Science by consensus is Evidence (de)based Science™
Science by consensus is an exercise in self-fulfilling prophecy.
Predictive algorithms are only as accurate as their premise and their parameters. You can craft a model with whatever weighted parameters you like in order to obtain a pre-determined outcome.
If you convince others to believe in your mathematical model which you configured based on an incorrect premise which leads to a deliberately exaggerated & catastrophised outcome, then you can sell almost anything to them -- even that which greatly harms them and their country.
Mathematic modellers dismiss empirical data as “opinions” if the data presents a threat to their “consensus”. But Empirical Data are NOT “Opinions”. Empirical Data are Facts.
Using bogus Mathematical Modelling to cover up unfavourable & inconvenient facts shown by Empirical Data is not “Scientific Expertise”.
It is Mathematical Sorcery which is glorified by Academic Terrorists.
It is not enough to be an intellect. Integrity is most important. Most academics lack the latter.
This applies to "Covid", "Climate" and all topics in between.
Pharmacovigilance trick to coverup, minimise & dismiss unpalatable facts:
How to hide, neglect & dismiss Drug Adverse Events as “rare”?
Use the Pharmacovigilance Trick.
Dice bad pregnancy outcomes into numerous sub-groups such that a 1 in 10 severely bad pregnancy outcome is divided & scattered under 10 different labels.
Slicing & dicing adverse events under multiple labels reduces the reported adverse events under each label. These are then dismissed as being consistent with “background rates”. It’s how vaccine adverse events involving vascular, cardiac, immune systems are also hidden.
Here is the very first analysis of Pfizer vaccine’s data in pregnant women & breastfeeding mothers.
— The Solitary Reaper
Post Script-1: Fun with Numbers
How to make sense of COVID-19 case & test numbers -- Sensitivity and Specificity.
Read:
Post Script-2: Mathematical Sorcery
Speaking of fun with numbers and mathematical sorcery, in a future post, I will share excerpts from an Email which I wrote to my abusive PhD supervisors in 2015 in which I expressed my concerns about how some academics get published. For some strange reason, it angered them (even though my intention was not to evoke their anger). I may even let you all guess why…..