It is all about it. The regular CBS report on causes of death could have shown where last summer's excess mortality came from. However, since 1 July, CBS no longer reports causes of death on a monthly basis. Because this causes quite a stir and is therefore doubted, below are some confirmations of this fact.
For some undisclosed reason, this monthly report has just been abolished (I should also try it with my customers...). From now on, only quarterly reporting will take place. We are now in October: month 10. Meanwhile, the third quarter is also over and there is still no report with causes of death about the second quarter. Way too slow, of course, in a period like this.
A crisis requires real-time monitoring of the situation. Surely it will not be the case that CBS will treat its quarterly reports in the same way as the Ministry of Health, Welfare and Sport does with FOI requests: delaying, sabotaging, filtering, in short, withholding information and redacting in documents what they do not like? What and when, they decide for themselves. (See also this article by Follow the Money.) This can no longer be called 'Openness of Government', this is totalitarian behavior and unworthy of a parliamentary democracy.
The possible reason for the radio silence at CBS
'Plausibility checks' are carried out on the data. Previously, I would have welcomed that, but trust in the processes of governments and large institutions has fallen to a minimum. It is not inconceivable that the 'plausibility criteria' will lead to fierce internal discussions. We see in the formation of a cabinet how disagreement can lead to paralysis.
Meaning-giving
http://nl.wikisage.org/wiki/Plausibiliteit
Plausibility is about filling a gapcognitivegap by adding a missing link that makes the preliminary conclusion acceptable. Plausibility andprobabilityare related. Characteristic is not an exact, scientific determination, but a reasoned (mental) process ofMeaning-making, an obvious explanation, a new fact, the interpretation of a step of thought, an associative expectation pattern or an interpretation that fits into a certain presupposition or experience of reality so that 'the picture seems to be complete'.
The word 'plausibility' has its origin in common with 'applauding', or applauding. It is a subjective process that can be applied very easily unscientifically. Aerosol transmission has also not been plausible for a long time – and still is not according to some arteriosclerosis. Plausibility can very easily be confused with 'desirability', because it fits in with the probabilities associated with a certain view. Paradigms are persistent. How do you ever find out which causes of death are plausible?
Data corruption also makes its appearance, then we know that
With desirability checks, the door is open for confirming efficiency or preparing new policy by means of data processing. Plausibility is a subjective matter, a way of interpreting. Data collectors and suppliers should stay away from interpretation. They should arm themselves against their own bias. Interpretation and resulting policy adjustments are up to politicians, not to the data manager. If the data supplier starts pre-sorting on policy, this will inevitably lead to data corruption. Because who pays the data supplier? Indeed: the policymaker and he has a hard enough time with all that goodness, which some people just don't want to understand.
In this way, totalitarian elements weave themselves through the government like a fungus. At first, you don't even see it; At most, it starts to smell a bit musty. While a fungal thread at one end doesn't know what the other end is doing, they all do the same thing. They are connected to each other and they don't even realize it. This way they can build whole stink mushrooms without even noticing.
What if causes of death resemble the list of vaccine side effects
The causes of death last summer are of considerable value. If CBS, in consultation with the Ministry of Health, Welfare and Sport and RIVM, sees data that do not seem plausible, then something must be done with it. What then? Take away? Replaced by other data? Fill in "unsure"? We don't know. Either way, it's a dangerous approach to data reporting. Data is really data. If data leads to conclusions that you think are not plausible and therefore do not fit your stall, then you should not tamper with the data but with your stall.
"What? But then our measures would not have had any effect? That's not plausible!"
"So much mortality after vaccination...? Extremely unbelievable. That must be Covid, an invisible variant, that's plausible."
Nonsense, of course – but how does it work? No idea.
TRANSPARENCY
The raw data must be able to be placed next to the report, so that independent peer reviewers can assess the extent to which the original data has been rightly corrected or violated. Dates of this importance should never be prepared in a small committee for presentation, whatever story they tell. The provisional data should be requested on the basis of the transparency required in the Public Administration Act.
Coding of causes of death
The categorization of causes of death is done according to the guidelines of the WHO. The WHO benefits greatly from outcomes that reflect an adequate approach to the pandemic. With the right figures, WHO will be able to justify their close relationship with the Chinese, for example, from whom they have taken so much good advice (intubation, lockdowns, incomplete virus sequences, PCR testing, social credit system – oh no not that one). Now in real science there is no butcher who wants to inspect his own meat. Unfortunately, that scientific integrity is hard to find in governments and also medical government officials and scientific institutes (see e.g. my article about the KNAW).
CBS will have to consult the RIVM to ask whether causes of death are plausible, which cannot be demonstrated mathematically. RIVM is therefore asked to edit the effectiveness test of its own performance. Now the RIVM will also want to see its measures and vaccine propaganda effectuated in the data. Again my favorite question comes to mind: "What could possibly go wrong?"
Just a bad idea
In short: there are far too many and far too large interests at stake to allow the agencies that have made a mess of it over the past year and a half, not only in terms of public health but certainly in terms of data and mathematics, to now manipulate the figures on the basis of 'plausibility checks'. What are the plausibility criteria? How are they described? The same clique of Dissel adepts uses plausibility that was scientifically debunked decades ago!
There is a possibility that it is data that harms the willingness to vaccinate. Because vaccinations are good, this is a possible legitimization to present the data in a more vaccine-friendly way. This has been happening for some time in the media, at Lareb, by vax representatives on talk shows, by ministers, advisors and not least at the RIVM itself.
CBS and RIVM have previously said that the data are too complex to be able to 'report transparently'. Let's not be fooled: that's pure mystification (* English has a better word: "obfuscation": to cover, cover, mangle to hide). If the RIVM thinks it can interpret the figures correctly, then it is certainly doable for professional data analysts and other serious data researchers.
It seems to me worthy of a WOB request to get the provisional, unredacted data from Causes of Death Q2 on the table. It has already come to that with my trust in the government. I'm not the only one, as evidenced by this blog of the Eucalyptic Society.
Related articles on Virusvaria:
Oud-CBS-directeur Jan van der Zanden: https://virusvaria.nl/voormalig-cbs-directeur-duidt-huiveringwekkende-cijfers/
Oversterfte zomer 2021: https://virusvaria.nl/vanwaar-al-die-zomerdoden/
KNAW – De teloorgang van wetenschappelijk integriteit: https://virusvaria.nl/knaw-verloochent-gedragscode-voor-wetenschappelijke-integriteit-met-erepenning-van-dissel/
Knurftige datapresentatie: https://virusvaria.nl/modellen-als-spiegels-van-de-competentie/
Dood na vaccinatie wordt bij Lareb nauwelijks gemeld (of geaccepteerd?): https://virusvaria.nl/lareb/
