6 January 2020 #MAGAanalysis #2020Treason
Not From Without, From Within
We'll discuss Neon Revolt's 3 articles below. If you haven't, you should read them now. Before we turn to them, I'll offer my own thoughts about this terrible
Even typing, I must pause and look at those words before I hit "Tweet." Not from fear for self.
Those words. Those are stunning even to me.
Even to me? I have never once been a Mike Pence fan. And, I have often judged him more harshly than I cared to express, but I am on record. Not a Pence fan.
Fear does NOT = Knowledge
I do not act on fear. I act on knowledge.
But I note and heed my fears, carefully. I am afraid Neon is right.
For all my work on analysis, I just hadn't seen it that way till today.
https://t.co/UzxLPIiGDT
1) What do we think?
2) What do we know?
3) What can we prove?
Can we prove it? I'm not read in at that level. Besides, how? Our courts are as corrupt as can be. Where do you prove it?
When We Must Harden Our Hearts and Steel Our Souls
No matter how you cut it, if we wish to save America, there is a battle of one form or another in front of us. There's no getting around that.
Back in a bit...
https://t.co/10eZ9hRYFc
https://t.co/QTcT7iNadR
When I embrace a leader as my guide, I need to understand his thought, knowledge, and proof. And that means slow, careful reading and notation. That's what we turn to now.
"The Democrat Party and its political operatives, with the unwitting aid of “useful idiots” from the
Republican Party, stole the presidential election from Donald J. Trump."
included:
1) Changes in the law approved by State Legislatures;
2) Rule changes and new guidance
initiated by Secretaries of State or other election officials;
3) Court rulings and interventions;
4) and the aggressive use of so-called “public-private partnerships” to commandeer and manipulate the
election process in key Democrat strongholds such as Wayne County, Michigan and Dane County,
Wisconsin.
1) Relaxing mail-in and absentee ballot rules;
2) Sending absentee or mail-in ballots or
3) Applications for such ballots to every voter (universal
mailing);
4) Increasing both the legal and
5) Illegal use of drop boxes;
6) Ballot harvesting; and
7) The use of corrupted voting machines.
1) Relaxation of ID verification;
2) Reduced signature matching requirements;
3) Illegally counting naked ballots to increase ballot curing –
4) Both legal and illegal; and
5) Reduced poll watching and observing.
More from Pasquale "Pat" Scopelliti
More from Government
Abbott is pushing a lie to protect incompetence. There is no Federal oversight of the Texas Grid, ergo fewer regulations (sound familiar) - so point one: state legislature needs reform. 2/
2. Point 2: there were clear signs the grid would get overloaded under extreme cold conditions. Why? Due to a vacuum of regulations mandating winterization of turbines and power generators. This from sources, in Texas!
3. Point 3: Of the power shortfall that hit Texas, over 80% was due to problems at coal and gas fired plants. Power generators were just not winterized. Decisions to do so have been ignored since the 1990s.
4. Point 4: these are winterized wind turbines in Denmark. The ocean is frozen. The turbines are generating.
5. #Texas| the main issue is: catastrophic governance at the State level (no Federal oversight of the Texas grid) failing to allocate funding to winterise the Natural Gas, Coal and Wind Turbine elements that contribute to the grid. (~ 80/20
Texas Gov. Abbott blames solar and wind for the blackouts in his state and says "this shows how the Green New Deal would be a deadly deal for the United States of America" pic.twitter.com/YfVwa3YRZQ
— Andrew Lawrence (@ndrew_lawrence) February 17, 2021
2. Point 2: there were clear signs the grid would get overloaded under extreme cold conditions. Why? Due to a vacuum of regulations mandating winterization of turbines and power generators. This from sources, in Texas!
3. Point 3: Of the power shortfall that hit Texas, over 80% was due to problems at coal and gas fired plants. Power generators were just not winterized. Decisions to do so have been ignored since the 1990s.
4. Point 4: these are winterized wind turbines in Denmark. The ocean is frozen. The turbines are generating.
Same thing in Denmark. It's cold enough here that the ocean is frozen and yet look at those reliable windmills just chugging along. pic.twitter.com/1NTljk7hk9
— Elizabeth Gummere (@BethGummere) February 17, 2021
5. #Texas| the main issue is: catastrophic governance at the State level (no Federal oversight of the Texas grid) failing to allocate funding to winterise the Natural Gas, Coal and Wind Turbine elements that contribute to the grid. (~ 80/20
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!