Ofcom ‘harmed the public’ in its Covid/Steyn ruling against Mark Steyn

Ofcom ‘harmed the public’ in its Covid/Steyn ruling against Mark Steyn

Pictured: Kathy Gyngell, left; Norman Fenton, second left; Mark Steyn, right.

Kathy Gyngell, the founder and editor of the TCW (The Conservative Woman) website, has published a powerful blog by an expert risk assessment  professor about Ofcom’s and the High Court’s ham-fisted – and arguably dictatorial – role in discrediting Mark Steyn, a courageous campaigning journalist/blogger in highlighting the massive growing concerns about the dangers of the Covid-19 vaccines.

News-watch has been campaigning for more than a decade to make the BBC and Ofcom more accountable for its decisions about impartiality – including its own (ultimately rejected)High Court application for judicial review in 2019 about the BBC’s cavalier rejection of complaints.

The latest developments in the Steyn saga underline that Ofcom, just like the BBC,  makes highly questionable rulings – with itself as judge and jury – which seriously threaten free speech held by the so called ‘right’ in British politics.

Mr Steyn was censured by Ofcom on March 2023 for two broadcasts he made on GB News in 2022. In them, he stated that, despite strong claims to the contrary by the government and the NHS ‘establishment’,  there was unequivocal mounting evidence that the Covid-19 vaccines were potentially a serious danger to the public.

In brief, Ofcom ruled  that the first Steyn show breached its rules as it gave a “materially misleading interpretation” of the figures “without sufficient challenge or counterweight”, which it said risked “harm to viewers”.

Mr Steyn’s application for judicial review was heard at the High Court in June and the sweeping rejection verdict  was handed down at the beginning of this month.

The TCW blog by Norman, Fenton, emeritus professor of risk at the Queen Mary University in London, published in full below, contains a damning rebuttal of the Ofcom evidence against Mr Steyn  and the High Court judge’s ruling.

News-watch also has another application for judicial review – due to be heard in the High Court in February 2025 (after a delay in listing of an unbelievable two years since the application was submitted) – about Ofcom’s rejection of complaints. More details will follow during the autumn.

It was Ofcom, not Mark Steyn, that misled and harmed the public

August 19, 2024

IT’S BEEN three weeks since the judge (Mrs Justice Farbey) in Mark Steyn’s case ruled against him, upholding Ofcom rulings against him for comments made in two of his GB News shows back in 2022. The full judgement can be found here.

One of the Ofcom rulings (claim AC-2023-LON-001656) focused on a programme in which Steyn claimed that UKHSA (UK Health Security Agency) data showed triple-vaccinated people were at much greater risk of contracting, being hospitalised, and dying from covid than unvaccinated people. Ofcom ruled that Steyn misled the public on these claims.

The other ruling (claim AC-2023-LON-002280) focused on a show in which his guest Naomi Wolf made claims about vaccine adverse reactions. Ofcom ruled that these claims were inaccurate, and that Steyn failed in his duty as the presenter to challenge Wolf on them.

The Ofcom rulings led to Steyn losing his job at GB News (while he was in hospital following the second of two heart attacks in quick succession after the rulings). Ofcom, who act as judge and jury, did not allow him to provide any defence against the rulings so he decided to mount a judicial review against their rulings in the High Court.

A couple of weeks before the case went to court on June 11 2024 I was asked to provide a report about the statistical issues in the case. As the claim regarding the Naomi Wolf programme was not about statistics, I focused entirely on the claim made against Steyn regarding the UKHSA data. My findings bear on Mrs Justice Farbey’s final decision (point 106 relating to claim AC-2023-LON-001656) that: Ofcom was not ‘obviously wrong’ to insist that broadcasters avoid the risk that vaccinated individuals be caused alarm.

 

 

Hence, it is important now to bring the facts into the public domain that show that Ofcom was indeed ‘obviously wrong’. Sadly, it seems the judge did not have these full facts at her disposal.

The full Ofcom complaint against Steyn is detailed here. In particular, their ruling with respect to claim AC-2023-LON-001656 stated: ‘Mark Steyn said in the programme that UKHSA data on those people that had, and those that had not, received a third Covid-19 vaccination dose could be compared because the two groups included approximately the same numbers of people. However, his interpretation that there was “only one conclusion” from this comparison – that the third vaccination caused increased levels of infection, hospitalisation and death – was misleading because it did not take account of key factors such as the significant differences in age or health of the people in these two groups. The programme also failed to reflect that the UKHSA reports made clear that the raw data should not be used to draw conclusions about vaccine efficacy, due to the biases inherent in the vaccinated and unvaccinated populations.’

The details of my report, which includes relevant links to the data and evidence, is provided below. In summary what I found was that:

  • Ofcom’s editorial judgement/ruling that ‘Mark Steyn misled the viewer’ is based on the narrow examination of the available UKHSA data and only that to which Steyn specifically referred. Ofcom took no account of the full data available at that time which categorically supports (and strengthens) the contention, suggested by Steyn, that the vaccinated were more likely to be hospitalised than the unvaccinated. Analysis of all the data in fact shows Steyn’s assessment not just to be correct but to underplay or underestimate the negative hospital outcomes for the vaccinated categories when compared with the unvaccinated. Their ruling made no reference to the full data published at that time, which showed negative hospital outcomes for the vaccinated to be the one clear conclusion that could be taken from it.
  • It is somewhat ironic that the only editorial criticism they could have validly made was that Steyn did not provide an analysis in support of his contention using the full published data – and that if he failed in anything it was to insufficiently alert the audience to the risks from booster vaccination. Not only were the boosters ineffective, but the covid case rates in the ‘ever vaccinated’ were higher than those in the ‘never vaccinated’ in almost all age groups, and at least three times higher in the boosted than the never vaccinated.
  • With respect to covid mortality data, Steyn’s comparison between the UKHSA boosted and unboosted vaccine categories was over-simplified but this was understandable given the obfuscated way in which the UKHSA presented the data. Even had he broken it down by age to avoid ‘age confounding’ (as the Ofcom counsel claimed he should have done) it would not have changed the overall conclusion to be drawn from the data that, for a reason known only to Ofcom, they failed to take into account.
  • What was missing from Ofcom’s analysis was that for the much more important statistic – all-cause mortality (as opposed to just covid mortality) – in most age groups the all-cause mortality rate was higher in the boosted than the unboosted. And, once we take account of systemic biases in the data, all-cause mortality was higher in the ever vaccinated than the never vaccinated in each and every age group.
  • Once the systemic biases in both the relevant UKHSA and the ONS datasets are accounted for, both show a consistent lack of efficacy for the vaccines. Ofcom in its ruling against Steyn has encouraged the suppression of this critical information while the public has continued to be offered booster vaccines, exposing them to risk and thereby subjecting them to harm.
  • If Steyn missed addressing the effect of age confounding, Ofcom’s omission was much more serious and fundamental. It is guilty of using this narrow point to ‘disprove’ a thesis which in every other respect stands up. They are in fact guilty of the ‘blowfish fallacy‘. This is the technique of laser-focusing on an inconsequential methodological aspect of scientific research, blowing it out of proportion in order to distract from the bigger picture. If you persuade people to focus hard enough on specific details, they can miss the gorilla walking through the room.

As stated on its website, ‘OFCOM’s principal duty is: (i) to further the interests of citizens, and (ii) to further consumer interests in relevant markets, where appropriate by promoting competition.’

 

 

Ofcom is supposed to be independent and dispassionate. It is neither its role to endorse Government policy nor to prevent criticism of it. Yet an infamous programme segment was screened on ITV which insisted that the (subsequently withdrawn) AstraZeneca vaccine was 100 per cent effective against hospitalisation and death with no interrogation from the presenters about risk, at great potential harm to the public. Ofcom did nothing about this despite hundreds of complaints to them about this segment.

Detailed analysis from my report

Mark Steyn OFCOM case: the UKHSA data

Norman Fenton, 21 May 2024

Summary points

  • The thrust of Mark’s comments were correct and, if anything, understated because even at the time of the broadcast it was known that, not only were the boosters ineffective, but the covid case rates in the ‘ever vaccinated’  were higher than those in the ‘never vaccinated’ in almost all age groups and at least three times higher in the boosted than the unvaccinated.
  • With respect to covid mortality data, there are issues with age confounding in what Mark said about the UKHSA data comparing the boosted to the unboosted; this was understandable given the obfuscated way in which the UKHSA presented the data. However, other data and relevant information does indeed confirm the gist of Mark’s statements. Moreover, for the much more important all-cause mortality (as opposed to just covid mortality) in most age groups the rate is higher in the boosted than the unboosted. And, once we take account of systemic biases in the data, all-cause mortality is higher in the ever vaccinated than the never vaccinated in each age group.
  • If Mark had taken all data that were available at the time into consideration, he could have made even stronger statements showing lack of effectiveness and risks of the booster (and the vaccination in general).

Background/context: The UKHSA data

 

 

In week 44 of 2021 the UKHSA weekly vaccine surveillance reports stopped publishing graphs that consistently showed the covid case rates in almost all age groups were higher in the ‘ever vaccinated’ than the ‘never vaccinated’. This was well documented in ‎[1]. However, despite attempts at obfuscation, the reports still provided tables of raw data that enabled us to produce the case rate comparisons as shown in Figure 1. Note that in this week the case rates were higher in the ever vaccinated in all age categories above 30.

Figure 1

This (and subsequent) UKHSA data caused such embarrassment that some key academics who strongly supported the vaccine programme attempted to argue that the UKHSA data should not be used at all and that the ONS data should be used instead. This dispute is discussed in ‎[1]‎[3], where we argue that there are problems with both the UKHSA and ONS data, but that, once we account for systemic biases both datasets show consistent lack of efficacy of the vaccines. Key biases of both datasets include the curious definitions of the different categories of vaccinated people. For example, a person is defined as ‘unvaccinated’ in the first 20 days after the first dose, single vaccinated in the first 20 days of the second dose, etc. These definitions grossly exaggerate vaccine efficacy as explained in ‎[4]‎[8] especially as people are disproportionately likely to test positive within the first two weeks of vaccination (such vaccinated people are classified as unvaccinated!).

 

 

What Mark said about the number of boosted (‘triple vaccinated’) versus unboosted:

  • ‘Let us start with the basics. There are approximately equal numbers of triple vaccinated as the combined total of single, double and unvaccinated’;

Based on Table 7 of week 15 report ‎[2], this statement is correct.

  • ‘As you can see, from a pool of 63million, down at the bottom there, 63million, there are 32million who are triple vaccinated. That leaves just under 31million who are either double, single, or unvaccinated. So, we have two groups of similar size, 31, 32million. So, it’s relatively easy to weigh the merits of the third shot upon group A vs group B.’

While this statement is correct for the population as a whole, the numbers of boosted versus non-boosted in each of the different age categories are not roughly equal. For example, in the 70-79 age category, almost all are boosted (4,655,045 compared to 442,667 unboosted), whereas in the 30-39 age category more are unboosted than boosted (5,2103,368 against 4,211,897)

What Mark said about the (covid) mortality rates:

  • ‘We matched these numbers across all age groups. So, the point is, an 80-year-old with a booster shot is more likely to die than an 80-year-old without a booster shot. And likewise, a 30-year-old with the booster shot is more likely to die than a 30-year-old without a booster shot.’

While it is true that, for the overall population those boosted are much more likely to die with covid than those unboosted, this is because the boosted population is made up of disproportionately older people. We call this ‘age confounding’. To avoid age confounding, what we need to do is compare the covid mortality rate in each of the different age groups.  In fact, for the 70-79 age group there were 1,668 covid deaths in the boosted compared with 341 in the unboosted. When we divide by the number in each group, we get a covid mortality rate of 36 per 100K people in the boosted group compared with 77 per 100K people in the unboosted group. So, in the 70-79 group the mortality rate is higher in the unboosted (but see later comments about this). However, in the 30-39 age group the story is very different. Here, there are 10 deaths in the boosted group and 9 in the unboosted, meaning that the mortality rate is lower in the unboosted, 0.17 per 100K people, compared with 0.23 per 100K in the boosted.

  • ‘There’s 32million who had the third booster shot, there’s 31million who didn’t. So, we can directly compare the numbers, overall numbers, because they’re the same size. So, if you got the booster shot, you’re dying at three times the rate of the people who didn’t get the booster shot.’

Again, while that statement is true for the overall population it is not true for each age group based on the UKHSA data. In some age groups the mortality rate is higher, but in others it is lower as the examples above demonstrate. However, both the definitions of the vaccination categories and the bizarre definition of a covid ‘death’ (as anybody who dies within 28 days of a PCR positive test irrespective of cause of death) mean that comparing covid mortality rates between the vaccinated and unvaccinated is almost meaningless. It is for this reason that vaccine efficacy is best measured by comparing all-cause-mortality in the vaccinated against the unvaccinated ‎[7].  Moreover,  what was missing from Mark’s analysis, is that there is extensive evidence, as documented for example in ‎[3]‎[4]‎[5]‎[6]‎[7]‎[8], that all-cause mortality is higher in almost all age groups in the vaccinated than the unvaccinated once we adjust for systemic biases.

 

 

What Mark said about the covid case rates:

While there is again some age confounding in what Mark said about the case rates, there is no dispute that the UKHSA data shows that covid case rates are much higher (generally at least 3 times higher) in all age categories (except the under 18s) in the boosted (3 doses) compared to the unvaccinated. This is shown in Figure 2.

Figure 2

A comprehensive thread on X ‎[9] deals with this and the attempts made by the ONS and UKHSA to cover up the embarrassing data.

 

 

It is also extremely important to point out that all UK Government claims – including in both the UKHSA and ONS data that (at the time of the programme) the unvaccinated were at higher risk of hospitalisation and death were based on a combination of fraudulent definitions and deliberately murky record-keeping as explained in ‎[10].

The recent report ‎[8] is important to this case because it is a new systematic analysis that shows the extent to which every major study that has claimed vaccine efficacy is biased/flawed due to inappropriate vaccination classification and statistical tricks by which you could show that even a placebo is highly effective.

References

[1]   ‘UKHSA Efficacy Stats Death Watch: Week 44’, https://www.eugyppius.com/p/ukhsa-efficacy-stats-death-watch

[2] https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1069290/Weekly_Flu_and_COVID-19_report_w15_v2.pdf

[3]    ‘Official mortality data for England suggest systematic miscategorisation of vaccine status and uncertain effectiveness of Covid-19 vaccination’, http://dx.doi.org/10.13140/RG.2.2.28055.09124

 

 

[4]   https://wherearethenumbers.substack.com/p/how-to-create-the-illusion-your-vaccine

[5]   ‘Official mortality data for England reveal systematic undercounting of deaths occurring within first two weeks of Covid-19 vaccination’, http://dx.doi.org/10.13140/RG.2.2.12472.42248

[6]    ‘What the ONS Mortality Covid-19 Surveillance Data can tell us about Vaccine Safety and Efficacy’, http://dx.doi.org/10.13140/RG.2.2.30898.07362

[7]    https://probabilityandlaw.blogspot.com/2021/09/all-cause-mortality-rates-in-england.html

[8]     ‘The extent and impact of vaccine status miscategorisation on covid-19 vaccine efficacy studies’  http://dx.doi.org/10.1101/2024.03.09.24304015

[9]     https://x.com/Jikkyleaks/status/1675005406274523137

[10]    https://wherearethenumbers.substack.com/p/claims-the-unvaccinated-were-at-higher

Here is my report (pdf).

This article appeared in Where are the numbers? on August 16, 2024, and is republished by kind permission.

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