PANDA | Science. Sense. Society.

In this PANDA Open Session, cognitive scientist Mark Changizi examines three highly intuitive ideas that must be overturned: (1) That free expression is a privilege (2) That civil liberties must be balanced (3) That evil emanates from the evil-intentioned Watch his full presentation at YouTube: https://youtu.be/YCVp4RW4ieE Rumble: https://bit.ly/3JNvzcx

WHAT'S IN A NAME? https://pandata.org/sars-cov-2-whats-in-a-name-everything/ This paper on the naming of the "new virus" was published as preprint on 11 February 2020. It is a statement of the Coronavirus Study Group, part of the International Committee on Taxonomy of Viruses (ICTV). It makes interesting reading. Notably, it contains the following: "Likewise, we know that RNA viruses persist as a swarm of co-evolving closely related entities (variants of a defined sequence, haplotypes), known as quasispecies. Their genome sequence is a consensus snapshot of a constantly evolving cooperative population in vivo and may vary within a single infected person and over time in an outbreak. If the strict match criterion of novelty was to be applied to RNA viruses, it would have qualified every virus with a sequenced genome as a novel virus…" This is entirely consistent with what those of us who have been arguing all along, i.e.: ⚫️There was nothing novel around; ⚫️All that was found – by shining the spotlight of PCR on it – was part of the endemic and constantly mutating coronavirus swarm. In the paper, they report on the genome of the "new" virus, discuss its variation from known coronoviruses, and conclude thus: "The above results show that, in terms of taxonomy, SARS-CoV-2 is (just) another virus in the species Severe acute respiratory syndrome-related coronavirus. In this respect, the discovery of this virus differs considerably from the description of the two other zoonotic coronaviruses, SARS-CoV and MERS-CoV, introduced to humans in the 21st century. Both these viruses were considered novel by this study group based on prototyping two species." This is basically the group stating that they thought that SARS1 was novel, but not SARS-CoV-2!

With a population of under 2 million, Northern Ireland provides an important case study to understand the true impact of the "vaccination" campaign. Watch on Rumble 👉 https://bit.ly/3JGeqSe

THE "AUTHORITATIVE" WHO WAS WORKING BLIND Excerpt 👉 https://pandata.org/the-non-science-of-whos-weekly-covid-reports/ The WHO started generating weekly Covid reports on 17 August 2020 after giving up on their idea of daily reports. The steps taken by the WHO to generate each Weekly Epidemiological Update (WEU) may have ensured consistency, but it is certain that the results were not accurate. For instance and by their own testimony, they admit to enormous gaps in their data: “During this period, reporting completeness varied significantly.” “The number of countries reporting data on new hospitalisations ranged from 41% to 12%.” “The number of countries reporting data on ICU admissions ranged from 17% to 4%.” “11% [of countries] reported weekly new hospitalisation data at least 80% of the expected times.” “9% [of countries] did the same for new ICU admission data.” Furthermore, in the last published WEU it says: “Please note that the absence of reported data from other countries to the WHO does not imply that there are no COVID-19-related hospitalizations in those countries. The presented hospitalization data are preliminary and might change as new data become available. Furthermore, hospitalization data are subject to reporting delays. These data also likely include both hospitalizations with incidental cases of SARS-CoV-2 infection and those due to COVID-19 disease.” Therefore, not only do they admit to a lack of data and to delays in reporting, but also to the fact that the data they did receive may or may not be indicative of Covid at all.

"MEDIA LITERACY" IS BEING USED AS A COVER FOR CENSORSHIP Excerpt from https://pandata.org/post-twitter-files-part-media-literacy-and-funding/ Many fact check platforms offer media literacy and fact-checking courses: their main targets are children, students and journalists, although courses may be offered more widely. For example, Logically and NewsMobile joined forces with Facebook to offer a media literacy programme in India in 2021. Africa Check, its main funders being Meta, Bill & Melinda Gates Foundation and Google, trained 4,500 journalists in fact-checking; operates a media literacy programme in schools; and trained over 10,000 people in media literacy. Encouraging audiences to think critically, understand nuances and potential inaccuracies, and to avoid online scams and dangers is commendable, but courses on offer have a narrow focus. For example, a media literacy course for seniors, funded by Meta and operated by MediaWise, limits trustworthy sources to organisations such as mainstream media, Wikipedia, WHO and the CDC. The course facilitators claim that those who spread other narratives, described as ‘misinformation’ or ‘disinformation’, are doing this for financial gain such as advertising revenue and clickbait, or they may be linked to foreign or harmful sources. This and other courses, such as AFP’s fact checking courses for journalists, advise the importance of checking out the source by up-reading (finding out where the information came from) or lateral reading (checking what other sources say about the author or the website/news site). This is problematic because when checking out dissenting voices, despite having appropriate qualifications or experience to join the debate, they are often smeared on internet websites. Being able to listen to a variety of thoughtful and educated views on science, health and other issues should be normal in a free society, without prior judgement of credibility. For example, an AFP course for journalists entitled “Identify trustworthy sources on health topics and evaluate studies” gives useful detail on analysing academic papers, but emphasises the trustworthiness of a small number of elite medical journals and peer review. However, AFP does not acknowledge the influence of pharmaceutical companies and questions of possible bias in medical journals and peer review, as described by retired editors of both the British Medical Journal and the New England Journal of Medicine. Many academics have seen this trend significantly worsen since 2020, whilst issues of flawed data in peer reviewed and published papers that support official narratives are sometimes ignored. Hence journalists cannot rely on medical journals nor even peer review when investigating health issues, and “trustworthy sources” identified by AFP do not give a full picture of the range of useful academic opinions.

OBTAINING DATA IN REAL-TIME Excerpt from https://pandata.org/the-dashboard-that-ruled-the-world/ Even with the help of modern computers, it typically takes many months (or even years) to produce reliable mortality data. For example, the latest year for which official all-cause mortality figures are available in Canada is still only 2020. The national statistics office, StatsCanada, is quick to point out that “reporting delays” and “incomplete data” are the reason behind the three year effort. If it currently takes two or three years for a federally funded organisation such as StatsCan to publish mortality data, how was it possible for JHU to get Covid death data in real time? It is equally challenging to produce statistics about one particular pathogen or virus. For instance, seven months after the 2017/2018 flu season had ended, the CDC in the US was still only providing estimates for cases and deaths. Their stated reason was that “data on testing practices and deaths from the 2017-2018 season” were not yet available. The date of that statement was 22 November 2019. Exactly two months later the JHU dashboard went live, promising information on cases and deaths in real-time of a newly found respiratory virus that is similar to the flu. If it takes months or years to obtain mortality and case data for the flu, how was it possible to obtain data for Covid in real time? If it was not possible to do this in 2019, how did it suddenly become possible to do it in 2020? Naturally, there are plenty of countries in the world where data reporting is unreliable at the best of times. Likewise, the Human Mortality Database, which tracks mortality by country, is regularly ten years behind for many countries. How then did JHU expect to be able to plot Covid deaths for every country in the world in real time? More crucially, how did they possibly update their dashboard “every 15 minutes”?

Few elements established the deadly virus narrative as much as the avalanche of Covid dashboards that appeared in early 2020. And none were as influential as one developed in "just a few hours" as a "spur-of-the-moment" decision: the Johns Hopkins Covid-19 Dashboard. "The January 22 launch [of the dashboard] happened so early on in the Covid timeline that the first WHO situation report had only been released the preceding day, and the term 'Covid' had not even been coined yet." https://pandata.org/the-dashboard-that-ruled-the-world/

"The agreements are being promoted by wealthy countries as promoting equity. Yet, the rush to vote and implement will inevitably undermine equity by preventing states with fewer resources from equally participating in their development and having time to assess impact on their more fragile healthcare environments. This approach has not been so apparent in international health since the colonial era." https://dailysceptic.org/2024/04/09/the-who-is-pushing-through-the-pandemic-agreement-and-ihr-amendments-unlawfully/ Who gains indeed!

This post was deemed too spicy for LinkedIn 😉