But you couldn't pay for the Jobs I did for you.
Celebrities and this public showcasing of being nice.
You and your brand are evil!
Order it! I\u2019ll pay for you.
— Lilo Aderogba \U0001f33a\U0001f33a\U0001f33a (@Liloaderogba) January 6, 2021
Happy new year \U0001f33a \U0001f495 https://t.co/811ncG9ebY
I knew she was going to be really busy...
I was really excited as I'm just a student and just trying to make money for myself, I put into so much effort designing just trying to secure a spot....
She came on again, she wanted to launch Adire t-shirts, I made designs for them and sent them, her PA said she approved them and she posted them.
After I finished the Adire project which she named ADR by LILO...
Mehn I felt really bad, I was down, I had to stay awake all night to get the list of the winners to make the design. Nights upon nights, my efforts, my money spent all for IG tags?!
Some of these celebrities do these to up and coming brands and it's really evil. Y'all that do this should fix up!
Your RTs would go a long way getting my voice heard, Getting people know what some of these celebrities do so people can learn and not fall for it.
I could remember going to switch on the generator at 2am and my dad waking up to shout at me for disturbing his sleep "cos of some job I probably won't get paid for" I just begged him and went on to work and I didn't even know it would be all for nothing! pic.twitter.com/K2HTw1n9yh
— Enitan (@bolu__temi) January 6, 2021
More from Society
global health policy in 2020 has centered around NPI's (non-pharmaceutical interventions) like distancing, masks, school closures
these have been sold as a way to stop infection as though this were science.
this was never true and that fact was known and knowable.
let's look.
above is the plot of social restriction and NPI vs total death per million. there is 0 R2. this means that the variables play no role in explaining one another.
we can see this same relationship between NPI and all cause deaths.
this is devastating to the case for NPI.
clearly, correlation is not proof of causality, but a total lack of correlation IS proof that there was no material causality.
barring massive and implausible coincidence, it's essentially impossible to cause something and not correlate to it, especially 51 times.
this would seem to pose some very serious questions for those claiming that lockdowns work, those basing policy upon them, and those claiming this is the side of science.
there is no science here nor any data. this is the febrile imaginings of discredited modelers.
this has been clear and obvious from all over the world since the beginning and had been proven so clearly by may that it's hard to imagine anyone who is actually conversant with the data still believing in these responses.
everyone got the same R
these have been sold as a way to stop infection as though this were science.
this was never true and that fact was known and knowable.
let's look.
above is the plot of social restriction and NPI vs total death per million. there is 0 R2. this means that the variables play no role in explaining one another.
we can see this same relationship between NPI and all cause deaths.
this is devastating to the case for NPI.
clearly, correlation is not proof of causality, but a total lack of correlation IS proof that there was no material causality.
barring massive and implausible coincidence, it's essentially impossible to cause something and not correlate to it, especially 51 times.
this would seem to pose some very serious questions for those claiming that lockdowns work, those basing policy upon them, and those claiming this is the side of science.
there is no science here nor any data. this is the febrile imaginings of discredited modelers.
this has been clear and obvious from all over the world since the beginning and had been proven so clearly by may that it's hard to imagine anyone who is actually conversant with the data still believing in these responses.
everyone got the same R
this methodology is a little complex, so let me explain what i did.
— el gato malo (@boriquagato) May 30, 2020
a few EU countries provide real day of death data. this lets us plot meaningful curves to show rate of disease change.
what struck me is how similar all the curves were.
everyone got the same shape. pic.twitter.com/bN0hILzoSl
I've seen many news articles cite that "the UK variant could be the dominant strain by March". This is emphasized by @CDCDirector.
While this will likely to be the case, this should not be an automatic cause for concern. Cases could still remain contained.
Here's how: 🧵
One of @CDCgov's own models has tracked the true decline in cases quite accurately thus far.
Their projection shows that the B.1.1.7 variant will become the dominant variant in March. But interestingly... there's no fourth wave. Cases simply level out:
https://t.co/tDce0MwO61
Just because a variant becomes the dominant strain does not automatically mean we will see a repeat of Fall 2020.
Let's look at UK and South Africa, where cases have been falling for the past month, in unison with the US (albeit with tougher restrictions):
Furthermore, the claim that the "variant is doubling every 10 days" is false. It's the *proportion of the variant* that is doubling every 10 days.
If overall prevalence drops during the studied time period, the true doubling time of the variant is actually much longer 10 days.
Simple example:
Day 0: 10 variant / 100 cases -> 10% variant
Day 10: 15 variant / 75 cases -> 20% variant
Day 20: 20 variant / 50 cases -> 40% variant
1) Proportion of variant doubles every 10 days
2) Doubling time of variant is actually 20 days
3) Total cases still drop by 50%
While this will likely to be the case, this should not be an automatic cause for concern. Cases could still remain contained.
Here's how: 🧵
One of @CDCgov's own models has tracked the true decline in cases quite accurately thus far.
Their projection shows that the B.1.1.7 variant will become the dominant variant in March. But interestingly... there's no fourth wave. Cases simply level out:
https://t.co/tDce0MwO61
Just because a variant becomes the dominant strain does not automatically mean we will see a repeat of Fall 2020.
Let's look at UK and South Africa, where cases have been falling for the past month, in unison with the US (albeit with tougher restrictions):
Furthermore, the claim that the "variant is doubling every 10 days" is false. It's the *proportion of the variant* that is doubling every 10 days.
If overall prevalence drops during the studied time period, the true doubling time of the variant is actually much longer 10 days.
Simple example:
Day 0: 10 variant / 100 cases -> 10% variant
Day 10: 15 variant / 75 cases -> 20% variant
Day 20: 20 variant / 50 cases -> 40% variant
1) Proportion of variant doubles every 10 days
2) Doubling time of variant is actually 20 days
3) Total cases still drop by 50%
