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.
1/

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/
It is challenging to estimate the effect of interventions in the absence of a counterfactual. This difficulty is compounded by likely confounders, such as climate (not mentioned in the paper). Territories that implemented similar interventions might share comparable climate.
6/
This is a sophisticated piece of work, with both strengths and weaknesses. Though, to me, its primary value is the proposed methodological framework rather than its estimates of the efficacy of individual interventions, which efficacy remain debatable.
7/
There is room for scientific discussion about how solid the estimates presented in the paper may be. Though, accusing colleagues expressing reservations about the robustness of some of the findings of 'spreading disinformation' feels inadequate, to say the least.
8/
This paper has generated endless conflict. One intriguing feature is that all the spats are around 'educational settings'. Interestingly, the paper also claims that T&T and isolation of cases, among other measures, are completely ineffective, yet no one seems to care ... 🤔
9/

More from Science

What are the classics of the "Science of Science" or "Meta Science"? If you were teaching a class on the subject, what would go in the syllabus?

Here's a (very disorganized and incomplete) handful of suggestions, which I may add to. Suggestions welcome, especially if you've dug into relevant literatures.

1. The already classic "Estimating the reproducibility of
psychological science" from the Open Science Collaboration of @BrianNosek et al.
https://t.co/yjGczLZ6Je

(Look at that abstract, wow!)


Many people had pointed out problems with standard statistical methods, going back decades (what are the best refs?). But this paper was a sledgehammer, making it impossible to ignore the question: what, if anything, were we actually learning from all those statistical studies?

2. Dean Keith Simonton's book "Creativity in Science: Chance, Logic, Genius, and Zeitgeist". If an essentially scientometric book could be described as a fun romp through science & creativity, this would be it

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A brief analysis and comparison of the CSS for Twitter's PWA vs Twitter's legacy desktop website. The difference is dramatic and I'll touch on some reasons why.

Legacy site *downloads* ~630 KB CSS per theme and writing direction.

6,769 rules
9,252 selectors
16.7k declarations
3,370 unique declarations
44 media queries
36 unique colors
50 unique background colors
46 unique font sizes
39 unique z-indices

https://t.co/qyl4Bt1i5x


PWA *incrementally generates* ~30 KB CSS that handles all themes and writing directions.

735 rules
740 selectors
757 declarations
730 unique declarations
0 media queries
11 unique colors
32 unique background colors
15 unique font sizes
7 unique z-indices

https://t.co/w7oNG5KUkJ


The legacy site's CSS is what happens when hundreds of people directly write CSS over many years. Specificity wars, redundancy, a house of cards that can't be fixed. The result is extremely inefficient and error-prone styling that punishes users and developers.

The PWA's CSS is generated on-demand by a JS framework that manages styles and outputs "atomic CSS". The framework can enforce strict constraints and perform optimisations, which is why the CSS is so much smaller and safer. Style conflicts and unbounded CSS growth are avoided.