by John Ridgway
Any politician faced with the challenge of protecting the public from a natural threat, such as a pandemic or climate change, will be keen to stress how much they are ‘following the science’ — by which they mean they are guided by the dominant scientific narrative of the day. We would want this to be the case because we trust the scientific method as a selective process that ensures bad science cannot hope to survive for very long. This is not a reality I choose to ignore here, but it is something I would certainly wish to place in its proper context. The problem is that the scientific method is not the only selector in town, and when all others are taken into account, a much murkier picture emerges – certainly not one that is clear enough to place a dominant narrative upon an epistemological pedestal.
Feedback reigns supreme
Of all the selection pressures that operate within a scientific community, perhaps the most fundamental is not the peer review of academic papers but one that can be summarised as follows:
“For to everyone who has will more be given, and he will have abundance; but from him who has not, even what he has will be taken away.” (Matthew 25:29, RSV).
This is the so-called Matthew effect [1], also known as ‘cumulative advantage’. It is a positive feedback that serves to place fame and influence in the hands of a select few. This is true in life generally but also in academia specifically. For example, work that has already received a significant number of citations will tend to attract even more, if only because a currently large number of citations raises the likelihood of further reference resulting from any random selection from existing citation lists. This bibliometric phenomenon, in which success breeds success, was first studied by the physicist Derek de Solla Price, who emphasised its essentially stochastic properties:
“It is shown that such a stochastic law is governed by the Beta Function, containing only one free parameter, and this is approximated by a skew or hyperbolic distribution of the type that is widespread in bibliometrics and diverse social science phenomena.” [2]
In practice, however, the selection will be anything but random since factors such as influence and prestige will also determine the likelihood of one’s work being cited. Either way, the higher profile scientist will become even more successful.
The Matthew effect also has a bearing upon the chances of a paper being published in the first place. An editor or reviewer’s familiarity with the quality of an author’s existing canon of published work will make it easier to judge the latent merit of a submitted paper, improving that author’s chances of adding to his or her list of publications. A less well-known author will have no such advantage. This creates a positive feedback that can result in a mono-culture based upon the work of a relatively small number of dominant authors. Again, the Matthew effect may be purely statistical, requiring no particular bias or prejudice to be in evidence. As Remco Heesen and Jan-Willem Romeijn, the philosophers of science who have studied this effect, put it:
“This paper concerns biases that are rooted not in the prejudices of editors or reviewers, but rather in the statistical characteristics of editorial decision making…Hence, even if editors manage to purge their decision procedures of unconscious biases, they will be left with biases of a strictly statistical nature. The statistical biases contribute to the already existing tendency towards a mono-culture in science: a purely statistical Matthew effect.” [3]
There are in fact a number of ways in which mono-cultures may develop, each one involving the Matthew effect. For example, there is the feedback in which funding leads to success, which in turn leads to more funding. Also, a senior faculty member’s research interests will influence recruitment policy, thereby reinforcing faculty interest in those research areas [4]. Take, for example, the scientific mono-culture that quickly developed within the field of foundational physics. As physicist Lee Smolin explained back in 2006:
“The aggressive promotion of string theory has led to its becoming the primary avenue for exploring the big questions in physics. Nearly every particle physicist with a permanent position at the prestigious Institute for Advanced Study, including its director, is a string theorist; the exception is a person hired decades ago.” [5]
This dominance is not the fruit of the scientific method, since the vital element in which theories are tested experimentally is notable by its absence. This is not the case of a theory that ousted its contenders by proving to be more testable or by enjoying greater experimental verification. Its initial appeal stemmed from some early and quite spectacular theoretical successes, but string theory has since become mired in an arcane and thoroughly untestable set of mathematical conjectures that does not even qualify as a theory in the accepted sense. On the contrary, the ultimate dominance of string theory seems to be the result of positive feedbacks in which academic success became far more important than scientific achievement. In the words of Lee Smolin:
“Even as string theory struggles on the scientific side, it has triumphed within the academy.”
String theory’s rise to dominance is a classic case of what the Matthew effect can achieve when the scientific method is compromised. As such, it stands as a cautionary tale for any scientific field in which theorising and modelling ultimately outstrips the capacity for experimental confirmation.
Another of the problems with mono-cultures is that they can lead to a potentially unreliable narrative that acts as a societal beacon for normative thinking. As the narrative strengthens, and societal attitudes embed, so will the power to coerce a greater level of alignment within the scientific community. The consensus becomes a self-reinforcing social dynamic, for good or for bad. This is an example of a class of phenomena studied by organizational scientists Jörg Sydow & Georg Schreyögg:
“More often than not, organizations and also inter-organizational networks, markets or fields are characterized by dynamics that seem to run by and large beyond the control of agents…Among these mostly hidden and emergent dynamics, self-reinforcing processes seem of particular importance; they unfold their own dynamic, turning a possibly virtuous circle into a vicious one (Masuch, 1985).” [6]
Of course, no one who has been caught up in such a dynamic need assume the presence of subterfuge. That being said, the human race is no stranger to politicking and manipulation, and so bias and hoaxing remain optional extras. In particular, one has to be concerned that the growth of AI will increase the likelihood of problematic mono-cultures developing. As David Comerford, Professor of Economics and Behavioural Science, University of Stirling, points out:
“Just a few years ago it took months to produce a single paper. Now a single individual using AI can produce multiple papers that appear valid in a matter of hours.” [7]
Given that the Matthew effect is a numbers game, anything that can generate papers on an industrial scale must be of concern. And there is evidence that the trend is for such papers to be written by ghost writers in the services of corporate interest – so-called ‘resmearch’. As David Comerford explains:
“While the overwhelming majority of researchers are motivated to uncover the truth and check their findings robustly, resmearch is unconcerned with truth – it seeks only to persuade.”
And that is before considering the possibility that individuals may be using AI to increase their productivity so as to game the Matthew effect in their favour. Either way, AI has reduced the costs of producing such work to a virtual zero, thereby placing greater pressure upon the scientific method to counter the emergence of potentially unreliable mono-cultures.
The natural selection of bad science
Whilst mono-cultures are to be avoided, they won’t usually be centred upon bad science. Indeed, in science there is always a guiding hand designed to prevent this happening. Work is routinely evaluated by peers for its quality and value, and such scrutiny should be to the benefit of the good science. Except the evidence would seem to suggest that bad science can still thrive despite such scrutiny. There is another selection operating, but far from acting as a corrective force, filtering out poor work and removing both purely statistical and bias-fuelled positive feedbacks, it seems to be one that can actually promote bad science. The explanation for this troublesome effect has been given by Paul E. Smaldino and Richard McElreath. The opening statement of their paper’s abstract sets the scene:
“Poor research design and data analysis encourage false-positive findings. Such poor methods persist despite perennial calls for improvement, suggesting that they result from something more than just misunderstanding. The persistence of poor methods results partly from incentives that favour them, leading to the natural selection of bad science. This dynamic requires no conscious strategizing—no deliberate cheating nor loafing—by scientists, only that publication is a principal factor for career advancement.” [8]
The poor research design and data analyses alluded to here are the misuse of p-values and variations on the theme of data torturing, all of which have been widespread within the behavioural sciences for many years now. The problem arises because publication provides the primary method of reward, and yet publication requires positive results, which in turn encourages practices that lead to false positives. Richard Horton, editor of The Lancet, points towards the need to have the right incentives:
“Part of the problem is that no one is incentivised to be right. Instead, scientists are incentivised to be productive and innovative.” [9]
Smaldino and McElreath emphasise that no stratagem is required:
“This paper argues that some of the most powerful incentives in contemporary science actively encourage, reward and propagate poor research methods and abuse of statistical procedures. We term this process the natural selection of bad science to indicate that it requires no conscious strategizing nor cheating on the part of researchers. Instead, it arises from the positive selection of methods and habits that lead to publication.”
They continue by pointing out the obvious fact that “Methods which are associated with greater success in academic careers will, other things being equal, tend to spread”. One would like to think that only the good practices spread, but this is clearly not the case. The ones that spread are the ones that are associated the most with career success, and this unfortunately involves a set of criteria that only partially correlates with quality of work. In this instance, the weaker the statistical power of the data, the greater the chances of publication — and publication is what everyone seems to want.
Fortunately, this is not a problem in which the scientific method stands idly by. Replication and reproducibility are its cornerstones and, as a consequence, the malpractice has manifested itself in the infamous ‘reproducibility crisis’ within science. Opinions differ regarding how serious the problem is; some would claim that the crisis is existential whilst others feel the problem is somewhat overstated. However, no one is claiming that the problem is easily rectifiable, which is unsurprising given that the problem has its roots in the reward structures that sustain academia [10].
So where does that leave us?
The social structures and reward mechanisms within science are such that both good and bad science can find itself the beneficiary of a natural selection, and it can be very difficult for the lay person to know which way the selection has operated when creating a dominant narrative. Knowing the strength of consensus is not nearly as important as understanding the mechanisms at play, and to assume that they are dominated by the scientific method is naïve. Add to that the statistical effects that predispose academia to the emergence of potentially damaging mono-cultures, and one has further reason to resist the temptation to automatically accept the narrative of the day.
It should be appreciated, however, that this is not an anti-science sentiment. It is precisely because social dynamics can entrench ideas irrespective of their epistemological validity that the scientific method is so important. Nevertheless, a mature appreciation of the importance of the scientific approach should entail an understanding that the scientific method cannot hope to be one hundred percent effective in eradicating the vagaries and stochastics of consensus building. In particular, it cannot hope to fully avoid the effects of statistical Matthew effects and their predisposition to create mono-cultures. A mature appreciation of the importance of the scientific approach should therefore include also an understating that there is really no need to invoke the idea of a scientific subterfuge. There is no conspiracy, only scientists doing their job.
Footnotes:
[1] The term was first coined in the context of the sociology of science by Robert K. Merton and Harriet Anne Zuckerman. See Merton R.K. 1968 “The Matthew effect in science”, Science, New Series, Vol 159, No. 3810, pp. 56-63. https://repo.library.stonybrook.edu/xmlui/bitstream/handle/11401/8044/mertonscience1968.pdf?sequence=1&isAllowed=y.
[2] de Solla Price, Derek J. 1976, “A general theory of bibliometric and other cumulative advantage processes”, J. Amer. Soc. Inform. Sci., 27 (5): 292–306, https://doi.org/10.1002/asi.4630270505.
[3] Heesen R., Romeijn JW. 2019 “Epistemic Diversity and Editor Decisions: A Statistical Matthew Effect”, Philosophers’ Imprint, Vol. 19, No. 39, pp. 1-20. http://hdl.handle.net/2027/spo.3521354.0019.039.
[4] In fact, respect for senior faculty members has a lot to answer for when it comes to establishing consensus. See Perret C. and Powers S. T. 2022, “An investigation of the role of leadership in consensus decision-making”, Journal of Theoretical Biology, Vol 543, 111094, https://doi.org/10.1016/j.jtbi.2022.111094.
[5] Smolin L. 2006 “The Trouble With Physics”, page xx, ISBN 978-0-141-01835-5.
[6] Sydow, J., Schreyögg, G. 2013 “Self-Reinforcing Processes in Organizations, Networks, and Fields — An Introduction”. In: Sydow, J., Schreyögg, G. (eds) Self-Reinforcing Processes in and among Organizations. Palgrave Macmillan, London. https://doi.org/10.1057/9780230392830_1.
[7] Comerford D. 2025 “We risk a deluge of AI-written ‘science’ pushing corporate interests – here’s what to do about it”. The Conversation. https://theconversation.com/we-risk-a-deluge-of-ai-written-science-pushing-corporate-interests-heres-what-to-do-about-it-264606.
[8] Smaldino P.E., McElreath R. 2016 “The natural selection of bad science”, R. Soc. Open Sci., 3: 160384, http://doi.org/10.1098/rsos.160384.
[9] Horton R. 2015 “Offline: What is medicine’s 5 sigma?”, The Lancet, Volume 385, Issue 9976 p1380. https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(15)60696-1/fulltext.
[10] Leyser O., Kingsley D., Grange J. 2017, “Opinion: The science ‘reproducibility crisis’ – and what can be done about it”. University of Cambridge – Research News. https://www.cam.ac.uk/research/news/opinion-the-science-reproducibility-crisis-and-what-can-be-done-about-it.
great article. ai is just a tool, just like the internet, be an early adopter. you can direct its hive mind, on general scientific consensus, with some minor knowledge in coding, directing its “personality”.
Thank you, John. Hard science has always had … an attitude … concerning social science. Some of it deserving, some not. I hope they listen to your well written piece.
Unto those that have not, the AMO has given, thus:
A Statement of the American Meteorological Society
27 August 2025
Here we identify five foundational flaws in the Department of Energy’s 2025 Climate Synthesis report.
Each places the report at odds with scientific principles and practices.
1: Lack of breadth across scientific fields.
2: Lack of depth within scientific fields and specific topics.
3: The DoE Report is based on an unrepresentative group of subject matter experts.
4: The DoE Report selectively emphasizes a small set of unrepresentative findings, particularly those that might appear beneficial on superficial examination…
5: The DoE Report extrapolates from a limited subset of findings to reach conclusions that do not follow from comprehensive consideration of the scientific evidence …
“The DoE Report selectively emphasizes a small set of unrepresentative findings, …”
I other words, it is unacceptable to you because it goes counter to the consensus. I’m reminded of Einstein’s remark directed to the 100 physicists criticizing his Special Relativity theory: “Why 100 when it would only take one to show me to be wrong?”
Your complaint is a special variety of ad hominem where you dismiss hypotheses that are not accepted by the majority, irrespective of the facts. Paradigm Shifts come about because one person questions the consensus and offers an alternative.
How about dismissing the ones that don’t make sense? That is what scientists do.
1, 2 and 3 are ad homs. Not a good start.
Best to take the DoE report on its merits.
The DOE report is just as biased as any other climate report.
This time, “consensus” scientists were excluded. In the past, skeptic scientists were excluded.
Consensus scientists claim CO2 emissions will be harmful in the long run.
Skeptic scientists claim CO2 emissions will be harmless in the long run.
CO2 emissions in the past 50 years have been harmless. I believe they have been beneficial.
Will the next 50 years of CO2 emissions will be harmful? That’s hard to believe.
Unfortunately, climate science has deteriorated into a wide range of predictions.
With no evidence that scientists can predict the climate in 100 years. That means climate predictions are not science at all. They are climate astrology.
We get predictions because people love predictions. Governments pay scientists to make scary climate predictions. Then the government seized more power to fight the coming climate crisis. A crisis that is most likely completely imaginary.
Money was invented partly to measure the success of a venture. It can be used to measure scientific success, but this approach seems to be seldom used now.
As an example, for 15 years I was a Geochemist co-manager of a team of about 50 graduate explorers for new mineral deposits/mines in Australia. Four of our discoveries were of world rank. Three of these were without surface expression, showing only geophysical responses such as gravity, magnetics and gamma spectrometry. Thus, science was vital to discovery. As policy, we managers insisted on high quality data with much replicate sampling, quality control etc.
In year 2015 my geological colleague summarized the dollar value of sales from these 4 mines to date, some 30 years after mining started. Year 2015 values were used for currency and product prices. The grand total was 42,300 million Australian dollars, roughly $US 28 billion at present.
We suggest that this calculation places a type of value on science, one that does not have drawbacks of other methods such as the Matthew effect discussed above. Geoff S
Follow the money trail … invariably ends up at the Federal pig trough. Billions and billions of taxpayer dollars are distributed by the bureaucrats. Abuse is inevitable, as are truly bizarre research activities, especially when re-election trolling politicians show up. The bureaucrats controlling the research grants end up being grand poobahs.
At the risk of enraging academia, the out-of-control money spigot needs to tuned off.
Academia and private industry should work out a system where the pragmatic merits of the research are jointly evaluated, with that joint guidance driving the distribution of funds. The sponsoring private entities receive some form of tax break for sponsoring the effort. The penalty for abuse ends ups as a violation of the tax code.
In passing, the approach does not preclude using taxpayer money but the bureaucrats have their wings severely clipped. Need a 2 out of 3 authorization, the requesting organization, private sponsor(s), and federal government.
If no entity is interested in sponsoring the research, then academia can fund the effort themselves, perhaps using their endowment money. This approach avoids the obvious intellectual property rights problems that logically emerge when institutions are using taxpayer money. Private industry can chip in as well, but not the taxpayer. To the extent that the effort involves expenses, then that constitutes a tax write-off for the involved parties.
Mike,
Here in Australia, I worked as a scientist since about 1965 and so had experience with different systems.
Our golden science years, in hindsight, were about 1975 to 1985. Much academic research was funded by industry and chosen on a needs basis. Our national science research body, CSIRO, had a lovely record of success with, for example, invention/commercialisation of atomic absorption spectrometry and the pastoral introduction of the Townsville Stylo legume. We in industry would fund projects for typically excellent results. Nationally, there was far less of both political and bureaucratic involvement in public enterprise and private science. Our Atomic Energy Commission in the 1970s researched nuclear electricity and promoted building a reactor on land near Sydney. They also did top collaborative research with industry, such as using the MOATA research reactor for highly accurate analysis of the ores from the emerging world class Ranger Uranium mines.
These types of arrangement are not now available in Australia. CSIRO has been taken over by activist managers, the AAEC no longer exists.
It is easy to demonstrate that such science in Australia has regressed. It is easy to show how this happened and who the public players are/were. It is quite difficult to work out why it happened, what motivated the activist players, whether they knew they caused harm, not beneficial progress.
Reader help is appreciated.
Geoff S
The only real driver of economic performance and human development is personal freedom.
I once read that 95% of what scientists say turns out to be erroneous.
Medical science research lives by a far higher standard than climatology will ever be held. And yet, even in medicine, “most current published research findings are false.” (see—e.g., John P. A. Ioannidis, “Why Most Published Research Findings Are False,” in PLOS Medicine)
Throughout the eons adaptation has always been the first principle in humanity’s survivability. Early humans that could solve novel problems like, adapting to dramatic climate shifts, e.g., by finding new food and energy sources and creating better thermally regulated shelters.
Pingback: The Matthew Effect: How Science Selects Success and Failure
John: TY for tackling an octopus. Three points:
1 – Real Science is under an intense assault. The reason is simple: it acts as a gatekeeper against dumb policies (e.g., industrial wind energy, COVID treatments like Remdesivir, etc.) — as the proponents of said poor policies hate that they are being exposed.
2 – One of the most insidious assaults is going on in US K-12 schools. The NGSS is an inferior set of Science standards, that includes the scrapping of the traditional Scientific Method(!). BTW, 49 States have adopted all or most of the NGSS.
3 – I hate seeing the phrase “Bad Science.” IMO there is no such thing. Science is a process. An analysis, policy, etc, either follows the process or it does not. If it does not, it is not “Bad Science” but rather it is NOT Science. A more appropriate use of “Bad” would be to scientists. There are definately MANY “Bad” Scientists — people who are untethered from real Science.
In addition to the more nuanced problems of peer review and scientific publications, we have this
“Numerous recent scientific and journalistic investigations demonstrate that systematic scientific fraud is a growing threat to the scientific enterprise. In large measure this has been attributed to organizations known as research paper mills. We uncover footprints of activities connected to scientific fraud that extend beyond the production of fake papers to brokerage roles in a widespread network of editors and authors who cooperate to achieve the publication of scientific papers that escape traditional peer-review standards. Our analysis reveals insights into how such organizations are structured and how they operate.”
…” Changing the culture and incentives of science is a slow process. Many of the stakeholders whose engagement is necessary for change are those benefiting from the status quo. However, in our view, the severity of the situation requires urgent action”
https://www.pnas.org/doi/10.1073/pnas.2420092122
Great points. I like the incentive points that bring out bad science. It brings to mind the corrupt publishing industry of scientific papers. A way to combat this is being explored by the Journal of Global Surgery. http://www.jogs.one It is peer reviewed but minimizes costs allowing scientists, researchers and doctors to publish their findings in an economic way. It is a great model to encourage a greater breadth of research and consideration.
Extremely interesting article, I’ll have it printed and posted on the wall!
Thank you for a well-written and thought provoking article.
Those perverse incentives! As Mike Jonas stated, AMO’s statements 1, 2, and 3 are a type of ad hominem. They are also an example of gatekeeping and cancel culture. I would disagree that we should always say “there is really no need to invoke the idea of a scientific subterfuge. There is no conspiracy, only scientists doing their job.” Climategate in 2009 made us aware that beyond the Matthew Effect, there is sometimes corruption, too.
Doug,
You’re right, I didn’t say quite what I had meant to say. The point is that there is no need to invoke the idea of scientific subterfuge, since a dodgy mono-culture is still possible even when scientists are just doing their job. That doesn’t mean to say that scientific subterfuge hasn’t occurred from time to time. So don’t worry, no one has forgotten Climategate; nor do I overlook the fact that the only reason why they got away with the feeble excuses given at the time is because they were protected by the prevalent mono-culture of the day. That’s what a dodgy mono-culture can do – it offers free get-out-of-jail cards to those who are faithful.
Great essay, John. It illicits so many questions.
Doug: “Climategate in 2009 made us aware that beyond the Matthew Effect, there is sometimes corruption, too.”
John: “That’s what a dodgy mono-culture can do – it offers free get-out-of-jail cards to those who are faithful.”
“…they were protected by the prevalent mono-culture of the day.”
There remains the jail-free-card for the unfaithful–call it the wicked politics card.
While climate is often described as a wicked problem it will always remain innocent, lacking intent. Yet the sculptural effect that climate science describes is wickedly anthropomorphic by very definition. Said science describes concepts infused with political attribution, often unresolved naturally except through the impetus of politics for change–how ironic, how convoluted. Is it really so ironic?
The essential question remains; what is the state of today’s mono-culture relative to climate science?
The elephant in the room is the IPCC; the quintessential case study. They’re the poster child representing almost all the attributes in your essay. They hold all the get-out-of–jail-free cards by design.
First para, “elicit”
Jungletrunks,
The IPCC, by its own admission, exists to create consensus:
https://cliscep.com/2025/01/01/three-cheers-for-the-ipcc/
John, your linked essay is also good.
The devil is in the details, consensus is a benign word without context; you get into some of the mono-culture aspects of the IPCC in the last linked essay.
If you have time you should read the link to the book below “The Evolution of International Cooperation in Climate Science”, it covers just about the entire laundry list you described in your essay; at least skip towards the end. It’s a case study for “Mono-cultures, and the Natural Selection of Bad Science”.
Pages 54-56
…scientists described the developments of the 1980s as a “revolution” in the social structure of climate science… “A steady diet of fresh scientific perspectives helps to maintain regular doses of funding, helped in turn by an endless round of conferences” (O’Riordan and Jäger, 1996, 2)
https://web.archive.org/web/20160304004003/http://journal-iostudies.org/sites/journal-iostudies.org/files/JIOSfinal_5_0.pdf
John, one of the jaw dropping excerpts from your last link:
“…from an IPCC guideline document on the consistent evaluation and communication of uncertainties:
‘Use the following dimensions to evaluate the validity of a finding: the type, amount, quality, and consistency of evidence (summary terms: ‘limited’, ‘medium’, or ‘robust’), and the degree of agreement (summary terms: ‘low’, ‘medium’, or ‘high’).’ ”
That’s right, the 98% empirical based climate science we all know and love is authoritatively weighted using excruciatingly precise rigor; a high school multiple choice methodology that weighs expert feelings about the finer points of difficult science.
Design by committee is a celebrated methodology for so many of human kinds most vaunted pedestrian accomplishments; i.e., bridges to nowhere, California high speed rail.
https://medium.com/@christian.hartvig/cooking-the-perfect-disaster-why-design-by-committee-tastes-so-bland-64720d8a749b
Jungletrunks,
Thanks for the link. It made for a very interesting read, emphasising as it did just how much the IPCC’s existence depends upon its ability to perpetuate consensus thinking. Basically, without consensus it has no purpose. Of particular note is the observation that early consensus statements were very vague and non-committal but they have now been superseded by much bolder statements. Is this purely down to the extent to which scientific understanding has developed? Well, that might be the case if the scientific method were the only selector in town, otherwise…
As for the IPCC’s guidelines for ‘the consistent evaluation and communication of uncertainties’, all I can say is that it appears to be a recipe for consistently getting it wrong. It uses a 3×3 matrix in which strength of evidence can be combined with levels of consensus, as if they are independent variables. This is errant nonsense. If strength of consensus is not being driven by strength of evidence then what is the driver and why is it allowed to influence the overall calculation of confidence levels? High levels of confidence in the presence of low quality evidence — just because a good level of consensus has somehow been achieved — are not worth a dime. Also, add the fact that evidence can include expert testimony, the strength of which involves evaluations of consensus, and you have a clear example of double counting! It’s just a mess of confused thinking and it lies at the heart of the IPCC’s methodology for formulating public statements.
The mono-Culture is a good characterization
Tunnel vision
Echo chamber
High levels of bias
Praise from peers for correct thoughts
All of which fall under the mono culture theme.
excellent examples of exclusion of experts outside the approved circle:
LCOE – yet excluding any cost accountants with manufacturing expertise
Renewables – excluding any engineers such as planning engineer
Paleo – exclusion of botanical scientists outside the circle
failure to bring in experts or even generalists outside the sphere to crosscheck basic reasonableness
Numerous examples in medical science such as :
Most every pro effectiveness masking study
96 US cities Increase in premature mortality with increases in ground level ozone Bell Mcdermott.
You’ve got to ac-cent-tchu-ate the positive
E-lim-i-nate the negative
Latch on to the affirmative
Don’t mess with Mr. In-Between…
H/t the Andrew Sisters.
There will be a paper someday perhaps explaining how it came to be that the Left abandoned science and in their distrust of humanity sought to destroy it. The mathematics of McShane and Wyner should be thought of as the chalkboard squeak heard ’round the world: M&S’ paper did not simply debunk MBH98/99/08 (aka, the ‘hockey stick’ graph). That’s been done many times by many others. M&S’ greatest contribution is as an inspiration to a new generation of scientist and statistician to examine the pseudo science of Western academia and to pick up the chalk and start outlining the dead bodies upon which the failed ideology of the Left lies.
This Video highlights the fight that the world is in and is a celebration of the voices that speak truth to power. These climate scientists have put everything on the line to fight for what is right.
https://app.screencast.com/jwCizhbKhiVVH
This short video highlights the dangers of a Monoculture, and how people can fight back.
https://app.screencast.com/vZJnv6XSBOMS1
Another non-starter “green” program. It’s not bankable now and never will be.
“It’s a bit of a myth out there that direct air capture is going to be bankable,” 1PointFive President and General Manager Anthony Cottone, said at BloombergNEF’s Barrel of Tomorrow in the Age of AI Summit in Houston Thursday.
Lenders want to see long-term revenue, while customers in the voluntary carbon market are not always willing to commit to longer contracts, Cottone said. Capturing and removing carbon from the air successfully also involves sequestration, and carbon storage companies hold more risk with less economic reward, he said. That “asymmetric risk” makes it so that direct air capture startups “are having a very difficult time scaling that up.”
https://www.bloomberg.com/news/articles/2025-09-18/oxy-executive-says-direct-air-capture-model-isn-t-bankable-now
Test – I’m in jail …
The Greek jurors that sentenced their fellow citizen Socrates to death for the crime of questioning the official truth knew that with the help his powerful, influential, wealthy, wise and politically connected friends — who easily could buy off the legal system and pay the necessary bribes to get out of jail — Socrates could easily flee Athens. But, Socrates refused to behave as his jurors expected when he put his love for truth above his own life and drank the state’s hemlock.
Steve Koonin
“While global sea levels have risen about 8 inches since 1900, aggregate U.S. tide-gauge data don’t show the long-term acceleration expected from a warming globe.”
Monoculture translation
“U.S. tide-gauges may indeed not show the expected long-term acceleration, but the rate of global sea level rise is indeed accelerating. “
Discuss
fwiw – Church White have been considered the premier source for analysis of SLR based on tide gauges. Unfortunately, based on google search and google scholar searches, the seems to be dearth of tide gauge studies with ending dates after 2011 (or 2013). Does any one have source for SLR studies using only tide gauges with periods covered up through 2021/2022/2023/2024?
Here is a study from 2021.
“Mean and median sea-level accelerations based on these gauges were 0.0128 ± 0.0064 mm/y2 and 0.0126 ± 0.0080 mm/y2, respectively, both at the statistically significant 95% confidence level.”
Expect the alarmists to whine about why this doesn’t mean anything. This study corroborates what is obvious just looking at the NOAA graphs, that the acceleration is not what the satellite studies say it is. Just like other predictions, a great big whiff.
https://meridian.allenpress.com/jcr/article-abstract/37/2/272/450977/Sea-Level-Acceleration-Analysis-of-the-World-s?redirectedFrom=fulltext
Well it may be a useful polar-bears-are-dying-Pacific-Islands-are-sinking AGW Climatist’s notion that low-lying atolls like Tuvalu for example are simply shrinking due to rising sea levels, scientific studies confirm the islands have been in a state of dynamic change for millennia. These geologically young landforms are continuously shaped by forces like sediment deposition and cyclones.
Severe droughts, occurred around 4,200 and 3,200 years ago In the area area where the mosul dam was erected in Iraq in the ’80s. These two events, for example, you are with me at my house characterized as “Rapid Climate Change,” is associated with the collapse of civilizations like the Akkadian Empire and others across the Levant and Mesopotamia.
None of it ever had anything to do with humanity’s release of CO2 into the atmosphere.
Climate happens! And, without our help.
Wagathon: your 4200, actually 2346bce, brought the immediate collapse of all civilisations, at least in the Northern Hemisphere. The severe droughts came later with rapid climate change due to changed earth tilt. An obliquity change, and concurrent precession change (150 days) meant no growth time to all cereal harvests.
“Climate happens! And, without our help.” Or prayers!
sealevel.info gives lots of data, including from thousands of tidal gages worldwide. Also, global averages and acceleration. Reminder: satellite readings are calibrated via tidal gages and subject to ‘corrections’ and manipulation to address ocean dynamics – diurnal, from wave actions, tides, seasonal, etc.
Sabine Hossenfelder has recently posted a video that is very germane to this article:
https://www.youtube.com/watch?v=ZO5u3V6LJuM
As you watch it I invite you to reflect upon three things:
a) My article’s observation regarding what the Matthew effect can achieve once the scientific method has been compromised.
b) How a ‘natural selection’ for bad science, caused by the rewarding of paper productivity, can exacerbate the issue of problematic mono-cultures.
c) How the removal of Hossenfelder’s affiliation to the Munich Center for Mathematical Philosophy serves as yet another example of prosocial censorship aimed at someone who dares to criticise the system.
Pingback: Natural Selection of Bad Science. Part II - Climate Etc.
The eminent philosopher and pedagog John Dewey taught that the determinant of truth or falsehood of a statement is not stubborn facts, but warranted assertability, in other words, if it has desirable outcomes. He expressly believed in consensus. He thought he’d defined something new. In fact this is the old, paleolithic, superstitious, pre-scientific way of thinking, which is the default for humanity.
Much like the battle faced by Galileo. It would be insane to offer the GCMs of the global warming alarmists as proof of their predictions– that make less sense than offering the Bible as proof Earth was created in seven days.
This article highlights how the **Matthew Effect** and mono-cultures in science can unintentionally favor weak or popular research over quality work. It shows that fame, funding, and entrenched methods often overshadow new ideas, making it harder for innovative researchers to succeed. The key takeaway is that science needs both rigorous methods **and** fair systems for recognition and resource distribution to truly promote quality and diversity in research.
Much like the Democrat party, the politically corrupted AGW climate change nomenklatura of Western Academia is not slowly riding off into the sunset, it is rotting on the vine.
P-hacking has been a problem for decades, or even more, but will especially become more problematic as AI saturation becomes complete. The only hope, really, is to fight fire with fire. While P-hacking might be more difficult for human reviewers to spot, we can hope that AI can also point out AI P-hacking, among all the other methods dishonest researchers employ getting around honest reviewers. We want gatekeepers, but not those who filter ideas they don’t like, just dishonest players in the game.