Universities Continue to Boast About Pitifully Weak Neuroscience Results

Nowadays university press releases are notorious for their brazen  bunk. Authorship anonymity is a large factor that facilitates the appearance of misleading university and college press releases.  University and college press releases typically appear without any person listed as the author. So when a lie occurs (as it very often does), you can never point the figure and identify one particular person who was lying.  When PR men at universities are thinking to themselves "no one will blame me specifically if the press release has an error," they will feel more free to say misleading and untrue things that make unimpressive research sound important.  

 

Misleading press releases produce an indirect financial benefit for the colleges and universities that release them.  When there occurs untrue announcements of important research results, such press releases make the college and university sound like some place where important research is being done. The more such press releases appear, the more people will think that the college or university is worth the very high tuition fees it charges. 

Judging from the quote below, it seems that science journalists often look down on the writers of university and college press releases, even though such science journalists very often uncritically parrot the claims of such people.  In an Undark.org article we read this:

"Still, there are young science journalists who say they would rather be poor than write a press release. Kristin Hugo, for example, a 26-year-old graduate of Boston University’s science journalism program, refuses to step into a communications role with an institution, nonprofit or government agency.  'I’ve been lucky enough that I haven’t had to compromise my integrity. I really believe in being non-biased and non-partisan,' she says. 'I really, really, really want to continue that. I wouldn’t necessarily begrudge someone for going into [public relations] because there’s money in that, but I’d really like to stay out of it.' "

Let us look at the latest bad joke in the long-running comedy series entitled Neuroscience Press Releases. It is a press release with the untrue title "Neural Prosthetic Device Can Help Humans Restore Memory." We hear this untrue claim: "A team of scientists from Wake Forest University School of Medicine and the University of Southern California (USC) have demonstrated the first successful use of a neural prosthetic device to recall specific memories." Near the front of the press release is a reference to a scientific paper. The paper is a bottom-of-the-barrel kind of affair that fails to document any results greater than you should expect from mere chance, given several groups of researchers trying methods like the method tried, even if the methods all had zero effectiveness. 

The paper (which can be read in full here) is entitled "Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall of stimulus features and categories." In the "Main Results" section the paper states this about its tests with 14 subjects:

"Across all subjects, the stimulated trials exhibited significant changes in performance in 22.4% of patient and category combinations. Changes in performance were a combination of both increased memory performance and decreased memory performance, with increases in performance occurring at almost 2 to 1 relative to decreases in performance."

This does not sound like an impressive result at all.  If I were to tell 14 people to guess whether it will be sunny or cloudy in particular states on the first of next month, and then I asked them to do the same task for the 15th of the month, while they were holding a rabbit's foot, I might easily find that the number of people who did better with the rabbit's foot was twice as high as the number of people who did worse.  I might expect to get such a result with maybe a 25% probability. 

There is a way to roughly estimate the probability of getting results like those reported in the paragraph above. We have a description of 14 people being tested, and almost twice as many getting an improvement compared to those getting a decline in performance. The probability of this happening by chance is roughly equivalent to the chance of 14 people flipping a coin, and nine of them or more getting heads, and five of them or fewer getting tails; for in that case the number of "good" results are twice as many as the number of "bad" results (if you consider "heads" as the good result).  The Stat Trek binomial probability calculator screen below shows the odds of getting 9 or more "heads" results when flipping 14 coins.  It is 21%. Because the quote above says "almost 2 to 1" rather than "more than 2 to 1," and 9 is more than twice as high as 4, we can slightly round up this probability of 21% to be a probability of about 25%. 

So some neuroscientist reporting a result like the one mentioned above does nothing to show that anything more than chance was involved.  What we should always remember is that neuroscientists are free to do multiple tests, and file away in their file drawers tests that fail completely, producing only results expected by mere chance.  Also, there are many thousands of experimental neuroscientists who spend half of their time trying to produce impressive results; and very many journals have "publication bias" under which they only publish positive results. So we never should regard some result that could very easily have been produced by mere chance as a result telling us something about the brain or about the effectiveness of some medical intervention, particularly if such a result is not a well-replicated result. Getting something with a chance likelihood of about 25% is an utterly unimpressive result that does basically nothing to indicate that something more than chance was involved. 

The diagram below illustrates why getting a result with a chance likelihood of about 25% does basically nothing to show that some medical device is effective. The red N letters are a negative results, and the green P's are a positive result.  In the case shown below, reports of a positive effect get published, even though 9 out of 10 experiments failed to show the effect.  

Figure 4 of the "Developing a hippocampal neural prosthetic..." paper gives us a "heat map" of the results, shown below. The gray squares represent cases of "no significant change." The yellow, orange, brown and purple squares represent a negative change in memory performance. The blue squares represent a positive change in memory performance. No one making a brief study of the chart below will notice any difference. The amount of negative change seems like about the same as the amount of positive change. 

The authors then confess to us about the miserably bad statistical power of their results.  The "rule of thumb" used in experimental studies is that to reach a statistical power considered "good," you need to get what is called a statistical power of at least 80%. But the authors confess their results have a statistical power of only 10%.  

Such results have no persuasive power. They are results that are not good evidence for anything. The authors give this pitiful-sounding bit of excuse making for their poor results:

"With respect to the low overall statistical power, achieving high power would require an extremely large number of trials, which would take over an order of magnitude more time with a patient than what is possible in a clinical setting due to the time allotted for experiments. Within the clinical restrictions, and without causing undue fatigue on the patients, this experiment has run the maximum number of trials that was able to be performed with each patient. This is a restriction that is inherent with working with not only a patient population, but also the low number of overall trials compliant with a memory task (e.g., Suthana et al., 2012; Ezzyat et al., 2018) required to perform these types of experiments. Further, due to the relatively small nature of the patient population undergoing procedures which require the implantation of neural electrodes, this study, with an n of 14, has a relatively large patient population compared to many published neurostimulation papers. The low statistical power and limited patient group is therefore not unique to our lab or experiment, but also applies to other research that has been published in this area."

 

The excuses are not valid. If the device they created had worked, you would not have needed to run ten times as many trials on the 14 subjects used. In such a case good statistical power would have been demonstrated with the same number of trials.  As for the last sentence, it is equivalent to saying, "Yes, our results are pitiful, but all the other experiments like ours produce results equally pitiful." 

Now, there's nothing wrong with producing an unsuccessful study that fails to produce any decent evidence of memory improvement by electronic means. The only sin is if you boast about such a result, and produce an untrue press release shamelessly making the false claim  that you have produced a device that can "help humans restore memory." And that is exactly what Wake Forest University School of Medicine did. They have described a very unconvincing experimental result as evidence that someone created a device that can "help humans restore memory." It's just another example of what goes on every day in the world of science news: colleges, universities and other institutions making false boasts about achieving scientific goals they did not actually achieve. The epidemic of misleading statements in university press releases is an epidemic that continues to rage full blast, and you will find some of its worst examples in press releases about biology and medicine.

If I were to do a visual giving a proper metaphor for the type of boasting that went on in the press release described above, the kitten would have to be so small you couldn't even recognize it as a kitten. 

Postscript: The tendency of university press releases to make groundless boasts about biology and medicine accomplishments is also shown in a recent press release entitled "Research team uncovers universal code driving the formation of all cell membranes." We have a press release with what sounds like some runaway groundless boasting:

"The theory describes how membranes are compartmentalized, remodeled and regulated, and provides a basis for understanding fundamental questions such as how life is formed at conception, how viruses invade cells and how neurons send signals for feeling, thought and action....'We feel that this represents a conceptual revolution that is akin to the discovery of the genetic code,' says Overduin. 'We're the first to see the overall forest from the trees.... It's remarkable that an undergraduate student can come up with a new code that turns biology upside down and allows us to make sense of it in a radically new way.' "

This all seems very much like groundless boasting, and a look at the scientific paper provides no evidence that anything new has been discovered. Finding a new code used by cells comparable to the genetic code would involve discovering some new repository of information that used repeated symbolic tokens in a systematic way, involving some scheme of representation comparable to the Morse Code or the genetic code. The authors prevent no evidence they have discovered any such thing. All we have in the paper is some very woolly speculation not well-supported by any observations. The press release statements sound like runaway illusions of grandeur not justified by any observations. 

But that's how university press releases are these days. The rule is: "anything goes" when it comes to boasting. 

Why the Academia Cyberspace Profit Complex Keeps Giving Misleading Brain Research Reports

Why do so many untrue and misleading stories about brains and minds appear in the press? The answer is largely a financial one: because various parties profit from such misleading stories. Using the famous "follow the money" slogan in the main movie about the Watergate affair (All the President's Men), let us "follow the money" and see how various parties profit from misleading stories about brains and minds in the press. 

The interesting diagram below illustrates a profit complex that links academia and cyberspace (a word that means the same as the Internet). 

To understand this profit complex, you must first understand how modern scientists are judged by their peers and superiors in academia. There are two numbers by which scientists are judged: (1) the number of scientific articles that the scientist has written or co-written, called the paper count; (2) the number of other papers that have mentioned or cited one of the papers the scientist has written or co-written, called the citation count. If you are a scientist hoping for a promotion such as tenure or a higher salary, you very much want these numbers to be as high as possible. 

The desire to raise such numbers (for the benefit of a scientist) is very much a factor when a scientist designs an experiment. Given the choice between some "quick and dirty" experimental design that will be likely to produce some result that is either a quick and easy result or a positive result or a result that can be claimed as some important result, and some other design that involves some more stringent research method that is longer, harder, or less likely to result in a positive result or a result that can be claimed as important, a scientist who is very interested in increasing his paper count and his citation count will be more likely to choose the "quick and dirty" design.  Such "quick and dirty" designs will very often involve way-too-small sample sizes, in which fewer than 15 subjects are studied (often for studies in which many dozens, hundreds or thousands of subjects would be needed if you wanted to get a reliable result).  A scientific study found that research papers that failed to replicate were on average 153 times more likely to be cited than papers describing research that replicated, stating this: "papers that replicate are cited 153 times less, on average, than papers that do not." Such failing-to-replicate studies typically involve shoddy "quick and dirty" experimental designs. 

Nowadays science journals have a tendency called "publication bias," which is a tendency to publish papers reporting positive results and reject papers reporting null or negative results.  When a scientist does an experiment that produces a null or negative result, and is not able to get a journal to publish the paper, the scientist's paper count is not increased, and the effort does nothing to advance the scientist's career. So scientists will avoid very careful and stringent designs less likely to result in a paper reporting a positive result, and will be more likely to create "quick and dirty" designs more likely to result in a positive result and more likely to result in a positive result that can be produced more quickly.  The quicker the experiment can be done, the more quickly can the scientist's paper count be increased. 

After creating this design, some observations are produced. Desiring to report some positive result and ideally some important-sounding result, scientists will tend to filter or segregate the observations to produce some subset that is more favorable to the reporting of a positive and interesting-sounding result. Sometimes this process can be described as cherry-picking, and other times this process is something rather along the lines of "keep slicing and dicing the data until it gives what is wanted" or "keep torturing the data until it confesses."  There are 101 reasons that can be given for excluding some data points and keeping other data points. There are also hundreds of statistical methods that can be used to massage and filter data until you are left with more favorable results.  In this analysis of data, scientists will have a motivation not to use blind analysis techniques that minimize the chance of biased analysis in which scientists report seeing what they want to see. 

After such analysis is completed, there comes the writing of a scientific paper.  When writing up a scientific paper, scientists are very motivated to describe the research as showing some positive result, even if the research has mainly or entirely produced a negative or null result. This is because scientists want to increase their paper count (the number of published papers they have authored or co-authored); and given publication bias in which journals tend to reject papers reporting only negative results, a paper reporting a negative result may be unlikely to be published. Scientists will also be very motivated to report getting some important result. The more that a scientist tends to claim that some important result was produced by the research, the more likely will be the publication of the paper. Also, the more important the result that is claimed, the more likely the paper will be to be cited by other papers. Such citations are extremely important to scientists, as scientists are judged not just by their paper count (the number of papers they have written), but also by their citation count (the number of times such papers have been cited). 

It very often happens that in writing up papers describing their research, scientists make claims that are misleading, exaggerated or just plain false. At a blog entitled "Survival Blog for Scientists" and subtitled "How to Become a Leading Scientist," a blog that tells us  "contributors are scientists in various stages of their career," we have an explanation of why so many science papers have inaccurate titles:

"Scientists need citations for their papers....If the content of your paper is a dull, solid investigation and your title announces this heavy reading, it is clear you will not reach your citation target, as your department head will tell you in your evaluation interview. So to survive – and to impress editors and reviewers of high-impact journals,  you will have to hype up your title. And embellish your abstract. And perhaps deliberately confuse the reader about the content."

Is this how scientists are trained?

A neuroscientist makes this confession:

"This system comes with big problems. Chief among them is the issue of publication bias: reviewers and editors are more likely to give a scientific paper a good write-up and publish it in their journal if it reports positive or exciting results. So scientists go to great lengths to hype up their studies, lean on their analyses so they produce 'better' results, and sometimes even commit fraud in order to impress those all-important gatekeepers."

After a scientific paper has been written up and published, it is announced with a press release issued by the main academic institution involved in the research. Nowadays the press releases of universities and colleges are notorious for making sensationalized claims that are not warranted by anything discovered in the research being discovered. Often a tentative claim made in a scientific paper (basically a "perhaps" or a "maybe") will be stated as if it is was simply a discovery of a definite fact.  Other times a university press release will make some important-sounding claim that was never made in the scientific paper writing up the research.  An example was that when  there appeared a scientific paper merely claiming that "Regional synapse gain and loss accompany memory formation in larval zebrafish," there appeared a great number of press stories repeating the headline of a press release claiming that the formation of a memory had been observed (a claim not made in the paper).  We have every reason to believe that synapse gains and losses occur  continually in the human body, regardless of whether some new memory is forming. 

Authorship anonymity is a large factor that facilitates the appearance of misleading university and college press releases.  Nowadays university and college press releases typically appear without any person listed as the author. So when a lie occurs (as it very often does), you can never point the figure and identify one particular person who was lying.  When PR men at universities are thinking to themselves "no one will blame me specifically if the press release has an error," they will feel more free to say misleading and untrue things that make unimpressive research sound important.  We should always hold every single scientist involved in a scientific paper responsible and accountable for every untruth that appears in a scientific paper they co-authored and also ever untruth that appears in the university press release announcing the paper, unless that scientist has publicly protested the misstatement. 

 

Misleading press releases produce an indirect financial benefit for the colleges and universities that release them.  When there occurs untrue announcements of important research results, such press releases make the college and university sound like some place where important research is being done. The more such press releases appear, the more people will think that the college or university is worth the very high tuition fees it charges. 

Judging from the quote below, it seems that science journalists often look down on the writers of university and college press releases, even though such science journalists very often uncritically parrot the claims of such people.  In an Undark.org article we read this:

"Still, there are young science journalists who say they would rather be poor than write a press release. Kristin Hugo, for example, a 26-year-old graduate of Boston University’s science journalism program, refuses to step into a communications role with an institution, nonprofit or government agency.  'I’ve been lucky enough that I haven’t had to compromise my integrity. I really believe in being non-biased and non-partisan,' she says. 'I really, really, really want to continue that. I wouldn’t necessarily begrudge someone for going into [public relations] because there’s money in that, but I’d really like to stay out of it.' "

Misleading press releases also help to sustain cyberspace profit systems outside of a college or university. Such press releases are repeated (often with further exaggerations and misstatements) by a host of web sites offering clickbait headlines leading to web pages containing ads. The more people click on these clickbait headlines, the more page views there are for pages containing ads. The more people view those pages, the more advertising revenue the web sites get. 

So web sites giving science news stories have a very large financial incentive to produce exaggerated or untrue headlines that users will be more likely to click on.  If the headline on a web page truthfully says, "Another Junk Science Brain-Scanning Result," almost no one will click on the headline to go to the page with the story containing ads. But if the headline untruthfully says, "Breakthrough Study Reveals the Secret of Memory," then thousands of people may click on the headline, producing many pages views of the story the link leads to, and much more advertising revenue. 

The web sites are one profit center benefiting from poor and misleading science journalism that exaggerates or misrepresents unimpressive research. Another profit center is the science journalists themselves. Most science journalist do not work on some salary basis in which they are paid the same annual salary regardless of what they write. Instead most science journalists work on a per-article basis, earning about $1 per word for an article in a print magazine such as Discover Magazine, or about $300 per article for an online article. Such journalists tend to pitch their stories to editors. The more sensational sounding the story, and the more exciting the claims made, the more likely the story will be to get published.  An article that applies critical scrutiny to some impressive-sounding press release claim will be unlikely to be published.  By uncritically parroting unfounded but exciting-sounding claims in university and college press releases,  science journalists help to fatten their own wallets.  Often science journalists will imaginatively add their own unwarranted claims and unjustified spin about some research, hoping to further increase their chances of receiving fees for writing exciting-sounding news stories.  In general, science journalists getting paid by word or by article are often very unreliable sources of information.  

To "follow the money" all the way, we must go back to the scientists who originally chose "quick and dirty" designs, and who may have misstated the implications and findings coming from their research. What is the result when "quick and dirty" experiment designs are chosen? The result is that the paper count (the number of published papers) of a scientist will increase more quickly. What is the result when scientists misstate or exaggerate what their observations show or imply, making their research sound important when it is not? The result is a greater number of citations of their papers by other scientists. The very important "citation count" of a scientist will increase.  What is the financial result when a scientist has piled up a high paper count and a high citation count? That scientist will be more likely to get promoted, more likely to get the tenure that gives him a lifetime job, more likely to get a higher salary, more likely to get a lucrative book deal with a major publisher, and so forth. 

What we have is an infrastructure that all over the place incentivizes bad agents who mislead and misinform, as long as such persons mislead and misinform in some way that produces exciting-sounding results that fit in with popular academia belief systems.  Given such an infrastructure, you should not be surprised to hear that today's cognitive neuroscience is a house of cards that mostly rests on an illusory foundation. Most of the things that neuroscientists claim have been established by cognitive neuroscientists have not actually been established by them at all. Most of the more important-sounding claims made in the neuroscience news stories of recent years are claims lacking any solid foundation in observations. Junk science flourishes, because there are so many people in so many different places who profit from junk science. 

Inaccurate Titles and Misleading Citations Are Common in Science Papers

 I have discussed at some length on this blog problems in science literature such as poor study design, insufficient study group size, occasional fraud, misleading visuals and unreliable techniques for fear measurement. Such things are only some of the many problems to be found in neuroscience papers. Two other very common problems are:

(1) Scientific papers often have inaccurate titles, making some claim that is not actually proven or substantiated by the research discussed in the paper.

(2) Scientific papers often make misleading citations to papers that did nothing to show the claim being made. 

Regarding the first of these problems, scientists often write inaccurate titles to try to get more citations for their papers. For the modern scientist, the number of citations for papers he or she wrote is a supremely important statistic, regarded as a kind of numerical "measure of worth" as important as the batting average or RBI statistic is for a baseball hitter. At a blog entitled "Survival Blog for Scientists" and subtitled "How to Become a Leading Scientist," a blog that tells us  "contributors are scientists in various stages of their career," we have an explanation of why so many science papers have inaccurate titles:

"Scientists need citations for their papers....If the content of your paper is a dull, solid investigation and your title announces this heavy reading, it is clear you will not reach your citation target, as your department head will tell you in your evaluation interview. So to survive – and to impress editors and reviewers of high-impact journals,  you will have to hype up your title. And embellish your abstract. And perhaps deliberately confuse the reader about the content."

Is this how today's scientists are trained?

A study of inaccuracy in the titles of scientific papers states, "23.4 % of the titles contain inaccuracies of some kind."

The concept of a misleading citation is best explained with an imaginary example.  In a scientific paper we may see some line such as this:

Research has shown that the XYZ protein is essential for memory.³⁴

Here the number 34 refers to some scientific paper listed at the end of the scientific paper. Now, if the paper listed as paper #34 actually is a scientific paper showing the claim in question, that this XYZ protein is essential for memory, then we have a sound citation. But imagine if the paper does not show any such thing. Then we have a misleading citation.  We have been given the wrong impression that something was established by some other science paper. 

A recent scientific paper entitled "Quotation errors in general science journals" tried to figure out how common such misleading citations are in science papers.  It found that such erroneous citations are not at all rare. Examining 250 randomly selected citations, the paper found an error rate of 25%.  We read the following:

"Throughout all the journals, 75% of the citations were Fully Substantiated. The remaining 25% of the citations contained errors. The least common type of error was Partial Substantiation, making up 14.5% of all errors. Citations that were completely Unsubstantiated made up a more substantial 33.9% of the total errors. However, most of the errors fell into the Impossible to Substantiate category."

When we multiply the 25% figure by 33.9%, we find that according to the study, 8% of citations in science papers are completely unsubstantiated. That is a stunning degree of error. We would perhaps expect such an error rate from careless high-school students, but not from careful scientists. 

This 25% citation error rate found by the study is consistent with other studies on this topic. In the study we read this:

"In a sampling of 21 similar studies across many fields, total quotation error rates varied from 7.8% to 38.2% (with a mean of 22.4%) ...Furthermore, a meta-analysis of 28 quotation error studies in medical literature found an overall quotation error rate of 25.4% [1]. Therefore, the 25% overall quotation error rate of this study is consistent with the other studies."

In the paper we also read the following: "It has been argued through analysis of misprints that only about 20% of authors citing a paper have actually read the original."  If this is true, we can get a better understanding of why so much misinformation is floating around in neuroscience papers.  We repeatedly have paper authors spreading legends of scientific achievement, which are abetted by incorrect paper citations often made by authors who have not even read the papers they are citing.  

A recent article at Vox.com suggests that scientists are just as likely to make citations to bad research that can't be replicated as they are to make citations to good research. We read the following:

"The researchers find that studies have about the same number of citations regardless of whether they replicated. If scientists are pretty good at predicting whether a paper replicates, how can it be the case that they are as likely to cite a bad paper as a good one? Menard theorizes that many scientists don’t thoroughly check — or even read — papers once published, expecting that if they’re peer-reviewed, they’re fine. Bad papers are published by a peer-review process that is not adequate to catch them — and once they’re published, they are not penalized for being bad papers."

We also read the following troubling comment:

"Blatantly shoddy work is still being published in peer-reviewed journals despite errors that a layperson can see. In many cases, journals effectively aren’t held accountable for bad papers — many, like The Lancet, have retained their prestige even after a long string of embarrassing public incidents where they published research that turned out fraudulent or nonsensical...Even outright frauds often take a very long time to be repudiated, with some universities and journals dragging their feet and declining to investigate widespread misconduct."

A Diagram of Explanatory Dysfunction in Academia

Below is a diagram that attempts to illustrate some of the explanatory problems afflicting colleges and universities. A major factor in such problems are what we may call achievement legends.

       Click to open in a separate tab                 

An achievement legend is a story that is repeatedly told in the classrooms of colleges and universities, a story claiming without proof that some wonderful progress was made by scientists. Such legends include the ones below and many others:

• The story that the origin of species and the origin of humanity were successfully explained by the nineteenth century biologist Charles Darwin.
  
• The story that neuroscientists have been able to figure out where the human mind comes from and how human memory works, by studying the human brain.
  
• The story that the “book of life” was discovered in the middle of the twentieth century, when scientists found some molecule that contained a blueprint or recipe for making human beings.
  
• The story that scientists have been been able to figure out important truths about the evolution of the universe, by coming up with ideas such as dark matter and primordial exponential cosmic inflation (not to be confused with ordinary expansion).
  

All of these stories meet the definition of legend, which is “a traditional story sometimes regarded as historical but unauthenticated.” None of these claims of achievement has been proven. There are very substantial reasons for rejecting each one of them. But these stories of great achievements keep being told again and again by our professors. One of the hardest things to dispel is a dubious achievement legend once it has spread. Such legends provide prestige boosts to various people in academia, and once a person has been hooked on an intoxicating conceit, it becomes incredibly hard for such a person to give it up and adopt a more realistic viewpoint about his relatively modest state of knowledge.

These achievement legends are pillars of a worldview that is predominant at colleges and universities. The worldview is based on the idea that the most important realities such as life and mind are explained by matter, and that such realities arose from blind accidental processes. Believing in the smug achievement legends, those who hold this worldview believe that scientists are making excellent progress in coming up with purely material explanations for life and mental phenomena.

But such a worldview is contradicted by a gigantic number of observational facts. Such facts and observations can be divided into two different categories: the paranormal and the not-at-all-spooky. In the paranormal category are a host of observations that mainstream professors may dismiss as “impossible,” even though they are massively reported. These include things such as apparition sightings, deathbed visions, near-death experiences, anecdotal accounts of clairvoyance, extremely high scores on tests of extrasensory perception (such as we would never expect any human to get by chance), photos of dramatic recurring patterns in mysterious orbs, and so forth. But there is also a huge number of "not at all spooky" observations that stand in opposition to the prevailing academic worldview. Among these are observations such as these:

1. Low-level observations indicating that DNA does not have and cannot have a blueprint or recipe for making a human.
   
2. Innumerable observations of incredibly organized biological complexity vastly more fine-tuned than anything that can reasonably be explained as a result of chance.
   
3. Observations proving that brain tissue does not have the long-term information storage capability it would need to have if prevailing ideas about brains and minds are correct.
   
4. Observations proving that massive damage to brains often has only slight effects on mind and memory, contrary to what we would expect under the dogma that the mind is merely the product of the brain, and the dogma that memories are stored in brains.
   
5. Observations establishing that the universe has many types of physical fine-tuning such as we would not expect under prevailing academic assumptions.
   

These are part of a massive body of evidence that defies and discredits the worldview prevailing among the professors of academia. But such professors do a very good job of keeping their classrooms and journals and textbooks as places where such evidence is not discussed. Professors exert a kind of de facto censorship in which such opposing evidence is excluded from the sheltered world of academia. The “no entry” symbols in my diagram illustrate this type of de facto censorship.

The evidence I just discussed gives rise to contrarian viewpoints that differ from the prevailing worldview held by academic professors. But there is little or no fair discussion of such contrarian viewpoints in the regimented literature and classroom presentations of academia. If there is any discussion of such viewpoints, an academic authority will typically make sure to label the contrarian thinkers with various defamatory or deprecatory labels designed to prevent anyone from taking their opinions seriously.

Academia produces a huge flow of research and literature. But the research and literature is largely what I call dogma-driven. Dogma-driven research is research designed to reassure professors that they are on the right track, and that their grand explanatory pretensions are justified. Examples include the following:

• Innumerable papers presenting different variations of Guth's theory of primordial cosmic inflation, most of which are designed to bolster our confidence in such a theory.
  
• Innumerable papers speculating about dark matter and dark energy, two things that have never been observed.
  
• Countless papers trying to shore up the doctrine of common descent, by presenting 1001 different scenarios describing inheritance paths that life could have taken to progress through Darwinian evolution.
  
• Thousands of brain scanning studies, designed to provide evidence for claims that the brain is the source of mental phenomena or the storage place of memories.
  
• Thousands of papers presenting variations of the unverified theory of supersymmetry.
  

Theory-biased analysis occurs both in journals and in textbooks. The observational facts are all passed through the prism of existing theories, which are often based on smug achievement legends. There will be either no discussion of a vast number of observational facts conflicting with such theories, or the discussion will be very skimpy and jaundiced. Reasonable alternative explanations will not be discussed, or will be discussed in some skimpy deprecatory manner. 

The result of such research is all too often unimpressive. A significant fraction of all research findings reported in scientific journals cannot be reproduced. The problem was highlighted in a widely cited 2005 paper by John Ioannidis entitled, “Why Most Published Research Studies Are False.” 

A scientist named C. Glenn Begley and his colleagues tried to reproduce 53 published studies called “ground-breaking.” He asked the scientists who wrote the papers to help, by providing the exact materials to publish the results. Begley and his colleagues were only able to reproduce 6 of the 53 experiments. In 2011 Bayer reported similar results. They tried to reproduce 67 medical studies, and were only able to reproduce them 25 percent of the time.

But a reader of science news sites would hardly guess that such problems exist. Every week such sites seem to report a glorious march of progress, and make it sound as if wonderful breakthroughs are occurring almost every week.  The problem is that weak scientific research and analysis is uncritically trumpeted.

Part of the problem is university press offices, which nowadays are shameless in exaggerating the importance of research done at their university. They know the more some locally arising scientific research is hyped, the more glory and attendees will flow to their university.

A scientific paper reached the following conclusions, indicating a huge hype and exaggeration crisis both among the authors of scientific papers and the media that reports on such papers:

"Thirty-four percent of academic studies and 48% of media articles used language that reviewers considered too strong for their strength of causal inference....Fifty-eight percent of media articles were found to have inaccurately reported the question, results, intervention, or population of the academic study."

Exacerbating this problem is an economic situation in which there is a huge monetary motivation for hyping second-rate research, to make it sound like some glorious breakthrough. Web sites that report science news have ads on their pages. The more users click on a particular page, the more money the web site makes from ad revenue. Given such a situation, there is a huge motivation for web sites to hype science research.  You won't click on some headline of "Another doubtful animal study with too small a sample." But you may click on a misleading headline of, "Amazing study unveils the secret of how memory works."  And once you make such a click, some web site will make money from some ad on the page you clicked on. So the science news hype and exaggeration keeps flowing full blast. 

Almost every day in the science news you can find examples of hyped-up headlines that are inaccurate. The glaring example I find on today's ScienceDaily.com is a story with the extremely false headline "Strongest evidence yet that neutrinos explain how the universe exists." The long-standing matter-antimatter asymmetry mystery is that the Big Bang should have produced equal amounts of matter (protons and electrons) and antimatter (antiprotons and positrons), in incredible densities denser than a neutron star. Since matter and antimatter destroy each other upon contact, forming into only photons of energy,  the Big Bang should have left nothing but photons of energy.  This problem cannot at all be solved by any possible finding about neutrinos, mere "ghost particles" that are millions of times less massive than electrons, which are 1836 times less massive than protons. When you read the story you will find zero evidence justifying the headline. 

In many an area of science, researchers are mostly spinning their wheels, making little progress.  A hundred promising leads are not being followed up, because professors don't want to find out about what such leads suggest, which is often that the cherished tenets of such professors are dead wrong. Meanwhile there are endless poor papers inspired by dubious theories, because professors want to be reassured that they are on the right track, and that their beloved dogmas are correct. Much too little real explanatory progress is being made, but you would never know it from reading the "hype almost anything that moves" science press, which seems to trumpet almost any dubious "glorify our guys" press release coming from a university press office, while only very rarely applying critical scrutiny to such claims.