The BBC boat is not about to be rocked by its newly appointed Chairman; but the blame for which lies with a blustering, but backsliding & bottling Boris Johnson.
My latest for
https://t.co/LRmRlaJFpk
Doesn't exactly suggest a radical reformer, does it?
Sadly, BBC's new chairman looks unlikely to change that.
#DefundTheBBC
https://t.co/IkYKDZqFf1
ICYMI: \u201cThere are millions of Americans who are very worried one man can create a lie so huge that his supporters believe in him over the principle of democracy."@maitis pushes Tea Party Movement co-founder @michaeljohns over his belief the election was "stolen"#Newsnight pic.twitter.com/SENIYKdbsd
— BBC Newsnight (@BBCNewsnight) January 14, 2021
No 'seemed' about it. News-Watch survey established it was skewed 2:1 or more pro-Remain.
Oh, but it was still "incredibly balanced", apparently.
ex-BBC journo and trenchant critic Robin Aitken.
https://t.co/ugZ0wkXD5w
Anyone who hasn't read his "The Noble Liar: How and Why the BBC Distorts the News to Promote a Liberal Agenda" needs to, pronto.
#DefundTheBBC
https://t.co/qX3Kx3SBIS
Spot-on, Robin Aitken at @spectator.
https://t.co/OfZwD94hWY>
Precisely. Blame for this is Johnson's alone
On #BBC loss of trust & audience it says: 'papered over by the generosity of the licence fee payer'.
'Generosity'? FFS, it's an illiberal, regressive tax, levied by coercion on pain of fine or imprisonment.
https://t.co/3i7FMT8vf7
More from Government
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!
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Department List of UCAS-China PROFESSORs for ANSO, CSC and UCAS (fully or partial) Scholarship Acceptance
1) UCAS School of physical sciences Professor
https://t.co/9X8OheIvRw
2) UCAS School of mathematical sciences Professor
3) UCAS School of nuclear sciences and technology
https://t.co/nQH8JnewcJ
4) UCAS School of astronomy and space sciences
https://t.co/7Ikc6CuKHZ
5) UCAS School of engineering
6) Geotechnical Engineering Teaching and Research Office
https://t.co/jBCJW7UKlQ
7) Multi-scale Mechanics Teaching and Research Section
https://t.co/eqfQnX1LEQ
😎 Microgravity Science Teaching and Research
9) High temperature gas dynamics teaching and research section
https://t.co/tVIdKgTPl3
10) Department of Biomechanics and Medical Engineering
https://t.co/ubW4xhZY2R
11) Ocean Engineering Teaching and Research
12) Department of Dynamics and Advanced Manufacturing
https://t.co/42BKXEugGv
13) Refrigeration and Cryogenic Engineering Teaching and Research Office
https://t.co/pZdUXFTvw3
14) Power Machinery and Engineering Teaching and Research
1) UCAS School of physical sciences Professor
https://t.co/9X8OheIvRw
2) UCAS School of mathematical sciences Professor
3) UCAS School of nuclear sciences and technology
https://t.co/nQH8JnewcJ
4) UCAS School of astronomy and space sciences
https://t.co/7Ikc6CuKHZ
5) UCAS School of engineering
6) Geotechnical Engineering Teaching and Research Office
https://t.co/jBCJW7UKlQ
7) Multi-scale Mechanics Teaching and Research Section
https://t.co/eqfQnX1LEQ
😎 Microgravity Science Teaching and Research
9) High temperature gas dynamics teaching and research section
https://t.co/tVIdKgTPl3
10) Department of Biomechanics and Medical Engineering
https://t.co/ubW4xhZY2R
11) Ocean Engineering Teaching and Research
12) Department of Dynamics and Advanced Manufacturing
https://t.co/42BKXEugGv
13) Refrigeration and Cryogenic Engineering Teaching and Research Office
https://t.co/pZdUXFTvw3
14) Power Machinery and Engineering Teaching and Research
On the occasion of youtube 20k and Twitter 70k members
A small tribute/gift to members
Screeners
technical screeners - intraday and positional both
before proceeding - i have helped you , can i ask you so that it can help someone else too
thank you
positional one
run - find #stock - draw chart - find levels
1- Stocks closing daily 2% up from 5 days
https://t.co/gTZrYY3Nht
2- Weekly breakout
https://t.co/1f4ahEolYB
3- Breakouts in short term
https://t.co/BI4h0CdgO2
4- Bullish from last 5
intraday screeners
5- 15 minute Stock Breakouts
https://t.co/9eAo82iuNv
6- Intraday Buying seen in the past 15 minutes
https://t.co/XqAJKhLB5G
7- Stocks trading near day's high on 5 min chart with volume BO intraday
https://t.co/flHmm6QXmo
Thank you
A small tribute/gift to members
Screeners
technical screeners - intraday and positional both
before proceeding - i have helped you , can i ask you so that it can help someone else too
thank you
positional one
run - find #stock - draw chart - find levels
1- Stocks closing daily 2% up from 5 days
https://t.co/gTZrYY3Nht
2- Weekly breakout
https://t.co/1f4ahEolYB
3- Breakouts in short term
https://t.co/BI4h0CdgO2
4- Bullish from last 5
intraday screeners
5- 15 minute Stock Breakouts
https://t.co/9eAo82iuNv
6- Intraday Buying seen in the past 15 minutes
https://t.co/XqAJKhLB5G
7- Stocks trading near day's high on 5 min chart with volume BO intraday
https://t.co/flHmm6QXmo
Thank you
I'm going to do two history threads on Ethiopia, one on its ancient history, one on its modern story (1800 to today). 🇪🇹
I'll begin with the ancient history ... and it goes way back. Because modern humans - and before that, the ancestors of humans - almost certainly originated in Ethiopia. 🇪🇹 (sub-thread):
The first likely historical reference to Ethiopia is ancient Egyptian records of trade expeditions to the "Land of Punt" in search of gold, ebony, ivory, incense, and wild animals, starting in c 2500 BC 🇪🇹
Ethiopians themselves believe that the Queen of Sheba, who visited Israel's King Solomon in the Bible (c 950 BC), came from Ethiopia (not Yemen, as others believe). Here she is meeting Solomon in a stain-glassed window in Addis Ababa's Holy Trinity Church. 🇪🇹
References to the Queen of Sheba are everywhere in Ethiopia. The national airline's frequent flier miles are even called "ShebaMiles". 🇪🇹
I'll begin with the ancient history ... and it goes way back. Because modern humans - and before that, the ancestors of humans - almost certainly originated in Ethiopia. 🇪🇹 (sub-thread):
The famous \u201cLucy\u201d, an early ancestor of modern humans (Australopithecus) that lived 3.2 million years ago, and was discovered in 1974 in Ethiopia, displayed in the national museum in Addis Ababa \U0001f1ea\U0001f1f9 pic.twitter.com/N3oWqk1SW2
— Patrick Chovanec (@prchovanec) November 9, 2018
The first likely historical reference to Ethiopia is ancient Egyptian records of trade expeditions to the "Land of Punt" in search of gold, ebony, ivory, incense, and wild animals, starting in c 2500 BC 🇪🇹
Ethiopians themselves believe that the Queen of Sheba, who visited Israel's King Solomon in the Bible (c 950 BC), came from Ethiopia (not Yemen, as others believe). Here she is meeting Solomon in a stain-glassed window in Addis Ababa's Holy Trinity Church. 🇪🇹
References to the Queen of Sheba are everywhere in Ethiopia. The national airline's frequent flier miles are even called "ShebaMiles". 🇪🇹