In preparation for COVID, the British outfit, BBC, played a leading role in creating something called the Trusted News Initiative:
The stated intent was to combat disinformation. But the results have now been found to be contrary-to-purpose. Like new legislative bills which have names which state the opposite of their effects (e.g., insurance premiums rose very fast under the Affordable Care Act), it looks like they deliberately named their initiative deceptively.
It is not just a little ironic for them to include the word “Trusted” when they intended to do so much lying to us. Outfits involved in the Initiative are the big ones — such as Reuters, BBC, Associated Press, Meta (Facebook), Google, and Microsoft (MSNBC):
When the really big media outlets in the USA were tracked, it was found that coverage during COVID was steeped in negative language and that the amount of negativity was insensitive to the reality-on-the-ground regarding COVID cases:
Here is the same graph with purple notes added:
When you repeat a mantra that is disconnected from the reality at hand, it is called bias, and the official definition of bias involves an error which systematically occurs in one direction, or on one side of an issue — rather than tracking with the truth. When looking at the share of all reports that were COVID, it almost looks like Black Plague:
Approximately 94 out of every 100 news stories had been COVID-related. But early on, a landmark seropositivity study revealed that the infection fatality rate (IFR) estimates put out by mainstream media and government officials did not properly account for the true spread of COVID. In Santa Clara County, the officials were off-the-mark by 56x:
If 56 times as many people have COVID than what you believed, then any estimate of infection fatality will get diluted once you finally incorporate them. From the pre-print of the study directly above, the wording says it all:
Estimating 94 deaths from 54,000 infections, the infection fatality rate (IFR) drops down to 0.17% (or 17 deaths per 10,000 infections). This “flu-like mortality rate” was confirmed in the UK in their Technical Briefing No. 5 as they prospectively followed 117,000 COVID cases for 28 days and found 169 deaths (14 deaths per 10,000 infections):
But if COVID is no more lethal than a severe flu, then why have over 9 of every 10 news reports involve COVID? The plausible answer is: For the purpose of propaganda. The evidence suggests that the extent of the lying by government and by media regarding COVID was unprecedented in modern affairs (unmatched institutional disreputability).
Reference
[statistical evidence of COVID propaganda uncovered in major media narratives] — https://www.nber.org/papers/w28110
[at least 9 of every 10 news stories involved COVID in the UK] — Morani M, Cushion S, Kyriakidou M, Soo N. Expert voices in the news reporting of the coronavirus pandemic: A study of UK television news bulletins and their audiences. Journalism (Lond). 2022 Dec;23(12):2513-2532. doi: 10.1177/14648849221127629. PMID: 38603191; PMCID: PMC9510961. https://pmc.ncbi.nlm.nih.gov/articles/PMC9510961/
“The content analysis study generated a total of 1347 items across five broadcasters with 1259 items that focused on the coronavirus pandemic.”
[official reports of COVID cases were up to 56-fold in error] — Bendavid E, Mulaney B, Sood N, Shah S, Bromley-Dulfano R, Lai C, Weissberg Z, Saavedra-Walker R, Tedrow J, Bogan A, Kupiec T, Eichner D, Gupta R, Ioannidis JPA, Bhattacharya J. COVID-19 antibody seroprevalence in Santa Clara County, California. Int J Epidemiol. 2021 May 17;50(2):410-419. doi: 10.1093/ije/dyab010. PMID: 33615345; PMCID: PMC7928865. https://pmc.ncbi.nlm.nih.gov/articles/PMC7928865/
[being wrong by up to 56x means IFR can be up to 56x lower than officially reported] — Pre-print of the study directly above this entry. https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v2
[169 COVID deaths by Day 28 from 117,000 COVID infections] — Page 3. Epidemiological findings. UK Technical Briefing #5. https://www.gov.uk/government/publications/investigation-of-novel-sars-cov-2-variant-variant-of-concern-20201201