Sceptical covid-19 research and sceptical polar bear science: is there a difference?

Reposted from Polar Bear Science

Posted on September 6, 2020 |

This essay about medical researchers having trouble getting their papers published because the results don’t support the official pandemic narrative has disturbing parallels with my experience trying to inject some balance into the official polar bear conservation narrative.1 Especially poignant is the mention of models built on assumptions sold as ‘facts’ that fail once data (i.e. evidence) become available – which of course is the entire point of my latest book, The Polar Bear Catastrophe That Never Happened.

Read the commentary below, copied from Lockdownsceptics.org (6 September 2020). Bold in original, link added to the story to which this is a response, and brief notes and links added as footnotes for parallels with polar bear conservation science.

Thanks for the ongoing sanity that is Lockdown Sceptics. I read the piece yesterday about how the scientific community is slowly starting to wake up to the fact that we have been significantly underestimating the level of immunity in the population (something that LS has been saying for months). I was really struck by these lines:

“Unfortunately, not all scientists are so timid with their views. Could it be the silence of too many sceptical scientists that has allowed more confident scientists like Neil Ferguson to become so influential?”

As sceptical scientist myself, this point hit home, but the reasons for the silence of the sceptical scientific voice are not just to do with lack of confidence.

Firstly, it is important for a scientific argument to have data. Without data you’re just expressing an opinion which, of course, can still carry weight depending on who is expressing it.3 However, there are real issues both with the data we have around COVID-19 and its reporting.

It is a well-known problem in science that the “negative results” are rarely published and so the literature is heavily weighted towards positive findings. 4 This can lead to a false perception of what is happening. So for sceptical scientists wanting to make arguments, the data may simply not be there as it was a “negative result”.

Scientists also tend to want to publish interesting findings. As a result, the COVID-19 literature tends to be biased towards the serious or rare cases as these are by definition “interesting”. 5

Here’s an example of the title and the first few lines of a case report in the New England Journal of Medicine from April, which illustrates this point:

Coagulopathy and Antiphospholipid Antibodies in Patients with COVID-19

“We describe a patient with Covid-19 and clinically significant coagulopathy, antiphospholipid antibodies, and multiple infarcts. He was one of three patients with these findings in an intensive care unit designated for patients with COVID-19….”

There is nothing wrong with this paper, it is a typical case report. However notice that the title gives no qualification of the fact that the patients are in the intensive care unit and as such are not representative of the vast number of patients with COVID-19. If you just read the title you could erroneously infer that ALL patients with COVID-19 have issues with their blood coagulating and their immune system going haywire. That’s the problem, a report of a rare finding, designed to alert clinicians in the ICU of potential complications, can feed confirmation bias in a lot of the media (and the public) that COVID-19 is the new plague that will kill you as soon as look at you.

Unfortunately you cannot publish the balancing paper:

Mild cough in Patients with COVID-19

“We describe a patient with Covid-19 and a mild dry cough that resolved itself in a few weeks…”

It is uninteresting. Although ironically it would be interesting (and probably publishable) if COVID-19 was actually causing all patients to have major complications!

Finally as you reported today in your article about Prof. Gupta, there is also further worrying bias in the COVID-19 literature with editors scared to publish “dangerous” ideas that could “impact our response to COVID-19”. Limiting publication of such finding in “lesser journals” (essential ones that aren’t so widely read), is an effective way of burying the findings as they may appear less “valuable” than a publication in Nature.6

This literature bias makes addressing the major issue facing the sceptical scientist even more daunting. This issue is that they need to overturn established orthodoxy around COVID-19 and our responses to it.

The advantage that modellers had at the start of the COVID-19 pandemic is that they did not much real world data because they could run their models built on assumptions.7 So it’s not surprising that the modellers got in first. It is only now that we have the actual data can we look at what the modelling predictions and point out how inaccurate these were and start to see where the assumptions were wrong.

The problem is that the models and modellers created and established “facts” and you require a lot more data to overcome an established “fact” than was needed to create that “fact” in the first place.8

This was compounded by the fact that we then implemented solutions with assumed efficacy (e.g. wearing face coverings, lockdowns) and the use of these solutions have now become more articles of faith rather than scientific hypotheses.9 So to overcome such solutions will require large amounts of evidence to achieve a shift amongst the scientific community, many of whom have been active advocates of these very solutions. Imagine what data you would actually need to persuade Nicola Sturgeon that mask wearing has no benefit or Matt Hancock that lockdown is not the answer? I’d wager it would be almost impossible and will be all the more impossible if don’t allow the publication of “dangerous data” in the first place.10

Finally I think it import to also understand that science is a professional industry and that most scientists work for businesses and institutions. Most of these businesses and institutions will have implemented COVID-19 based policies, supported by senior leadership who, even if they don’t believe in the policies, will need to be seen to be “doing the right thing”.11 Scientists working in these organisations will also have contractual obligations that will limit their ability to publish without permission or produce communication that could be deemed to be detrimental to their place of work.12

Imagine if you worked for one of the companies working on developing a vaccine and wanted to publish something saying that “vaccines are a waste of time and money because everyone will be basically immune through infection before they get to the clinic”? This effectively means that the vast majority of scientists are in environments that require a level of collective “self-censorship” and so, with a few exception, most of us have to bite our tongues or run the genuine risk of “blow back” on careers.13 We are not in the position of having a comfortable academic chair from which to cast our pearls of wisdom.14

Despite this, science is built on data and so ultimately I have to believe that we can get to a point where we stop treating COVID-19 as a special case and recognize it as just another disease to go alongside all the other risks we face in being alive. I am greatly encourage by the fact that we’re seeing journals like the BMJ publish “sceptical” opinion pieces as it shows that this shift may be starting to occur although today’s article about Prof. Gupta shows that we may have a lot further to go.15

Footnotes

  1. Of course, this analogy applies also to the experiences of many scientists sceptical of climate science narratives: I am not alone in this regard, nor am I alone in my experience of challenging the dominant narrative of polar bear conservation science. Mitch Taylor, Peter Ridd, Tim Ball, Judith Curry, Roger Pielke Jr. and a host of other scientists could write a similar list of parallels.
  2. cf. polar bears are thriving
  3. cf. Ian Stirling’s opinion carried significant weight early on
  4. cf. ‘negative results’ for polar bears is evidence of bears not starving due to reduced sea ice (or population increases), such as in the Beaufort Sea and Barents Sea
  5. cf. cannibalism blamed on climate change
  6. cf. or refuse to publish at all
  7. cf. the 2007 polar bear extinction model
  8. cf. the importance of summer sea ice to polar bears
  9. cf. Ian Stirling interview 2016
  10. cf. Six good years in a row for Western Hudson Bay polar bears
  11. cf. IUCN Polar Bear Specialist Group expelled Mitch Taylor
  12. cf. my expulsion from the University of Victoria
  13. cf. BioScience attack on my scientific credentials and integrity
  14. cf. Mitch Taylor on accountability in polar bear science
  15. cf. 2016 paper on status of Canadian polar bears

46 thoughts on “Sceptical covid-19 research and sceptical polar bear science: is there a difference?

  1. “medical researchers having trouble getting their papers published because the results don’t support the official pandemic narrative has disturbing parallels with my experience trying to inject some balance into the official polar bear conservation narrative”

    There are actually quite a few papers where medical researchers disagree with “the official pandemic narrative”.

    Pls see

    https://tambonthongchai.com/2020/04/03/11187/

    • Also, not all polar bear papers claim a disturbing or alarming survival condition for polar bears. Many simply point out that low sea ice years correspond with longer land vacations for the bears without a hunger issue. These bears can go for 6 months without eating. See for example Schielbe 2008 (spelling?) and a few others in the bibliography at the end of this post. Incidentally, you will find there that even the doomsayers close their case by conceding large uncertainties.

      https://tambonthongchai.com/2020/07/21/climate-change-vs-polar-bears/

      • Sorry Chaamjamal, This is absolutely typical of these kinds of process in science. Susan Crockford had to fight very hard to get her points accepted over many years – this was a major issue, and she had to fight every inch, with little support, and plenty of distracting (but very real) attempts at her personal employment and reputation. Finally after many years of persistent work, the points she makes are so evident to all but the most willfully ignorant scientists, that the arguments against her position dry up – nobody apologizes or accepts that they were wrong, none of the administrators try to reverse the reputational damage. Then people like you come along and say that there wasn’t really ever much of a disagreement actually, and not all people had alternative views. Frankly this is adding insult to injury – it’s hard enough for a professional scientist to disagree with the orthodoxy – so when one does, and wins, you should applaud her efforts and not try to diminish the value of her work.

        • “Jay Willis September 9, 2020 at 1:15 am
          Sorry Chaamjamal, This is absolutely typical of these kinds of process in science. Susan Crockford had to fight very hard to get her points accepted over many years – this was a major issue, and she had to fight every inch, with little support,”

          I am very sorry and I apologize if my comments have that ugly interpretation. I admire susan’s work and happy that our community has someone who knows the polar bear sitution. I was trying to be helpful but clearly I don’t know how. Apologies.

  2. I feel sure there is no difference. But we should ignore all these prophesies about both polar bears and Covid 19. Yawn broadly – and wait a year or two concerning Covid – and perhaps a few years more re polar bears. The facts and the true statistics will then be obvious to all. I believe the views of the sceptics will be validated for all to see and accept – but I really cannot be sure.

    It’ll all come out in the wash. With climate change hysteria, alas – we may have to wait 50 – 100 years.

    • The problem is while you’re sat about yawning other’s with a lot more motivation will be changing the world in which we live. If you want to live in an “Extinction Rebellion” dystopia fine, sorry I woke you up, but personally I don’t.

      • You beat me to it!

        I’m not sure which aphorism is more appropriate. Either “first they came for …” or “for evil to triumph …” For sure if we take Andy’s laid-back attitude we are in serious trouble!

    • Got to laugh at this perspective Andy.
      In Britain we are waiting for the day when we can finally defeat Napoleon Bonaparte. The reason why its important is not because we fear invasion by ‘le Grande Armee’ but because we can finally get rid of income tax.

      which was introduced in order to pay for that war

  3. The fact that we cannot get reliable statistics on Covid-19 points to an utter failure of the CDC to push for standards on reporting deaths across all 50 states. Without reliable data, any actions it recommends is just guesswork. We spend way too much money on this organization for a bunch of guesswork. Heads should be rolling.

    All tests have a some number of false-negatives and false-positives – so the Covid-19 test is no surprise. It is when the test fails so utterly that one cannot trust the data that immediate action must be taken. I for one do not think the Covid-19 test is that bad…but in time we will know more and I may change my mind.

    Covid-19 *is* a special case whether you want to admit it or not. Because it is the first time we have knowingly faced the disease and know so little that makes it special. If it ends up hanging around like the Flu, causing an epidemic every 2 or 3 years then we are in a good place to modify our response to it.

    Yes, the response was an over-reaction – but it likely did save a lot of lives (it keep hospitals from being flooded). There was no way to know back in March that we were over-reacting. I would rather over-react than under-react when the really bad plague finally comes around.

    The people reporting on polar bears are flat out lying to support their cause. I am not convinced the same is happening in the reporting of Covid-19. I think the data is so bad and research so uncoordinated (including false results) that it’s impossible to know just what reality is at any given moment. It doesn’t take a conspiracy to develop wrong conclusions – just incompetence.

    • Medical metrology and governance are completely unreliable to the extent that if they were in financial accountancy would be considered fraudulent and criminal. Basic terms are confused and used interchangeably when they are not. So what is the difference between a ‘case’ and an ‘infection’ and a positive PCR test? These are freely used interchangeably but then plugged into very specific formulae. If you add in financial incentives to mis-report with no accountability for mis-reporting then the problems become uncontrollable. As modellers with no medical knowledge just ‘plug the numbers in’ to hugely iterative models and give the results of the Lorentzian chaos to innumerate scared politicians.

      This is an area that should be far more disciplined – but it may be too late as the failure of medical metrology, statistics and modeling has led to economies crashing worldwide.

  4. There’s no difference. Both sets of ‘research’ are politically motivated and presume their results based on a political view in advance.

  5. I would definitely NOT have assumed that the title Coagulopathy etc. meant that this applied to ALL Covid patients everywhere. Especially where the very first sentence in the report made it quite clear that this applied to just three patients in intensive care.

    I guess the critique was prompted by the lack of any qualifying word in front of ‘patients’. Here are some options:

    C. and A. Antibodies in Insignificant Numbers of Patients with Covid 19.

    C. and A. Antibodies in More Patients with Covid 19.

    The actual title, C. and A. Antibodies in Patients with Covid 19, is neutral. The reader can then assess the report without having had a subliminal prompt in the title to read it from a biased perspective (one way or another). It’s almost as if the writer of the commentary quoted above is looking for and finding bias even when it does not exist (or where the original author tried to avoid it).

    • The people most affected by reports of coagulopathies are those in medical and paramedical areas such as my nurse daughter. She knows a coagulopathy is the worst of the worst. So she refuses to listen to reason about epidemiology, even though she has never seen a covid patient with coagulopathy (old names ‘consumptive shock’ and ‘diseminated intravascular coagulation’). For someone actually caring for the sick, such things are what nightmares are made of. And nowhere is there any information as to whether this affects the majority of those dying of covid.

      On the good side, an activated form of Vit D appears to have dropped the death rate for hospitalized patients from 8% to 0 in a Spanish trial. Even if it is only half as good in replication, this changes the game. Note that taking 2000 IU a day of D3 takes more than a month to build even near the levels they gave, so start now if you don’t use it. Here in BC, the my shadow is already longer than me at midday, an indication that the UVB is now negligible, although some UVA is still getting through and will produce a mild burn if you are out all day.

  6. “However notice that the title gives no qualification of the fact that the patients are in the intensive care unit and as such are not representative of the vast number of patients with COVID-19”

    The title says “coagulopathy”.

  7. Covid-19 is government science. It’s up to the individual to believe in it. Me personally I never listen to what the Gov says and so far I have seen no scientific proof but only manipulation of data and deaths caused by covid-19.

    • Which is still an improvement on Pseudoscience and junk science pushed in the name of a good cause Climate Science(tm).

  8. There is now a serious divided between what the media is saying about the pandemic and the experiences of it by real people. Very few people know anyone who has had a bad case of COVID-19. How long can people be told that there is a plague when no one they know has fallen ill from it.

    Here in Canada, more and more people (and especially the young) are rebelling against the measures to suppress the spread of the virus. The politicians and the established media are deriding them as ignorant and irresponsible, but the suppressions of commerce and the closing of the schools and the coming destruction of the airlines were all mistakes, and this will become impossible to deny. Why? Our medical leaders keep raving about increasing case numbers, and yet hospitalization numbers are barely budging.

    In Canada, 99.5 percent (at least) of people who are infected recover without serious harms. The median age of the dead is 84. I have not seen a single article in an established newspaper that admits these two facts, because the inevitable inference from them is that the damage resulting from the suppressive measures was unjustified by the seriousness of the pandemic.

    • I know one person who had a serious case of COVID-19 and was hospitalized twice. He was sick very early in the game and may have been a victim of the ventilator treatment. All the other people I know who have tested positive were very sick for a week or two with no permanent disabilities.

    • Even the cbc has mentioned something in a backhanded way in an article… https://www.cbc.ca/news/health/flu-vaccine-covid-19-twindemic-what-you-need-to-know-1.5709559

      that the flu numbers seem to have disappeared. I leave it to others the possible implications of that.

      The actual quote near the end of the article …
      But as for which strains will circulate, it’s too early to tell, both public health and infectious disease experts say, because normally predictions are made based on flu infections in Australia, which has its peak influenza period during Canada’s summer. But this year, the number of flu cases were so low that it’s difficult to collect data.

      It does make one wonder…

      • Flu cases in Australia have been very low this year, for two reasons. First, the precautions against Covid also work for flu – social distancing, washing hands, masks. Second, there was a big take-up of flu vaccinations, not because anyone thought they worked against Covid, but as a precaution. Given the uncertainties of a new disease, you didn’t want to catch flu and covid at the same time!

        Keep in mind that the flu stats are based on those people actually tested for the flu virus; many people have light cases of flu and don’t go to the doctor or get tested. Though anyone with flu-like symptoms might think they have Covid and be tested for that ( somehow I doubt they are simultaneously testing for flu!) On balance, I think the flu vaccinations are a big factor, where I live there were vaccination clinics everywhere – doctors, pharmacies, local councils.

    • Very few people know anyone who has had a bad case of COVID-19

      There is no one I directly know who has had COVID. I know of two people indirectly (daughter of a friend of my brother and the friend of that daughter whom she caught it from) who had minor cases of COVID (as tends to be the case with the young who get it). Beyond that is the gossip at work about 3 or 4 people in the company that supposedly have tested positive early on (but no serious cases involving hospitalization) though no one that I personally have met.

      That doesn’t mean that there aren’t bad COVID cases out there (including cases that ended in death). Just that things are not as bad as the media makes it out to be. After half a year, the number of cases, according to official numbers, is less than 2% and the number of deaths has been less than 0.1% of the US population. That’s really a very, very tiny portion of the population.

  9. Poor old bears. First their ice melts and now they get hit with a bad boy virus from Wu Han. What a double whammy. They need to form an action committee and get some funding.

    {sarc}

  10. Crying Wolf

    Well, we as the village are tired of it.

    And like the proverbial boy–there will be a comeuppance.

    I’m sick to death of hearing of “models say” when the models don’t actually say–those that interpret are the ones saying, but what they don’t say is more telling than what they do.

    It used to be you had to list out your exceptions, define your parameters, and defend your reasons why. Now it seems those checks to a model are simply ignored or hidden lest they get scrutinized because you couldn’t make a solid argument for them. Well, time to start the scrutiny I say…and let the chips fall where they may.

  11. It’s all over the place, recently looked at websites of three university presses who had produced decent books lately, two were like this–https://www.upress.state.ms.us/Books/A/Ain-t-There-No-More
    “We are committed to equality, inclusivity, and diversity…..Operating in a rapidly evolving marketplace and striving to be an antiracist organization, we value and promote equity and justice…. ”

    Are they admitting guilt? Maybe like sustainability, ecology took it for granted before it became “necessary.”
    Let’s replace journal impact factors with problem solving. Requires lots of false starts.
    “There’s no difference. Both sets of ‘research’ are politically motivated and presume their results based on a political view in advance.” Everybody doesn’t do it, sorry.

  12. People may be interested by a recent tweet sent out by the United Nations concerning Covid 19….

    United Nations 6 Sep
    “The #COVID19 pandemic is demonstrating what we all know: millennia of patriarchy have resulted in a male-dominated world with a male-dominated culture which damages everyone – women, men, girls & boys.”

    …..we all know that right?

  13. RGHE apostasy even with data has not been exactly welcomed at WUWT, either.

    In order to perform as advertised the greenhouse effect relies on “extra” energy upwelling from the surface and “extra” energy downwelling/”back” radiating from the cold troposphere towards the warm surface.
    What follows is a classical style experiment demonstrating why that “extra” energy is not possible.

    The central apparatus is an electric plate heater rated at 125 W with a surface area of 0.00895 m^2 which at equilibrium must radiate at 13,960 W/m^2. (125/0.00895)
    According to S-B for the heater to radiate ALL of its energy as a BB requires a surface temperature of about 808 F. (13,960/5.67E-8)^.25
    Let us call that input energy “Hot Ray.”

    The measured heater surface temperature in open air was about 670 F.
    A large chunk of the input energy is gone missing.
    Let us call the energy radiating at 670 F “Net Ray.”
    Hot Ray – ??? = Net Ray

    There is a contingent that asserts Hot Rays from one direction and Cold Rays from an opposing direction meet somewhere in the middle and go “boink” to produce Net Ray.
    Hot Ray – Cold Ray = Net Ray

    However, this experiment shows that the ??? in question is obviously the non-radiative heat transfer processes of the contiguous gang of heat transfer participating kinetic molecules, aka Non-Ray. These non-radiative heat transfer processes lower the heater’s surface temperature and the net amount of exiting radiation.
    Hot Ray – Non-Ray = Net Ray
    In observable fact, when fans and water sprays are applied, Non-Ray increases and Net Ray decreases, as does emissivity which equals Net Ray / Hot Ray.
    When the heater is operated under vacuum where Non-Ray = 0, i.e. does not exist, the heater surface exhibits close to the predicted BB temperature.

    If Hot Ray – Cold Ray = Net Ray were correct the vacuum Hot Ray would have been diminished by the Cold Ray from the inner walls of the vacuum box and display less than the BB.

    Zero evidence of that.

    Hot Ray = Net Ray means Cold Ray = 0

    QED

    LWIR from the cold troposphere cannot radiate “extra” energy back towards the warm surface.
    and
    BB radiation upwelling “extra” energy from the surface is not possible.

    Recall Feynman’s observation on theories and experiments.

    https://www.linkedin.com/posts/nicholas-schroeder-55934820_climatechange-globalwarming-carbondioxide-activity-6655639704802852864-_5jW

  14. 13 days until the sun dips below the equator and our primary source of Vitamin D is cut off. If you haven’t bought your Vitamin D and K2 supplements already I would do it now.

  15. Another example.
    Peter Ridd and the reality of the state of the GBR. His former institution’s reactions to his trying to give a counter-view to the alarmism, a view which threatens their pushi for more research funding.

  16. Check out this site
    https://www.trialsitenews.com/
    And see how a cheap proven cure for river blindness, Ivermectin, is stopping the virus progressing, yet governments are ignoring it and letting people die.
    Here in the UK Oxford University has tried to get interest in their inhaler trials but our National Health Service is ignoring it.
    https://www.qut.edu.au/news?id=165889
    Why are we letting people die whilst we try to get double blind trials going? Both of these drugs are proven safe and are cheap.

  17. I found this extra interesting, having just read Willis’s article about Scott Adams book on pervasive mass delusions. It applies to both bears and Wuflu reporting.

  18. ““We describe a patient with Covid-19 and clinically significant coagulopathy, antiphospholipid antibodies”

    No wonder Plaquenil (hydroxychloroquine) does… wonder.

    What fool would vaccinate against a disease best known for creating antiphospholipid antibodies?

  19. Here’s a 37-minute YouTube video by Ivor Cummins that makes some powerful points. It looks at graphs of key statistics. Here’s a rough summary:

    The Gompowitz (sp?) curve of fatalities seen in other epidemics is being followed, meaning there was little reason to panic at its height, and that it would fade without lockdowns.
    This is because most of the population has existing resistance / immunity to infections.
    Sweden’s death toll from flu in 2019 was much lower than that of its Nordic neighbors, providing more “dry tinder” (frail, vulnerable people who’d otherwise have died in the prior year) for Covid-19. Supporting this, countries that had had MORE severe 2019 flu seasons had lower impacts from Covid-19. (A very strong argument IMO.)
    The second wave in the U.S. is in the South, which reflects the geographic difference between temperate and tropical zones, which peak at different times. (A weak argument IMO.)
    Also contributing to the illusion of a second wave is a “casedemic” due to over-sensitive testing that detects fragments, not true cases (hospitalizations).
    This fake second wave was seen before in the Swine Flu epidemic—when what drove alarm about it was alarmism and media frenzy.
    Also, a likely seasonal effect.
    And the second wave might be due to Autumn flu, in part, being mis-counted as Covid-19.
    And the second wave is minor in size.
    Lockdowns are causing deaths from deferred elective testing and surgeries. Plus causing other social negatives.
    Lockdowns slow herd immunity, making infections in the fall more deadly.

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