@nntaleb 1/10
Science is assumed to be “evidence-based” but that term alone doesn’t mean much. What constitutes good evidence? How is evidence being used? Is it supporting or refuting a hypothesis? Was the hypothesis and experimental design predetermined or found ex post facto?

@engexplain @nntaleb 2/10
The reality is you can find “evidence” for almost any narrative. Limit the sample size, cherry-pick studies, etc. Systematic reviews, meta analyses, and randomized controlled trials are all susceptible to selective interpretation/narrative fallacy.
@engexplain @nntaleb 3/10
At the heart of the problem is the over-reliance on simplistic statistical techniques that do little more than quantify 2 things moving together.
@engexplain @nntaleb 4/10
Take Pearson’s correlation, based on covariance. Variation can increase simultaneously across 2 variables for countless reasons, most of which are spurious. Yet this simple notion of “causality” undergirds much of scientific literature.
@engexplain @nntaleb 5/10
Information-theoretic (entropy based) approaches on the other hand can assess *general* measures of dependence. Rather than some specialized (linear) view based on concurrent variation, entropy encompasses the amount of information contained in and between variables.
@engexplain @nntaleb 6/10
If you were genuinely interested in giving the term “evidence” an authentic and reliable meaning then the methods used to underpin an assertion would be rigorous.
@engexplain @nntaleb 7/10
We wouldn’t look to conveniently simplistic methods to denote something as evidential, rather we would look for a measure capable of assessing the expected amount of information held in a random variable; there is nothing more fundamental than information.
@engexplain @nntaleb 8/10
Consider Mutual Information (MI), which quantifies the amount of information obtained about one random variable through observing another random variable. This observing of the relationship between variables is what measurement and evidence is all about.
@engexplain @nntaleb 9/10
MI determines how different joint entropy is from marginal entropies. If there is a genuine dependence between variables we would expect information gathered from all variables at once (joint) to be less than the sum of information from independent variables (marginals).
@engexplain @nntaleb 10/10
If “evidence-based” science was genuinely invested in authentic measurement it would leverage *general* measures of dependence; that demands an approach rooted in information-theory. Without entropy you’re just picking data, choosing a narrative, and calling it “evidence.”

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@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.
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/
Read this thread from @lilithsaintcrow. I really mean it. Just read it. Because if what she is saying is true (and I happen to think it is) it explains *so much*

An example using the Flat Earthers: A thread of many parts:


I'm firmly convinced that the flat Earth thing was started by some adolescent trolls with nothing more productive to do. They didn't believe it, but they thought it was entertaining to keep pretending that they did.

You can't engage with them, because they *are playing a game*. They think it's fun to see if they can get anybody to engage with something completely stupid as though it's true.

If you challenge them, the rules of the game state that they have to argue as hard and a spuriously as they like, but *never* to admit that the Earth is not in fact flat. I suppose you have to make up your own entertainment on 4chan or whatever hole this was conceived in.

It's annoying as hell, but I suppose it doesn't do much harm.. except to folks like this:

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Fake chats claiming to be from the Irish African community are being disseminated by the far right in order to suggest that violence is imminent from #BLM supporters. This is straight out of the QAnon and Proud Boys playbook. Spread the word. Protest safely. #georgenkencho


There is co-ordination across the far right in Ireland now to stir both left and right in the hopes of creating a race war. Think critically! Fascists see the tragic killing of #georgenkencho, the grief of his community and pending investigation as a flashpoint for action.


Across Telegram, Twitter and Facebook disinformation is being peddled on the back of these tragic events. From false photographs to the tactics ofwhite supremacy, the far right is clumsily trying to drive hate against minority groups and figureheads.


Declan Ganley’s Burkean group and the incel wing of National Party (Gearóid Murphy, Mick O’Keeffe & Co.) as well as all the usuals are concerted in their efforts to demonstrate their white supremacist cred. The quiet parts are today being said out loud.


The best thing you can do is challenge disinformation and report posts where engagement isn’t appropriate. Many of these are blatantly racist posts designed to drive recruitment to NP and other Nationalist groups. By all means protest but stay safe.