A 2012 recording of former Belarusian KGB chief suggests President Alexander Lukashenko sanctioned assassinations of opponents abroad. Specifically mentioned is Belarus-born journalist Pavel Sheremet, who was killed by a car bomb in central Kyiv, Ukraine, in July 2016.
Belarus president Alexander Lukashenko authorised political murders in Germany in recent years, according to a bugged meeting of his former spy-chief. https://t.co/XWoiaemvuv
— EUobserver (@euobs) January 4, 2021
More from Government
1 of 19) A number of tweets were posted by @LLinWood beginning late last night and into the morning. There are a total of 19. This thread has compiled all.
{“Shots fired across the bow”}
{Warning to traitors}
{Light will reveal the evil plans}
{You were warned traitors}
{“Shots fired across the bow”}
{Warning to traitors}
{Light will reveal the evil plans}
{You were warned traitors}
As background to tweets I am about to post, you should read this article carefully. I ask that you read each of my tweets carefully & decide if the information conveyed demands that Patriots rise up so that every lie will be revealed.@realDonaldTrumphttps://t.co/9KIX4DEtha
— Lin Wood (@LLinWood) January 4, 2021
Which metric is a better predictor of the severity of the fall surge in US states?
1) Margin of Democrat victory in Nov 2020 election
or
2) % infected through Sep 1, 2020
Can you guess which plot is which?
The left plot is based on the % infected through Sep 1, 2020. You can see that there is very little correlation with the % infected since Sep 1.
However, there is a *strong* correlation when using the margin of Biden's victory (right).
Infections % from https://t.co/WcXlfxv3Ah.
This is the strongest single variable I've seen in being able to explain the severity of this most recent wave in each state.
Not past infections / existing immunity, population density, racial makeup, latitude / weather / humidity, etc.
But political lean.
One can argue that states that lean Democrat are more likely to implement restrictions/mandates.
This is valid, so we test this by using the Government Stringency Index made by @UniofOxford.
We also see a correlation, but it's weaker (R^2=0.36 vs 0.50).
https://t.co/BxBBKwW6ta
To avoid look-ahead bias/confounding variables, here is the same analysis but using 2016 margin of victory as the predictor. Similar results.
This basically says that 2016 election results is a better predictor of the severity of the fall wave than intervention levels in 2020!
1) Margin of Democrat victory in Nov 2020 election
or
2) % infected through Sep 1, 2020
Can you guess which plot is which?
The left plot is based on the % infected through Sep 1, 2020. You can see that there is very little correlation with the % infected since Sep 1.
However, there is a *strong* correlation when using the margin of Biden's victory (right).
Infections % from https://t.co/WcXlfxv3Ah.
This is the strongest single variable I've seen in being able to explain the severity of this most recent wave in each state.
Not past infections / existing immunity, population density, racial makeup, latitude / weather / humidity, etc.
But political lean.
One can argue that states that lean Democrat are more likely to implement restrictions/mandates.
This is valid, so we test this by using the Government Stringency Index made by @UniofOxford.
We also see a correlation, but it's weaker (R^2=0.36 vs 0.50).
https://t.co/BxBBKwW6ta
To avoid look-ahead bias/confounding variables, here is the same analysis but using 2016 margin of victory as the predictor. Similar results.
This basically says that 2016 election results is a better predictor of the severity of the fall wave than intervention levels in 2020!
