Academics need to engage with people spreading dangerous misinformation, especially under the guise of technical jargon.

If you do not respond, no one will and the world will be less informed.

The kind of engagement @jhausdorfer wants is *not possible* on the needed scale.
The idea that we should patiently educate the aggressively ignorant sounds laudable, but it practically means disengagement. How many who liked the above post consistently attempt to do this? They might try once, but they'll give up because it's too time-consuming.
Here is the thread:


Here is my response:


Note that the original post received a fair amount of attention. This is not a case where signal-boosting is a concern.
I agree completely with @jhausdorfer that you should give people the benefit of the doubt (and generally think @jhausdorfer is great). There is a skeptical view commonplace on Twitter and elsewhere that no one can ever be convinced of anything.
The obviously correct observation that many beliefs are not formed rationally has been transformed into the wildly incorrect view that people are not swayed by careful, rational discussion.
I know from vast experience that many people are willing to revise their views if you patiently explain to them what they got wrong. And even if they never say, "I was wrong", they will often moderate their tone in the future and internalize your points.
But there are types of people for whom the goal is surely not persuasion but containment. Some red flags:
a) Confident claims combined with elementary errors
b) Use of rhetorical techniques like the Gish gallop (en.wikipedia.org/wiki/Gish_gall…)
c) Condescension and insults on their part
In these cases, the goal is to convince onlookers not to listen to the person in question. One approach is to patiently respond to every claim, spending the next several weeks of your life educating them about statistics so onlookers marvel at your patience and tenacity.
This appears to be what Johannes is calling for. I may have spent as much time talking to strangers on Twitter about econometrics as any person in history. But this is time-consuming and I don't recommend engaging with the aggressively ignorant unless you get consumption value.
An alternative is to put up a sign-post. Say to bystanders: DANGER, do not trust this person. I don't think it's wrong to call my response "ridicule” in the sense of trying to make the person look ridiculous, but “ridicule” has additional connotations.
I was not simply insulting the person -- I was explaining to on-lookers exactly what was going on, exactly why it might appear as a technical discussion when it was in fact nothing of the sort.
If you insult and do nothing else, you achieve nothing. You must establish credibility with onlookers and try to explain why the person is incorrect. But if the person replies, don't make it look like "he said / she said". Leave a sign that says, “DANGER” to keep others informed.
You might say, "Of course this won't influence anyone, everyone has already picked sides, etc..." I would bet money that an experiment would show a treatment effect where bystanders reading my response updated negatively their beliefs about the original poster.
And while Johannes worries this will turn people away from the field, I think it will attract just as many. People want to informed, they want to be educated, and it is invigorating to see people who care about the truth stand up for themselves.
It is also acceptable to be funny at the expense of people who deserve it. You just have to be careful that someone really deserves it. In this case, engaging in dangerous misrepresentation, they did. The humor served a social purpose, to lower their status.
If you see an informed person arguing with someone like this, don’t just watch. Press like or retweet or comment. Make the warning sign bigger. You have credentials and information that you can use to influence people.
Fight back against the aggressively ignorant. Don't let them dominate the conversation. Lower their status in the eyes of on-lookers and reduce their influence. If you ignore them, their ideas will spread. Do your part to contain dangerous viruses, whether physical or memetic.
(@jhaushofer of course, I don't know why I am so bad at tagging people on Twitter)

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More from @Jabaluck

13 Sep
This is a very important point -- masks prevent COVID and are valuable in places where many people are dying of COVID. Currently, this is many places.

However, that doesn't mean that a cost-benefit analysis suggests, "everyone should wear masks until COVID is eradicated"
The value of masks in places where nearly everyone is vaccinated is clearly lower. Caution is necessary since, in many parts of the world, the vaccines being used have lower efficacy than in the US, meaning that masks likely have value on top of vaccines.
Additionally, masks may prevent breakthrough cases which may eventually spread to unvaccinated people. However, I haven't seen a quantitative calculation of the magnitude of this benefit -- it may be small.
Read 10 tweets
5 Sep
An intuitive way to grasp the effectiveness of masks: extrapolating from our results, every 600 people who wear masks for a year in public areas prevents 1 person from dying of COVID given status quo death rates in the US.
Note that this is *taking into account current vaccination rates in the US*. Despite the availability of vaccines in the US, the weekly death rate is higher than at any point prior to November 2020.
Here is how I arrived at this number. Our study shows that inducing a 30 pp increase in mask-use prevented 35% of COVID cases among the elderly.
Read 15 tweets
3 Sep
For those keeping track at home, this is definitely not what a confidence interval is. A 95% CI is a function of the data such that, given the data generating process with an unknown true parameter, the CI constructed in this way will contain the true parameter 95% of the time.
The idea that all values in a 95% CI are equally likely is preposterous. If one were instead constructing Bayesian credibility intervals, you do not need a gaussian prior to rule this out.
In the Bayesian problem, this would represent an absurd corner case where the data was completely uninformative about the underlying parameter within a specified range. I can't imagine how this would be a reasonable model of the situation at hand.
Read 5 tweets
3 Sep
To frame this as "mask advocates" vs. "vaccine advocates" is to thoroughly miss the point.

Everyone on earth with access to vaccines should get vaccinated.

Masks are also a powerful tool against COVID, and you've misunderstood what our study says about them.
@MartinKuldorff
Firstly, our study does not say that masks can only prevent 11% of COVID. Our study says that our intervention -- which raised surgical mask-wearing from 13% to 43% -- prevented 11% of COVID cases, and 35% among age 60+.
To put the point on your own terms -- if you vaccinated 30% of the population, would you prevent 35% of cases age 60+?
Read 14 tweets
1 Sep
I do agree that vaccines are probably even more effective than masks but there are three very important subtleties here that make the 11% way too conservative @ProfEmilyOster.
First, the 11% comes from a 30% increase in mask-use. The IV estimate (naively scaling things linearly) would thus be more like a 37% reduction in COVID from going from zero to universal masking.
Second, we find much larger effects among the elderly (a 35% reduction among 60+ without the above scaling). This suggests that the total reduction in morbidity and mortality from universal masking may be considerably larger than even the 37% number, perhaps more than 50%.
Read 4 tweets
1 Sep
Hi @benshapiro, our study DOES suggest benefits of mask-wearing for people under the age of 50:
1) We only studied adults, but for both surgical and cloth masks, we find impacts on COVID symptoms at all ages tested
The fact that we do not find an effect blood tests of age<50 is likely due to the fact that we collected blood only from a subset of symptomatic people and so our estimates on blood-test confirmed COVID are less precise.
Read 7 tweets

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