1) Science denial is destroying our societies, our civilization. Various vested interests, usually right wing ideologues find various scientific facts and information contrary to their agenda, so through propaganda they are orchestrating the public into denying this science.
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"NO LONGER BEST IN THE WORLD"
UNEP's new Human Development Index includes a new (separate) index: Planetary pressures-adjusted HDI (PHDI). News in Norway is that its position drops from #1 to #16 because of this, while Ireland rises from #2 to #1.
Why?
https://t.co/aVraIEzRfh
Check out Norway's 'Domestic Material Consumption'. Fossil fuels are no different here to Ireland's. What's different is this huge 'non-metallic minerals' category.
(Note also the jump in 1998, suggesting data problems.)
https://t.co/5QvzONbqmN
In Norway's case, it looks like the apparent consumption equation (production+imports-exports) for non-metal minerals is dominated by production: extraction of material in Norway.
https://t.co/5QvzONbqmN
And here we see that this production of non-metallic minerals is sand, gravel and crushed rock for construction. So it's about Norway's geology.
https://t.co/y6rqWmFVWc
Norway drops 15 places on the PHDI list not because of its CO₂ emissions (fairly high at 41st highest in the world per capita), but because of its geology, because it shifts a lot of rock whenever it builds anything.
UNEP's new Human Development Index includes a new (separate) index: Planetary pressures-adjusted HDI (PHDI). News in Norway is that its position drops from #1 to #16 because of this, while Ireland rises from #2 to #1.
Why?
https://t.co/aVraIEzRfh

Check out Norway's 'Domestic Material Consumption'. Fossil fuels are no different here to Ireland's. What's different is this huge 'non-metallic minerals' category.
(Note also the jump in 1998, suggesting data problems.)
https://t.co/5QvzONbqmN

In Norway's case, it looks like the apparent consumption equation (production+imports-exports) for non-metal minerals is dominated by production: extraction of material in Norway.
https://t.co/5QvzONbqmN

And here we see that this production of non-metallic minerals is sand, gravel and crushed rock for construction. So it's about Norway's geology.
https://t.co/y6rqWmFVWc

Norway drops 15 places on the PHDI list not because of its CO₂ emissions (fairly high at 41st highest in the world per capita), but because of its geology, because it shifts a lot of rock whenever it builds anything.
@mugecevik is an excellent scientist and a responsible professional. She likely read the paper more carefully than most. She grasped some of its strengths and weaknesses that are not apparent from a cursory glance. Below, I will mention a few points some may have missed.
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The paper does NOT evaluate the effect of school closures. Instead it conflates all ‘educational settings' into a single category, which includes universities.
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The paper primarily evaluates data from March and April 2020. The article is not particularly clear about this limitation, but the information can be found in the hefty supplementary material.
3/
The authors applied four different regression methods (some fancier than others) to the same data. The outcomes of the different regression models are correlated (enough to reach statistical significance), but they vary a lot. (heat map on the right below).
4/
The effect of individual interventions is extremely difficult to disentangle as the authors stress themselves. There is a very large number of interventions considered and the model was run on 49 countries and 26 US States (and not >200 countries).
5/
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I've recently come across a disinformation around evidence relating to school closures and community transmission that's been platformed prominently. This arises from flawed understanding of the data that underlies this evidence, and the methodologies used in these studies. pic.twitter.com/VM7cVKghgj
— Deepti Gurdasani (@dgurdasani1) February 1, 2021
The paper does NOT evaluate the effect of school closures. Instead it conflates all ‘educational settings' into a single category, which includes universities.
2/
The paper primarily evaluates data from March and April 2020. The article is not particularly clear about this limitation, but the information can be found in the hefty supplementary material.
3/

The authors applied four different regression methods (some fancier than others) to the same data. The outcomes of the different regression models are correlated (enough to reach statistical significance), but they vary a lot. (heat map on the right below).
4/

The effect of individual interventions is extremely difficult to disentangle as the authors stress themselves. There is a very large number of interventions considered and the model was run on 49 countries and 26 US States (and not >200 countries).
5/
