Van mijn studie herinner ik mij onder andere vakken als "Journalistiek schrijven", "Populariserend schrijven", "Schrijven per taalniveau" en meer van dat moois. Allemaal taalvarianten die ik sindsdien heb zien verschuiven en verkleuren, wat heel normaal en gezond is voor levend taalgebruik. Wat ik nooit specifiek heb gehad (of heb gemist) is "Wetenschappelijk schrijven". Wel op onderdelen zoals het correct noteren van referenties, hoe de structuur van een wetenschappelijk artikel eruit ziet - maar eigenlijk nooit de formuleringen, het wetenschappelijk idioom, de taal zelf.
Een voorbeeld. Een uitspraak als "die studie was bullshit" kan natuurlijk niet in een wetenschappelijk journaal (zo noemt deskundige Karremans een scientific journal, ik pas mij maar even aan). De woordkeuze "bullshit" is niet alleen ongelukkig maar wat hier vooral ontbreekt is de twijfelfactor. Die moet altijd doorklinken, ook als iets onomstotelijk lijkt. Dat is immers wetenschap: wat je bewijst is geldig totdat een andere wetenschapper iets heel anders net wat beter bewijst. Alles moet onzeker worden geformuleerd, in gedweeë afwachting van de onvermijdelijke ontkrachting. Een rotsvaste overtuiging presenteer je daarom hoogstens als een 'suggestie van de data'. Maar hoe vang je dat verder in woorden, die twijfel? Hoe val je niet direct door de mand als onwetenschappelijk?
A little exercise
Suppose I want to get a letter published about the fact that in all pro-vaccination studies the Healthy Vaccinee Effect (HVE) is kept out to boost vaccine effectiveness. After all, we have seen this in almost all reports and studies that promote vaccination readiness, most recently in the Nivel study (Vv, MDH) and in the UMCU study. Also abroad (combined article with Nivel study) this method is generally used generously, sometimes even alongside other correction methods in order to make the resulting figures slightly more opaque.
So I would prefer to say
"Alle overheidsstudies over coronavaccins zijn HVE-rommel, de beleidsincompetentie is genocidaal gebleken en die hele sector is corrupt."
That probably won't go down well with a scientific journal.
It will be rejected at first. Not on content but on something protocol: the wrong language, for example. Because of course it has to be in English, otherwise it is not really Science, or better yet Science™. So we have to retranslate a few things:
- "Rommel" → "methodological limitations": Nooit direct "slecht" zeggen, altijd vaag en technisch houden.
- "Genocidaal gebleken" → "influence policy outcomes": Avoid emotional or moral judgments, make it abstract and indirect.
- "Corrupt" → "systemic challenges": Suggestion of problems without accusing anyone.
Tips:
- Voeg woorden toe als "potentially", "may" en "further investigation" om elke stelligheid te neutraliseren.
- Do not make a claim that could negatively affect the willingness to vaccinate, not even in bandaged terms.
- Avoid mentioning vitamins, exercise or sunlight at all times.
Good. What should be in it, first straight to the point:
Het "healthy vaccinee effect" kan een belangrijke vertekening (bias) veroorzaken in observationele studies naar de effectiviteit van COVID-19-vaccins. Deze bias houdt in dat mensen die ervoor kiezen zich te laten vaccineren vaak gezonder zijn of gezondere gewoonten hebben dan degenen die dat niet doen. Ook terminale mensen zien af van vaccinatie, wat de sterfte in de groep niet-gevaccineerden sterk verhoogt. Hierdoor wordt de effectiviteit van vaccins in studies overschat, omdat de gemeten gezondheidsuitkomsten niet te danken zijn aan het vaccin, maar aan de onderliggende gezondheidstoestand van de gevaccineerde groep.
This bias is clearly visible when assessing vaccines such as BNT162b2 (Pfizer-BioNTech) in real-world data. Researchers carefully ignore this factor, do not correct for it when analyzing data, and do not use statistical methods that account for differences in health characteristics between vaccinated and unvaccinated people. As a result, the scientific results can be opposite to what actually happens, even in the case of serious outcomes such as mortality. Structural ignoring of the HVE is a characteristic of a conflict of interest. Policymakers are not able to reflect on this and in turn have an interest in supporting science. A self-reinforcing feedback loop.
Conclusion: The systematic ignoring or not quantifying of the Healthy Vaccine Effect can only be explained as a deliberately applied method to present the Vaccine effectiveness differently than it actually is. This is a gross violation of the first principle in the Code of Scientific Integrity.
In practice
Read how that eventually turned into a Scientific Journal ? That article was already written, a year ago.
"The paper by Furst et al. (2024) highlights the Healthy Vaccinee effect as a potential bias in observational studies assessing the efficacy of COVID-19 vaccines, and urges researchers to apply more rigorous statistical adjustments. For the full text, see the original publication: https://doi.org/10.20452/pamw.16634.”
They are not the only ones. In 2023, Vinay Prasad, among others, already demonstrated the same.1The adjusted 90% lower mortality due to Covid-19 reported among the participants who received a booster cannot be attributed with certainty to boosting. "Healthy vaccinee bias" in this population may also have led to overestimations of vaccine effectiveness in similar studies by Clalit Health Services. Including mortality unrelated to Covid-19 in all observational Covid-19 vaccine studies would provide important context. https://www.nejm.org/doi/10.1056/NEJMc2306683
Would it all be too cautious? Apparently yes. It is no longer about scientific differences of opinion, it is about shifting paradigms, but the language does not shift along. It's not even about science anymore if that first principle is not respected.
I fear that the hammer has to go in: the scientific language is also in need of a thorough overhaul. This fumbling leads to nothing.
Footnotes
- 1The adjusted 90% lower mortality due to Covid-19 reported among the participants who received a booster cannot be attributed with certainty to boosting. "Healthy vaccinee bias" in this population may also have led to overestimations of vaccine effectiveness in similar studies by Clalit Health Services. Including mortality unrelated to Covid-19 in all observational Covid-19 vaccine studies would provide important context. https://www.nejm.org/doi/10.1056/NEJMc2306683
OK, good story
"Conversely", strong conclusions are drawn in journals and then by the press.
Recipe: 1) take too small a group so that the statistical effect almost but just not reaches significance.
2) Then you state that no connection has been found between A and B.
Pure deception and premeditated manipulation. Good for all kinds of things you want to cover up.
Coincidentally, I used to dive into the articles/reasoning and financing of anti-organic food items.
There you will also find shrewd fraud.
For example, it was firmly claimed that there is more poison in organic meat than in non-organic meat. What is involved in unraveling? They only took the old pesticides (such as DDT that remains in fields for decades), not the new neo-nicotinoids.
In summary: By making a selective choice of what you do and do not include in what you want to prove, you can also get away with manipulative fraud in a scientific article.
As far as financing is concerned: Phew, bad for my night's sleep. There is a whole class of bread writers in science. They come up with articles aimed at their next job, subsidy or promotion. Especially in the anti-bio corner you will find these people (who therefore aim for a job at Big Pharma). Then they take a medicinal herb (St John's wort, chamomile, aswagandha ... all smeared and slandered) and then you do research with all your parameters set in such a way that the only result can be that you die from asvagandha (for example) and live forever from the covid jab.
This is also how HCQ, Ivermectin etc. have been handled. As long as you choose the sample and the research design well in terms of size, composition, duration, endpoints, etc. It is impossible to achieve a positive outcome and reformulate it to 'effect not proven'. If you then have the peer reviewers on your side (e.g. top people from the medical sector for whom a positive outcome could be disruptive) then you are in a strong position...
You write "From my studies I remember..." And after that, the deterioration must have arisen, I'm afraid. For years I had contact with many students and started to become more and more critical, but they were not waiting for that. Theses started with "I am ......... and my thesis is about ...." Primary school level. I was completely shocked at the level of the medical study. Already in the first year there was talk of "publishing in important journals" and fiddling with the data, read truth, did not matter. Those who did not have the level but did have pointed elbows were invariably in a list of names among the submitted pieces. And at presentations, they were regularly sick with fake notes from friends of parents in the profession. I have also experienced that there was research on the shelf by, for example, "Bill Gates" into malaria and that the master's student in question did not get out what should have come out. After a lot of hassle, the student did succeed but the research went to a shelf in Germany so that it would come out what they wanted to see... Well, I was awake right away, actually at the end of 2019 as far as corona is concerned, but I have had my concerns for much longer. Now there is a glimmer of hope that things are going in the right direction after all. The broom through!
In 2020-2021, I wondered why argumentation theorists (teachers I had at uni, for example) didn't get involved in the discussion. Fallacy was piled on top of fallacy in the media - also on behalf of OMT, RIVM and CBS - and those academics not only have the tools but especially the authority to pull it apart. At the time, I didn't have a clear idea that academia are dependent on governments. If they antagonize them, it could have consequences. So I'd rather wait and see...