Connect with us
[the_ad id="89560"]

Brownstone Institute

The Global War on Thought Crime

Published

9 minute read

From the Brownstone Institute

BY David JamesDAVID JAMES  

Laws to ban disinformation and misinformation are being introduced across the West, with the partial exception being the US, which has the First Amendment so the techniques to censor have had to be more clandestine.

In Europe, the UK, and Australia, where free speech is not as overtly protected, governments have legislated directly. The EU Commission is now applying the ‘Digital Services Act’ (DSA), a thinly disguised censorship law.

In Australia the government is seeking to provide the Australian Communications and Media Authority (ACMA) with “new powers to hold digital platforms to account and improve efforts to combat harmful misinformation and disinformation.”

One effective response to these oppressive laws may come from a surprising source: literary criticism. The words being used, which are prefixes added to the word “information,” are a sly misdirection. Information, whether in a book, article or post is a passive artefact. It cannot do anything, so it cannot break a law. The Nazis burned books, but they didn’t arrest them and put them in jail. So when legislators seek to ban “disinformation,” they cannot mean the information itself. Rather, they are targeting the creation of meaning.

The authorities use variants of the word “information” to create the impression that what is at issue is objective truth but that is not the focus. Do these laws, for example, apply to the forecasts of economists or financial analysts, who routinely make predictions that are wrong? Of course not. Yet economic or financial forecasts, if believed, could be quite harmful to people.

The laws are instead designed to attack the intent of the writers to create meanings that are not congruent with the governments’ official position. ‘Disinformation’ is defined in dictionaries as information that is intended to mislead and to cause harm. ‘Misinformation’ has no such intent and is just an error, but even then that means determining what is in the author’s mind. ‘Mal-information’ is considered to be something that is true, but that there is an intention to cause harm.

Determining a writer’s intent is extremely problematic because we cannot get into another person’s mind; we can only speculate on the basis of their behaviour. That is largely why in literary criticism there is a notion called the Intentional Fallacy, which says that the meaning of a text cannot be limited to the intention of the author, nor is it possible to know definitively what that intention is from the work. The meanings derived from Shakespeare’s works, for example, are so multifarious that many of them cannot possibly have been in the Bard’s mind when he wrote the plays 400 years ago.

How do we know, for example, that there is no irony, double meaning, pretence or other artifice in a social media post or article? My former supervisor, a world expert on irony, used to walk around the university campus wearing a T-shirt saying: “How do you know I am being ironic?” The point was that you can never know what is actually in a person’s mind, which is why intent is so difficult to prove in a court of law.

That is the first problem. The second one is that, if the creation of meaning is the target of the proposed law – to proscribe meanings considered unacceptable by the authorities – how do we know what meaning the recipients will get? A literary theory, broadly under the umbrella term ‘deconstructionism,’ claims that there are as many meanings from a text as there are readers and that “the author is dead.”

While this is an exaggeration, it is indisputable that different readers get different meanings from the same texts. Some people reading this article, for example, might be persuaded while others might consider it evidence of a sinister agenda. As a career journalist I have always been shocked at the variability of reader’s responses to even the most simple of articles. Glance at the comments on social media posts and you will see an extreme array of views, ranging from positive to intense hostility.

To state the obvious, we all think for ourselves and inevitably form different views, and see different meanings. Anti-disinformation legislation, which is justified as protecting people from bad influences for the common good, is not merely patronising and infantilising, it treats citizens as mere machines ingesting data – robots, not humans. That is simply wrong.

Governments often make incorrect claims, and made many during Covid.

In Australia the authorities said lockdowns would only last a few weeks to “flatten the curve.” In the event they were imposed for over a year and there never was a “curve.” According to the Australian Bureau of Statistics 2020 and 2021 had the lowest levels of deaths from respiratory illness since records have been kept.

Governments will not apply the same standards to themselves, though, because governments always intend well (that comment may or may not be intended to be ironic; I leave it up to the reader to decide).

There is reason to think these laws will fail to achieve the desired result. The censorship regimes have a quantitative bias. They operate on the assumption that if a sufficient proportion of social media and other types of “information” is skewed towards pushing state propaganda, then the audience will inevitably be persuaded to believe the authorities.

But what is at issue is meaning, not the amount of messaging. Repetitious expressions of the government’s preferred narrative, especially ad hominem attacks like accusing anyone asking questions of being a conspiracy theorist, eventually become meaningless.

By contrast just one well-researched and well-argued post or article can permanently persuade readers to an anti-government view because it is more meaningful. I can recall reading pieces about Covid, including on Brownstone, that led inexorably to the conclusion that the authorities were lying and that something was very wrong. As a consequence the voluminous, mass media coverage supporting the government line just appeared to be meaningless noise. It was only of interest in exposing how the authorities were trying to manipulate the “narrative” – a debased word was once mainly used in a literary context – to cover their malfeasance.

In their push to cancel unapproved content, out-of-control governments are seeking to penalise what George Orwell called “thought crimes.” But they will never be able to truly stop people thinking for themselves, nor will they ever definitively know either the writer’s intent or what meaning people will ultimately derive. It is bad law, and it will eventually fail because it is, in itself, predicated on disinformation.


Author

  • David James

    David James, PhD English Literature, is a business and finance journalist with 35 years experience, mainly in Australia’s national business magazine.

Brownstone Institute

Net Zero: The Mystery of the Falling Fertility

Published on

From the Brownstone Institute

By Tomas FurstTomas Fürst  

If you want to argue that a mysterious factor X is responsible for the drop in fertility, you will have to explain (1) why the factor affected only the vaccinated, and (2) why it started affecting them at about the time of vaccination.

In January 2022, the number of children born in the Czech Republic suddenly decreased by about 10%. By the end of 2022, it had become clear that this was a signal: All the monthly numbers of newborns were mysteriously low.

In April 2023, I wrote a piece for a Czech investigative platform InFakta and suggested that this unexpected phenomenon might be connected to the aggressive vaccination campaign that had started approximately 9 months before the drop in natality. Denik N – a Czech equivalent of the New York Times – immediately came forward with a “devastating takedown” of my article, labeled me a liar and claimed that the pattern can be explained by demographics: There were fewer women in the population and they were getting older.

To compare fertility across countries (and time), the so-called Total Fertility Rate (TFR) is used. Roughly speaking, it is the average number of children that are born to a woman over her lifetime. TFR is independent of the number of women and of their age structure. Figure 1 below shows the evolution of TFR in several European countries between 2001 and 2023. I selected countries that experienced a similar drop in TFR in 2022 as the Czech Republic.

Figure 1. The evolution of Total Fertility Rate in selected European countries between 2000 and 2023. The data corresponding to a particular year are plotted at the end of the column representing that year.

So, by the end of 2023, the following two points were clear:

  1. The drop in natality in the Czech Republic in 2022 could not be explained by demographic factors. Total fertility rate – which is independent of the number of women and their age structure – dropped sharply in 2022 and has been decreasing ever since. The data for 2024 show that the Czech TFR has decreased further to 1.37.
  1. Many other European countries experienced the same dramatic and unexpected decrease in fertility that started at the beginning of 2022. I have selected some of them for Figure 1 but there are more: The Netherlands, Norway, Slovakia, Slovenia, and Sweden. On the other hand, there are some countries that do not show a sudden drop in TFR, but rather a steady decline over a longer period (e.g. Belgium, France, UK, Greece, or Italy). Notable exceptions are Bulgaria, Spain, and Portugal where fertility has increased (albeit from very low numbers). The Human Fertility Project database has all the numbers.

This data pattern is so amazing and unexpected that even the mainstream media in Europe cannot avoid the problem completely. From time to time, talking heads with many academic titles appear and push one of the politically correct narratives: It’s Putin! (Spoiler alert: The war started in February 2022; however, children not born in 2022 were not conceived in 2021). It’s the inflation caused by Putin! (Sorry, that was even later). It’s the demographics! (Nope, see above, TFR is independent of the demographics).

Thus, the “v” word keeps creeping back into people’s minds and the Web’s Wild West is ripe with speculation. We decided not to speculate but to wrestle some more data from the Czech government. For many months, we were trying to acquire the number of newborns in each month, broken down by age and vaccination status of the mother. The post-socialist health-care system of our country is a double-edged sword: On one hand, the state collects much more data about citizens than an American would believe. On the other hand, we have an equivalent of the FOIA, and we are not afraid to use it. After many months of fruitless correspondence with the authorities, we turned to Jitka Chalankova – a Czech Ron Johnson in skirts – who finally managed to obtain an invaluable data sheet.

To my knowledge, the datasheet (now publicly available with an English translation here) is the only officially released dataset containing a breakdown of newborns by the Covid-19 vaccination status of the mother. We requested much more detailed data, but this is all we got. The data contains the number of births per month between January 2021 and December 2023 given by women (aged 18-39) who were vaccinated, i.e., had received at least one Covid vaccine dose by the date of delivery, and by women who were unvaccinated, i.e., had not received any dose of any Covid vaccine by the date of delivery.

Furthermore, the numbers of births per month by women vaccinated by one or more doses during pregnancy were provided. This enabled us to estimate the number of women who were vaccinated before conception. Then, we used open data on the Czech population structure by age, and open data on Covid vaccination by day, sex, and age.

Combining these three datasets, we were able to estimate the rates of successful conceptions (i.e., conceptions that led to births nine months later) by preconception vaccination status of the mother. Those interested in the technical details of the procedure may read Methods in the newly released paper. It is worth mentioning that the paper had been rejected without review in six high-ranking scientific journals. In Figure 2, we reprint the main finding of our analysis.

Figure 2A. Histogram showing the percentage of women in the Czech Republic aged 18–39 years who were vaccinated with at least one dose of a Covid-19 vaccine by the end of the respective month. Figure 2B. Estimates of the number of successful conceptions (SCs) per 1,000 women aged 18–39 years according to their pre-conception Covid vaccination status. The blue-shaded areas in Figure 1B show the intervals between the lower and upper estimates of the true SC rates for women vaccinated (dark blue) and unvaccinated (light blue) before conception.

Figure 2 reveals several interesting patterns that I list here in order of importance:

  1. Vaccinated women conceived about a third fewer children than would be expected from their share of the population. Unvaccinated women conceived at about the same rate as all women before the pandemic. Thus, a strong association between Covid vaccination status and successful conceptions has been established.
  2. In the second half of 2021, there was a peak in the rate of conceptions of the unvaccinated (and a corresponding trough in the vaccinated). This points to rather intelligent behavior of Czech women, who – contrary to the official advice – probably avoided vaccination if they wanted to get pregnant. This concentrated the pregnancies in the unvaccinated group and produced the peak.
  3. In the first half of 2021, there was significant uncertainty in the estimates of the conception rates. The lower estimate of the conception rate in the vaccinated was produced by assuming that all women vaccinated (by at least one dose) during pregnancy were unvaccinated before conception. This was almost certainly true in the first half of 2021 because the vaccines were not available prior to 2021. The upper estimate was produced by assuming that all women vaccinated (by at least one dose) during pregnancy also received at least one dose before conception. This was probably closer to the truth in the second part of 2021. Thus, we think that the true conception rates for the vaccinated start close to the lower bound in early 2021 and end close to the upper bound in early 2022. Once again, we would like to be much more precise, but we have to work with what we have got.

Now that the association between Covid-19 vaccination and lower rates of conception has been established, the one important question looms: Is this association causal? In other words, did the Covid-19 vaccines really prevent women from getting pregnant?

The guardians of the official narrative brush off our findings and say that the difference is easily explained by confounding: The vaccinated tend to be older, more educated, city-dwelling, more climate change aware…you name it. That all may well be true, but in early 2022, the TFR of the whole population dropped sharply and has been decreasing ever since.

So, something must have happened in the spring of 2021. Had the population of women just spontaneously separated into two groups – rednecks who wanted kids and didn’t want the jab, and city slickers who didn’t want kids and wanted the jab – the fertility rate of the unvaccinated would indeed be much higher than that of the vaccinated. In that respect, such a selection bias could explain the observed pattern. However, had this been true, the total TFR of the whole population would have remained constant.

But this is not what happened. For some reason, the TFR of the whole population jumped down in January 2022 and has been decreasing ever since. And we have just shown that, for some reason, this decrease in fertility affected only the vaccinated. So, if you want to argue that a mysterious factor X is responsible for the drop in fertility, you will have to explain (1) why the factor affected only the vaccinated, and (2) why it started affecting them at about the time of vaccination. That is a tall order. Mr. Occam and I both think that X = the vaccine is the simplest explanation.

What really puzzles me is the continuation of the trend. If the vaccines really prevented conception, shouldn’t the effect have been transient? It’s been more than three years since the mass vaccination event, but fertility rates still keep falling. If this trend continues for another five years, we may as well stop arguing about pensions, defense spending, healthcare reform, and education – because we are done. 

We are in the middle of what may be the biggest fertility crisis in the history of mankind. The reason for the collapse in fertility is not known. The governments of many European countries have the data that would unlock the mystery. Yet, it seems that no one wants to know.


Author

Tomas Furst

Tomas Fürst teaches applied mathematics at Palacky University, Czech Republic. His background is in mathematical modelling and Data Science. He is a co-founder of the Association of Microbiologists, Immunologists, and Statisticians (SMIS) which has been providing the Czech public with data-based and honest information about the coronavirus epidemic. He is also a co-founder of a “samizdat” journal dZurnal which focuses on uncovering scientific misconduct in Czech Science.

Continue Reading

Brownstone Institute

FDA Exposed: Hundreds of Drugs Approved without Proof They Work

Published on

From the Brownstone Institute

By Maryanne Demasi

The US Food and Drug Administration (FDA) has approved hundreds of drugs without proof that they work—and in some cases, despite evidence that they cause harm.

That’s the finding of a blistering two-year investigation by medical journalists Jeanne Lenzer and Shannon Brownleepublished by The Lever.

Reviewing more than 400 drug approvals between 2013 and 2022, the authors found the agency repeatedly ignored its own scientific standards.

One expert put it bluntly—the FDA’s threshold for evidence “can’t go any lower because it’s already in the dirt.”

A System Built on Weak Evidence

The findings were damning—73% of drugs approved by the FDA during the study period failed to meet all four basic criteria for demonstrating “substantial evidence” of effectiveness.

Those four criteria—presence of a control group, replication in two well-conducted trials, blinding of participants and investigators, and the use of clinical endpoints like symptom relief or extended survival—are supposed to be the bedrock of drug evaluation.

Yet only 28% of drugs met all four criteria—40 drugs met none.

These aren’t obscure technicalities—they are the most basic safeguards to protect patients from ineffective or dangerous treatments.

But under political and industry pressure, the FDA has increasingly abandoned them in favour of speed and so-called “regulatory flexibility.”

Since the early 1990s, the agency has relied heavily on expedited pathways that fast-track drugs to market.

In theory, this balances urgency with scientific rigour. In practice, it has flipped the process. Companies can now get drugs approved before proving that they work, with the promise of follow-up trials later.

But, as Lenzer and Brownlee revealed, “Nearly half of the required follow-up studies are never completed—and those that are often fail to show the drugs work, even while they remain on the market.”

“This represents a seismic shift in FDA regulation that has been quietly accomplished with virtually no awareness by doctors or the public,” they added.

More than half the approvals examined relied on preliminary data—not solid evidence that patients lived longer, felt better, or functioned more effectively.

And even when follow-up studies are conducted, many rely on the same flawed surrogate measures rather than hard clinical outcomes.

The result: a regulatory system where the FDA no longer acts as a gatekeeper—but as a passive observer.

Cancer Drugs: High Stakes, Low Standards

Nowhere is this failure more visible than in oncology.

Only 3 out of 123 cancer drugs approved between 2013 and 2022 met all four of the FDA’s basic scientific standards.

Most—81%—were approved based on surrogate endpoints like tumour shrinkage, without any evidence that they improved survival or quality of life.

Take Copiktra, for example—a drug approved in 2018 for blood cancers. The FDA gave it the green light based on improved “progression-free survival,” a measure of how long a tumour stays stable.

But a review of post-marketing data showed that patients taking Copiktra died 11 months earlier than those on a comparator drug.

It took six years after those studies showed the drug reduced patients’ survival for the FDA to warn the public that Copiktra should not be used as a first- or second-line treatment for certain types of leukaemia and lymphoma, citing “an increased risk of treatment-related mortality.”

Elmiron: Ineffective, Dangerous—And Still on the Market

Another striking case is Elmiron, approved in 1996 for interstitial cystitis—a painful bladder condition.

The FDA authorized it based on “close to zero data,” on the condition that the company conduct a follow-up study to determine whether it actually worked.

That study wasn’t completed for 18 years—and when it was, it showed Elmiron was no better than placebo.

In the meantime, hundreds of patients suffered vision loss or blindness. Others were hospitalized with colitis. Some died.

Yet Elmiron is still on the market today. Doctors continue to prescribe it.

“Hundreds of thousands of patients have been exposed to the drug, and the American Urological Association lists it as the only FDA-approved medication for interstitial cystitis,” Lenzer and Brownlee reported.

“Dangling Approvals” and Regulatory Paralysis

The FDA even has a term—”dangling approvals”—for drugs that remain on the market despite failed or missing follow-up trials.

One notorious case is Avastin, approved in 2008 for metastatic breast cancer.

It was fast-tracked, again, based on ‘progression-free survival.’ But after five clinical trials showed no improvement in overall survival—and raised serious safety concerns—the FDA moved to revoke its approval for metastatic breast cancer.

The backlash was intense.

Drug companies and patient advocacy groups launched a campaign to keep Avastin on the market. FDA staff received violent threats. Police were posted outside the agency’s building.

The fallout was so severe that for more than two decades afterwards, the FDA did not initiate another involuntary drug withdrawal in the face of industry opposition.

Billions Wasted, Thousands Harmed

Between 2018 and 2021, US taxpayers—through Medicare and Medicaid—paid $18 billion for drugs approved under the condition that follow-up studies would be conducted. Many never were.

The cost in lives is even higher.

A 2015 study found that 86% of cancer drugs approved between 2008 and 2012 based on surrogate outcomes showed no evidence that they helped patients live longer.

An estimated 128,000 Americans die each year from the effects of properly prescribed medications—excluding opioid overdoses. That’s more than all deaths from illegal drugs combined.

A 2024 analysis by Danish physician Peter Gøtzsche found that adverse effects from prescription medicines now rank among the top three causes of death globally.

Doctors Misled by the Drug Labels

Despite the scale of the problem, most patients—and most doctors—have no idea.

A 2016 survey published in JAMA asked practising physicians a simple question—what does FDA approval actually mean?

Only 6% got it right.

The rest assumed that it meant the drug had shown clear, clinically meaningful benefits—such as helping patients live longer or feel better—and that the data was statistically sound.

But the FDA requires none of that.

Drugs can be approved based on a single small study, a surrogate endpoint, or marginal statistical findings. Labels are often based on limited data, yet many doctors take them at face value.

Harvard researcher Aaron Kesselheim, who led the survey, said the results were “disappointing, but not entirely surprising,” noting that few doctors are taught about how the FDA’s regulatory process actually works.

Instead, physicians often rely on labels, marketing, or assumptions—believing that if the FDA has authorized a drug, it must be both safe and effective.

But as The Lever investigation shows, that is not a safe assumption.

And without that knowledge, even well-meaning physicians may prescribe drugs that do little good—and cause real harm.

Who Is the FDA Working for?

In interviews with more than 100 experts, patients, and former regulators, Lenzer and Brownlee found widespread concern that the FDA has lost its way.

Many pointed to the agency’s dependence on industry money. A BMJ investigation in 2022 found that user fees now fund two-thirds of the FDA’s drug review budget—raising serious questions about independence.

Yale physician and regulatory expert Reshma Ramachandran said the system is in urgent need of reform.

“We need an agency that’s independent from the industry it regulates and that uses high-quality science to assess the safety and efficacy of new drugs,” she told The Lever. “Without that, we might as well go back to the days of snake oil and patent medicines.”

For now, patients remain unwitting participants in a vast, unspoken experiment—taking drugs that may never have been properly tested, trusting a regulator that too often fails to protect them.

And as Lenzer and Brownlee conclude, that trust is increasingly misplaced.

Republished from the author’s Substack

 

Author

Maryanne Demasi, 2023 Brownstone Fellow, is an investigative medical reporter with a PhD in rheumatology, who writes for online media and top tiered medical journals. For over a decade, she produced TV documentaries for the Australian Broadcasting Corporation (ABC) and has worked as a speechwriter and political advisor for the South Australian Science Minister.

Continue Reading

Trending

X