Stuart Gilmour Profile picture
Oct 6, 2021 10 tweets 4 min read Read on X
In September 2021 an anti-vaccination meme started which claimed 70 members of Pfizer’s “investment board” are members of China’s Communist Party. Let’s look at how major news services and anti-China thinktanks drive anti-vaccination sentiments that kill Americans.
Snopes targeted this meme as false in September 2021, and briefly mentioned a news article in December 2020 that released the names, and says no government has verified it. Its role in helping to fuel anti-vax sentiment is clear from reddit subs like r/HermanCainAward.
This fabricated list was widely covered by The Daily Mail, the NY Post, the Epoch Times, the Australian, and Sky News. Foreign Policy’s supposed China expert Palmer referred to it as “an interesting data source for researchers”. Tory ex-leader Iain Duncan Smith wrote about it.
By September 2021 this list which included names like “Chen Thirsty” had become part of the anti-vaccination disinformation eco-system, and was fueling resistance to vaccination in America, spreading on Twitter, Facebook, and other social media.
So where did this original killer list come from? It was released to the media by the cybersecurity company Internet2.0, and promoted by the Inter-parliamentary Alliance on China (@ipacglobal). internet2-0.com/shanghai-ccp-m…
Internet 2.0’s board is a bunch of American and Australian cyber-security “experts” with backgrounds in cyber-security, the military and the defense industry. IPAC are a collection of legislators with an explicit anti-China ideology.
And what is Internet 2.0’s next scoop? A story about how an increase in sales of PCR kits in 2019 in Wuhan means that COVID-19 was leaked from a lab, that is being boosted by the Australian, Japan Times, Daily Mail, Bloomberg … and soon will be in the anti-vax disinfo world.
During the recent Facebook outage there was a lot of banter about how it will force Boomers to learn actual facts. But let’s not forget that these memes don’t emerge in social media: they are pushed by malicious agents and major media outlets.
There is a clear line from Internet 2.0’s fabricated list in December 2020 to people dying of COVID-19 misinformation in September 2021. That line goes through major news outlets, anti-China thinktanks, racist politicians and former Tory leaders before it gets near Facebook.
If your relatives have been sucked down that Qanon, anti-vax rabbit hole, don’t blame Zuckerberg: blame the anti-China thinktanks and major conservative news outlets that are happy to see your grandma die so they can drum up a war that makes them money.

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More from @drStuartGilmour

Oct 15, 2022
Follow up on my tweets from yesterday complaining about the new economist report on how “autocratic” countries over-state their GDP. I will analyze the paper this article references, and show a range of sleight-of-hand and maths errors in this work.
This is an excellent and egregious example of how economists don’t understand and/or misuse statistical tools. I will be referencing this version of the work the Economist is discussing – there are many versions, this one is the most recent (2021). bfi.uchicago.edu/wp-content/upl…
The first sleight of hand is the confusion of levels and rates of growth. The author builds a theory of the relationship between *growth* in night time light (NTL) and *growth* in GDP (first two pics). But their final model (eqn 6) analyzes ln(GDP) – a level not a rate! ImageImageImage
Read 15 tweets
Oct 14, 2022
It’s so exhausting dealing with this torrent of bad-faith data “analysis” from the Economist. The latest is an analysis of satellite data on night time lights and gdp growth that suggests “autocratic” states fiddle their numbers on gdp growth. economist.com/graphic-detail…
For starters it’s obvious bad faith. This figure from the report it references shows the gdp growth and night time light growth for “free” and not-“free” countries. The assumption this is dishonest rather than just a different growth relationship is so condescending.
Anyone who has been to a rapidly growing low- or middle-income country knows they don’t have the same lighting as rich countries. This is “partly free” (?!) Dhaka. Bangladesh isn’t prioritizing street lights and has a different urban landscape to Tokyo (which is “free”).
Read 7 tweets
May 16, 2022
@dakekang and @huizhong_wu your reporting on prison rates in your latest article about Xinjiang is wrong and misleading. Assuming your linked list is true, the imprisonment rate is not “the highest anywhere in the world” and your numbers are just wrong.apnews.com/article/religi…
First, you report that US prison rates are 364 per 100000. This is not correct. The number is actually 537, but you didn’t include US Jails in your figure. Please correct it. We don’t need more articles understating the USA’s incarceration epidemic.
Second, you say that the Konasheher country rate (3789) is “the highest known imprisonment rate in the world”. This is false, because you compare a county with countries. There are *many* counties in the USA with higher rates. See e.g. Indiana.
Read 6 tweets
Mar 29, 2022
Hong Kong has experienced a wave of #covid19 cases and deaths, and some media are blaming this on Chinese COVID vaccines, saying they don’t work. Let’s talk about whether this is true, and the implications for global vaccine equity of vaccine misinformation.
A recent presentation by Hong Kong University (HKU) professors has been used by the usual China “experts” and journalists to argue that reliance on China’s vaccine, Sinovac, compared to BioNTech’s mRNA vaccine was a bad idea, with tweets like this.
Let’s look at this slide in detail. 2-dose Sinovac gives 77% protection against death in over 60s, but 3-dose Sinovac gives 98% protection. This is weird, and it suggests that there’s more to this story than a weak vaccine: Risk profile and timing. Let’s look at these.
Read 16 tweets
Feb 14, 2022
Remember in 2020 there was a map showing how well-prepared different countries were, which received widespread derision for its terrible accuracy? I analyzed the underlying data to see how poorly it predicted pandemic outcomes.
The map is based on the Global Health Security Index, a numerical measure of pandemic preparedness compiled by Economist Impact in collaboration with Johns Hopkins and others. There is a published report, with a clear methodology.
ghsindex.org
The data is available from their website, giving 195 countries an overall score and also scoring them on six sub-domains which measure things like anti-microbial resistance (AMR) preparedness, adherence to international health regulations, and so on.
Read 21 tweets
Feb 12, 2022
This week 10 years ago I first visited Minamisoma, and began a five year long collaboration with the local community studying nuclear, tsunami and earrthquake disaster response and recovery. A thread about my research and what we learned. Image
When the Great East Japan Earthquake and Tsunami hit I was a brand new assistant prof, living in Tokyo for two weeks. Almost as soon as it happened all the Japanese students from the dept I worked in headed north to help with recovery. [I took these photos in Feb 2012] Image
They all went to a small town called Minamisoma, very close to the Dai-ichi Nuclear plant, that was partially evacuated after the incident. First they did health checks but soon were asked to help with other things. [Map source: Morita et al, PLOS ONE, 2018] Image
Read 24 tweets

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