the position justifies. Good scientists in academic circles are disenchanted with the idea of sitting in their office for 8 hours a day writing proposals to nameless government bureaucrats.
A poll conducted by Fastgrants showed that 78% of respondents would dramatically change the way in which they conducted research if that option were available under the terms of their current grant contract. The current system of grants is so inflexible and filled with bureaucratic minutia that merely operating within it is a full time occupation; stress shoulder by faculty instead of actually conducting research (grad-students do the research, perpetuating the cycle);.
There have even been proposals to utilize a lottery system rather than an assessment system to assign grant funding because bad ideas are so frequently funded. Scholars that get funding must write clever proposals and have a few friends in high places.
The result is a growing anti-scientific sentiment among the general population, and among scientists. The combined feminization of academia, DEI hires and the replication crisis have shown that scientific institutions can no longer be trusted. Scholars are not great misunderstood geniuses conducting cutting edge research any more.
A poll conducted by Pew Research over the last 5 years has found that confidence in scientists dropped. People with “a great deal of trust” in the sciences fell from 39% to 26% while those with “no trust” have increased from 13% to 23%. Part of this was the disastrous public response to the global pandemic. Another part of this is the absolute incompetence on display at major scientific institutions.
Growing discontent with public funding wasted in make-work faculty employment is going to have serious side-effects. For nearly half a century, academia has been riding high on its productions from the 1960s and 70s. Since then, breakthrough innovation has fallen off a comparative cliff.
Eventually, soon in all likelihood, free research money is going to dry up. When that happens, the internecine drama of modern academia is going to explode. Accusations will be made by faculty against other faculty because some one “stole” some one else’s research dollars. This’ll be an “anything that sticks” type of political bloodbath because the winner gets 5 years funded and the loser gets sacked. In about 10 to 15 years, academia will be a very bad place to be a white man. National labs may also see a collapses in public expenditure. Private corporations will still fund research projects, but they’ll demand something that few public grants ask for: results.
Things are going to get vicious as academics and scientists climb over each other to access a dwindling supply of public funds. Those in academia who are paying attention have already started to note the upcoming fiscal cliff. Many plan either to retire before then, or are quietly altering research plans while making lists of friends and enemies. It’s like highschool drama, but where winning means you get to keep your comfortable job.
What this all means for Innovative Development
While much of the article above complains about the state of the sciences, do not misunderstand: The sciences are absolutely crucial, particularly long-form low-return innovative breakthrough. Our financial system relies on perpetual growth, and without innovation we’ll see stagnation in a way that we’ve not seen since the Enlightenment. That said, modern academia and the modern national research institutions do not paint a pretty picture for public research. Those most capable of performing at high levels are not interested in playing the highschool popularity contest i.e. modern academia.
Most advances in the 21st century are iterative rather than innovative. AI is based on decades-old-theory and we just now have fast enough digital systems to implement it. The greatest breakthrough of the last two decades was a digital solution to the Byzantine Generals Problem which led to the creation of modern cryptocurrency and NFTs. That breakthrough wasn’t even performed by academia or a national lab. It was performed anonymously on the internet.
Outside of a few niche interests, stagnation may have already begun; it’s likely to continue. Small iterative advances will be made here and there, but the reduced return-on-investment for research will see those slow with time. Most serious innovation is going to take place in large driven companies like Space X. In the private sector, it’s mostly quick-return breakthroughs that are rewarded. Most of that falls under the category of applied engineering rather than basic research. Even then, bureaucrats want badly to regulate digital discourse which will incidentally slow or prevent innovation in digital spaces.
The most advanced work will likely be done by social and digital scientists who work part-time out of their basements. Which means that resources for the greatest minds will be limited compared to the resources consumed by bullshit.
Breakthrough research itself represents a problem for the global bureaucratic system… a major breakthrough like that which created Bitcoin has resulted in an entirely new asset class that’ll take decades to fully adapt into bureaucratic oversight. A stagnant bureaucracy doesn’t like change. Thus, in its own self-interest it selects against sending dollars to potentially breakthrough ideas.
It also looks bleak for demographics and resource limitations. The combination paints a similarly bleak outlook for the global financial system. Something to consider: all these different threads weave together into a pretty frayed tapestry of civilization.
[Analysis/Review] The Limits To Growth
![[Analysis/Review] The Limits To Growth](https://substackcdn.com/image/fetch/w_1300,h_650,c_fill,f_webp,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Faeb83685-cd18-4b16-bc46-6c1262ebac45_663x1000.jpeg)
The Limits to Growth is a scientific publication based on a number of computer simulations performed in the 60s and 70s. While the book uses a scientific and disconnected approach to the mathematics and models, the authors are not. Put simply, the Limits to Growth discusses series of simulations based on resource scarcity, human population, energy avail…
The Future of Academia
The university system is a degree-mill where conformity is rewarded and bureaucracy is bloated. A tremendous amount of public funding is swallowed by bullshit tier jobs: university assistant-dean-of-student-internal-affairs-oversight type positions, and bullshit tier research: turns out sleeping near an airport means you don’t sleep as well. The same is happening at a lot of national labs. Brilliant people don’t tend to conform to obviously wrong social statutes… thus the most brilliant people who should be conducting research are getting pushed out of it.
In fields like “computer science” one’s GitHub anthology is far more valuable than a University degree. The only successful programmers I’ve met (the ones that are well paid and do good work) have great GitHub’s with a lot of programming on them… and don’t have Comp-Sci degrees. The degree itself has been devalued.
The academic system is propped up by gratuitous public funding, and as that funding ends (either through inflation or the cutting of public grant programs), large swaths of the academic system are ending with it. Even without that effect, much of public education can now be performed online and performed better. The feminization of academia has driven away many of the most (potentially) productive students.
Disciplines that don’t require an expensive laboratory to teach or learn are going to get wiped out. When your Calc. 1 professor is a worse teacher than a youtuber with 100,000 subscribers, there’s no incentive to pay $3000 to take Calc. 1.
Ultimately, much of the conventional University system becoming educationally and research irrelevant. Alternative scholastic methods and research institutions, and alternative methods of judging academic character are slowly developing in new places, like here on substack. Those brilliant minds now pushed out of academia? They haven’t disappeared. They’re working on either creating new academies or companies (or taking the Breaking Bad approach to a society that doesn’t want them).
Brilliant scholars remaining in academia are as interested in its quiet destruction as the rest of us. They’ll have a chip on their shoulder for the rest of their lives; having been coerced into kowtowing to Woke idolatry to keep their jobs.
Over the next 50 years or so, Universities may become in-name-only institutions. Corporate research still needs to happen, though. Some national research will continue to be funded. The research dollars that remain will likely find find effective laboratories to fund research in. Institutions will develop while academia may restructure to focus on attracting corporate research funding instead of government.
The End of “Progress”
A Hegelian belief in “the march of progress” has characterized much of contemporary history. Often normal people have a difficult time understanding that true breakthrough innovation occurs with the blood and sweat and tears of exceptional scholars over thousands of hours. Innovation, progress, and scientific revolution are not the default-state of human civilization.
The last 300 years have been a wild aberration from the norm when it comes to human civilization and technical development. This roller coaster isn’t going to continue forever. The Limits to Growth indicate that physical resources are running low (to the point of price-inflation and supply-shocks). Cultural intellectual resources are thinning as iterative technical development seems to have slowed.
The continuous innovation of the last 300 years have been a process:
innovation→ adoption→ adaptation→ plateau
Innovation has led to an exponential increase in quality of life until the 1970s or so. Individually, a great breakthrough is made, it is adopted in industry, quality of life improves and population rises. Then things stagnate until there is another breakthrough innovation.
Breakthroughs have stacked atop one another for 300 years to create the illusion of constantly developing science and technology like a force of nature. Yet each one of these individual breakthroughs is a process that ends in stagnation. Eventually this civilization will see it’s last breakthrough. After that, technological stagnation follows with occasional iterative advancement.
We may have already seen the end, or Elon Musk might get us to mars atop his mighty rocket. There’s no way to know when the last major breakthrough will happen, but they are growing more infrequent and less significant over time. Bullshit research gives us bullshit results.
Could it be Fixed?
This brings us to one of the most important questions: is it possible to unfuck the disaster brewing in academia and scientific research?
The decline in marginal return on investment for scientific research indicates that there’ll be a continuous slowing of breakthrough research over time. We’ve managed to maintain a steady trend since the 1970s by dramatically increasing the number of scholars performing research. Even that trend is now slowing. There are the following problems to solve:
Economic slowdown due to reduction in scientific return-on-investment
Hold scholars to high standards
Find something to do with all these kids who hold an MS or PhD and can’t find work
Defeminize Academia
Economic Slowdown: The decline in marginal return on investment for scientific research indicates that there’ll be a continuous slowing of breakthrough research over time. We’ve managed to maintain steady technical development by dramatically increasing the number of scholars performing research. Even that trend is now slowing. To fix the sciences, it would require an economic and cultural reevaluation of expectations. There will be a slowing of technical innovation over time, and the population must come to expect and accept that change. The economic system will need to shift away from globalist tech-bro innovation and back to a more bourgeoise form of industrialism with the added limitation of scarce material inputs.
Hold Scholars to High Standards and Find work for MS and PhD Holders: This is, perhaps, the least difficult solution and kills two birds with one stone. Rather than pushing scholars to change their publication habits, create a National Replication Institute. While expensive, the work performed there would be simple. Scholars are hired (MS and PhD holders) and their jobs would be to select publications, especially high-impact publications, and replicate them. They’re given laboratories of required equipment and salaries to do the work. A scientist with a “passed replication” stamp on one of his or her articles would have it as a badge of honor indicating that the work was both good and significant enough to be tested in the first place. A big red “failed replication” stamp could torpedo a scientific career. A national institute of replication would probably cost a few billion dollars (US) but could itself radically improve the state of the global scientific community. This may become a future article.
Defeminize Academia: This may be the most difficult problem to solve as once a career path has become “women’s work” men tend to avoid it. The solution of “just ensure universities only admit 70% male students” would be work, but is socially untenable. The defeminization of academia will require some radical cultural restructuring regarding the feminine role in society in general. I’m open to hearing ideas on this one, let me know if you’ve got thoughts in the comments below.
Will it be Fixed?
It’s unlikely that the sciences are going to undergo the necessary changes. A National Replication Institute would be great if we could explain the problem to politicians, unfortunately they’re likely too busy eating crayons and sucking donor dick. The global elites have their wealth directly tied to an infinite-growth/infinite-innovation model of Keynesian economics. They’re unlikely to be willing to give up half their potential gains for something silly like preventing apocalyptic global economic instability. Defeminizing academia is probably not going to be possible until a major cultural reformation on gender roles.
So we must settle in for the long-haul. Scientific stagnation is very likely to occur during this century. Iterative advancements will be made to squeeze out more efficiency here and there, but major revolutions in ones’ way of life are likely a thing of the past. Instead one should think about squeezing out your own efficiencies as without global progress rent-seeking is going to become one of the optimal methods of securing economic stability.
The obvious solution is alternative academia to outcompete the state-backed academia, founded by autists for autists, somehow resilient against normie takeover, e.g. by strict meritocracy being autistically enforced.
Obviously this is illegal in the world of "civil rights" and "equity laws", because such a system would strongly bias towards white men, so such alternative academia would have to operate outside the west, or get past these laws somehow.
It will be fixed when the sacrifice and reward systems are fixed. Which is likely never.
However, there might be something with what Musk is driving at. When people do make it to Mars, which I think they will sooner rather than later. You will have people innovating – because they're on Mars!
People on Mars can't rely on bullshit research from Earth. They'll have to figure out new things on the spot. And I believe they will.
As the proverb goes, "Necessity is the mother of invention." Who first said it and when – I don't care, you get the point.
Why does everyone want to be rich?
People like to be comfortable, that much is known. And so, people will not strive for things that don't gain them something, either in the form of increased comfort, or the form of legacy. Currently the incentives are just not there for real scientific research. You can get big-ass grants for bullshit papers, why would you strive to do something real?
I would like to go a step further though. I think that all this is on purpose. I believe that there are innovations that have far surpassed what we’ve seen in the private realm – and bullshit research and the grant system itself are the cover.
In other words, you don’t need a conspiracy, you just need the existing scientific research framework to be minimally effective, and then incentivize that ineffectiveness.
That’s literally what we’re seeing right now.