Mask blindness at MIT
Some idiots at MIT (and one from Wellesley!) accidentally wrote a paper about themselves.
Today’s post is dedicated to all those who didn’t get into a fancy university and have felt somehow less adequate as a result. You probably dodged a bullet.
Five enterprising young people put together a nice little paper about…umm… let’s just have them explain.
Viral Visualizations: How Coronavirus Skeptics Use Orthodox Data Practices to Promote Unorthodox Science Online (Lee et al. 20211)
This paper investigates how pandemic visualizations circulated on social media, and shows that people who mistrust the scientific establishment often deploy the same rhetorics [sic] of data-driven decision- making used by experts, but to advocate for radical policy changes.
By “pandemic visualizations” they mean various representations of scientific data (you know, charts and graphs and stuff). These nasty little data visualizations are very dangerous tools in the hands of the public, since they are about power rather than knowledge (um… what?):
Historians, anthropologists, and geographers have long shown how visualizations—far from an objective representation of knowledge—are often, in fact, representations of power. To address this in practice, feminist cartographers have developed quantitative GIS methods to describe and analyze differences across race, gender, class, and space, and these insights are then used to inform policymaking and political advocacy.
I’m not going to bother discussing “feminist cartographers,” or whether the research shows pie charts are oppressive (is it the name or the shape?) and just leave this whole passage for you to ponder on your own, while simply reminding everyone that MIT receives funding from the government and the government gets those funds from you and me.
The authors are concerned that regular folks are debating public policy online, and doing a good job of it. Those horrible, unorthodox thinkers are then putting convincing arguments up on social media and this is clearly a problem.
The paper discusses the online debate about current health policies generally, but the authors have put a focus on the discussion of masks to exemplify the larger debate. And oh boy did they exemplify something - about themselves.
They analyzed social media posts in places like Facebook and Twitter, pointing out that pro- and anti-mask groups come to different conclusions even though they’re using the same data.
And of course the anti-mask position makes no sense, given the “consensus of the scientific establishment.”
Qualitative analysis of anti-mask groups gives us an interactional view of how these groups leverage the language of scientific rigor—being critical about data sources, explicitly stating analytical limitations of specific models, and more—in order to support ending public health restrictions despite the consensus of the scientific establishment.
The authors are really not even trying to mask (sorry) their contempt for the anti-maskers.
We define this counterpublic’s visualization practices as “counter-visualizations” that use orthodox scientific methods to make unorthodox arguments, beyond the pale of the scientific establishment.
Yes, we are “beyond the pale of the scientific establishment.” How wrong are we about this?
However, despite a preponderance of evidence that masks are crucial to reducing viral transmission, protestors [sic] across the United States have argued for local governments to overturn their mask mandates and begin reopening schools and businesses.
Anyone who has read the posts on this blog about the scientific research on masks will of course understand that I can’t just leave that statement alone. The authors give three references to justify the claim that there is “a preponderance of evidence” that masks work. We’re going to review them (although quickly) because it’s important to see how little research they did on this, given that it’s the core of the online debate they’re analyzing.
The supposed preponderance of evidence - even considering doubting this is “beyond the pale”
The first reference is the CDC web page2 on masks – you know, the thing that everyone online is arguing about whether it’s correct or not. It seems a bit disingenuous to use the CDC as the first reference given that this is what we are all debating. I spent ten posts explaining why the CDC is full of you-know-what so I won’t go over it in detail here.
The short explanation is the CDC referenced only a handful of lab studies on masks but no randomized controlled trials (RCTs), including the studies they funded. Some lab results looked promising, but those results have consistently failed to translate into lower rates of infections in RCTs. In short, none of the CDC’s references prove masks are effective.
The second reference is:
Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis (Chu et al. 20203)
The authors of this paper were trying to determine the best distance to use for social distancing, and were also assessing face masks and eye protection.
Our search identified 172 observational studies across 16 countries and six continents, with no randomised controlled trials and 44 relevant comparative studies in health-care and non-health-care settings (n=25 697 patients).
So no randomized controlled trials were reviewed at all. And how about their findings?
The findings of this systematic review and meta-analysis support physical distancing of 1 m or moreand provide quantitative estimates for models and contact tracing to inform policy. Optimum use of face masks, respirators, and eye protection in public and health-care settings should be informed by these findings and contextual factors.
Notice that the authors are clear that they think the studies they reviewed support physical distancing, but on face masks they just say the the use of masks “should be informed by these findings.”
So they didn’t conclude that masks work – obviously they’re not shy about saying physical distancing works so it’s important that they weren’t willing to make the same statement about masks.
The third reference is just plain silly.
Masks and medical care: Two keys to Taiwan’s success in preventing COVID-19 spread (Wang et al. 20204)
This is a one page correspondence to a journal in which the authors point out that Taiwan is really close to China and people in Taiwan wear masks and seek medical care when they’re sick and Taiwan didn’t get totally wrecked by the Rona so we should all do what they do.
You think I’m kidding. I’m not kidding. Check it out for yourself. It’s basically a press release about how well the government of Taiwan handles epidemics.
At the time they wrote the paper, the “preponderance of evidence” the authors mention is therefore:
The CDC’s webpage, which listed zero clinical studies
An observational study, which listed zero clinical studies
A press release
Here’s my summary so far:
The general idea of this paper is that regular folks have done a surprisingly good job of coming up with ways to look at data on masks. Ways that are sophisticated and make it look like masks don’t really work. This is shocking to the authors of the paper since the rest of us aren’t real scientists, so how can we be so convincing?
The authors firmly believe that masks are effective at preventing the spread of SARS-CoV-2, and they view this as unquestionable. (“All hail the Fauci, for his word is the science.”) And since they thought they already knew the answer they did less work than a lazy high school student.
So tough guy, do you have better references?
Yes. Yes I do. Better in the sense that these are reviews of the scientific literature written by people who study this subject for a living. Since MIT stands for Massachusetts Institute of Technology, I assume they have a working internet connection and therefore could have done what I did and go to PubMed and, you know, look stuff up. But they didn’t so here we go.
[If my earlier posts already have you convinced, skip this part. It is, however, a useful reference if you’re debating this subject yourself.]
The authors of the paper we’re slagging here today have an issue with people who do their own reading. The authors did the highlighting on this part:
In other words, anti-maskers value unmediated access to information and privilege personal research and direct reading over “expert” interpretations.
Oh noes! We’re reading the research for ourselves! But are the anti-maskers really valuing their own interpretations over those of “experts?” Well, let’s see what the expert interpretations are, and see if it’s the pro- or anti-maskers whose opinions align with the experts.
To counter the three references from the paper here are three literature reviews conducted by people who study this subject, and which I found without the use of feminist cartography or a degree from MIT:
Use of non-pharmaceutical interventions to reduce the transmission of influenza in adults: A systematic review (Smith et al. 20155)
Keep in mind that this is the most optimistic reference of the three I’m mentioning. The authors reviewed several types of NPI, and here is what they concluded about masks:
Health professionals are at risk of becoming infected when delivering clinical care to influenza infected patients and physical barriers such as surgical masks and N95 respirators have been proven to be effective in acute settings. Using these personal physical barriers in the community is without evidence and does not seem to reduce influenza symptoms or rates of influenza. (Smith 2015)
Big shock – health care workers taking care of symptomatic patients (“in acute settings” so really sick) get some benefits from PPE, but there’s no evidence anyone else does.
This is why, during the Era of Sanity that most people call the 20th century, hospital staffs wore masks when treating infectious people, and the rest of us wore masks on Halloween.
Face masks to prevent transmission of influenza virus: a systematic review (Cowling et al. 20106)
This is a review of various studies, and the lead author (Cowling) has actually conducted studies on masks that were funded by the CDC.
In conclusion there remains a substantial gap in the scientific literature on the effectiveness of face masks to reduce transmission of influenza virus infection. While there is some experimental evidence that masks should be able to reduce infectiousness under controlled conditions, there is less evidence on whether this translates to effectiveness in natural settings. There is little evidence to support the effectiveness of face masks to reduce the risk of infection. (Cowling 2010)
I’ve said the same thing several times on this Substack. Although there is mechanistic evidence for masks, randomized controlled trials in the community setting have consistently failed to show any benefit.
Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings—Personal Protective and Environmental Measures (Xiao et al. 20207)
I found this one because it was cited by one of the references the CDC listed on their web page about mask use. That’s right, the CDC helped me find this one.
In this review, we did not find evidence to support a protective effect of personal protective measures or environmental measures in reducing influenza transmission. Although these measures have mechanistic support based on our knowledge of how influenza is transmitted from person to person, randomized trials of hand hygiene and face masks have not demonstrated protection against laboratory-confirmed influenza, with 1 exception. (Xiao 2020)
Once again, the authors tell us that although there is mechanistic evidence, actual clinical trials have failed to show any benefit. And this was cited by one of the CDC’s own references about masks.
I could go on (I already found a dozen or so of these) but the answer doesn’t really change. If we’re looking for the “scientific consensus” then this is it. These are reports written by people who study non-pharmaceutical interventions for a living, stating what they find when they review the scientific literature. It’s just not what all the acronym people (CDC, CNN, NYT, etc.) keep telling us.
Notice that I have created no charts, graphs, or other “data visualizations” - all I have done is report what’s in published research. Those anti-maskers are so convincing because they’re correct.
If the kiddies at MIT had bothered to talk to anyone who has made a career of studying this and simply asked “hey, where are the randomized controlled trials that prove masks reduce infections?” they would have gotten a very enlightening answer: they don’t exist.
I’ve had enough so let’s wrap this up
The whole paper drips with contempt for those who would question the institutional narrative, so I’m not going to bother being nice about this summary.
Do you remember earlier, when I said you may have dodged a bullet? Hundreds of years from now anthropologists are going to find a paper like this and spend countless hours trying to diagnose the mental state of the authors as they wrote it. It’s a goldmine of illucidity:
Like data feminists, anti-mask groups similarly identify problems of political power within datasets that are released (or otherwise withheld) by the US government.
That started so crazy, then came so very close to a cogent thought, that I am crying and laughing at the same time. Yes, government officials sometimes manipulate data for political ends - that’s the thing the anti-mask people are complaining about. But “anti-mask groups” are “like data feminists?” What the heck does that even mean8?
This quintet of brainwashed toddlers at a pair of overpriced universities have blindly swallowed the narrative that masks are a proven, effective means of protecting the general community from infectious disease, which is not the opinion held by most people who study this subject for a living.
It would have taken them .000001% of the time they spent goofing off on social media sites to figure this out. But they would rather smugly tell us all how dangerous it is when we think for ourselves.
Another way to look at the whole thing is this: despite the complete lack of evidence that masks work, government health officials insist they do. The evidence against masks is so clear that even people in the general public have figured it out, while “health officials” remain steadfast in their insistence that masks work, and five aspiring future bureaucrats are struggling to explain the discrepancy.
The real lesson of this paper is that these kids still believe what they’re being told by institutions and authority figures.
The most incredible part is how close the authors came to learning something important, while completely failing to understand what they just wrote. This is them describing the side they think is wrong :
Most fundamentally, the groups we studied believe that science is a process, and not an institution. As we have outlined in the case study, these groups mistrust the scientific establishment (“Science”) because they believe that the institution has been corrupted by profit motives and politics. The knowledge that the CDC and academics have created cannot be trusted because they need to be subject to increased doubt, and not accepted as consensus. (their emphasis, not mine)
(“The knowledge that the CDC and academics have created…” - I had to pause a moment and savor this little morsel.)
If I were trying to summarize a useful lesson from the mask debate I’m not sure I could have done it better, and although they wrote it, this is the point of view the authors disagree with. Science is a process, and not something dictated by an institution. Institutions can be corrupted by profit and politics. What the CDC says may not represent the consensus of actual researchers.
It’s almost tragic, seeing how close they came to a useful conclusion. But the indoctrination has so captured their minds that they can accurately describe what’s happening, yet refuse to entertain the most rational explanation.
Second, more clear summary (maybe)
When I wrote the original post I wasn’t thrilled with the summary, so here’s a clearer (or maybe just more blunt) version:
The authors of this paper are investigating the spread of what they consider medical misinformation on social media, and decided to look at the debate about masks specifically as one example.
They attempt to explain how and why “anti-maskers” are able to make such convincing arguments, given that (in the view of the authors) there is a “preponderance of evidence” that masks work.
The success of the anti-maskers must mean they are very good at propagandizing their message since they are using the published data, and the authors assume this data supports the position that masks work.
The authors assume the CDC position is not just correct, but obviously correct, and no rational review of the evidence could show otherwise.
However the authors clearly didn’t review the evidence themselves, and have chosen instead to blindly trust the authority figures. And in doing so they have completely missed (or chosen to ignore) the possibility that maybe the reason the anti-maskers are so convincing is because they are correct.
From this perspective it is the authors of this paper who are spreading misinformation, and by cloaking that misinformation in the guise of a scientific paper they are essentially doing the thing they claim to be investigating.
So in a sense they wrote a paper about themselves.
Crystal Lee, Tanya Yang, Gabrielle D Inchoco, Graham M. Jones, and Arvind Satyanarayan. 2021. Viral Visualizations: How Coronavirus Skeptics Use Orthodox Data Practices to Promote Unorthodox Science Online. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, Article 607, 1–18. DOI:https://doi.org/10.1145/3411764.3445211
https://dl.acm.org/doi/10.1145/3411764.3445211
Current page:
https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/cloth-face-cover-guidance.html
Archived page:
https://web.archive.org/web/20200703223648/https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/cloth-face-cover-guidance.html
Chu, Derek K et al. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis. The Lancet, Volume 395, Issue 10242, 1973 - 1987. DOI:https://doi.org/10.1016/S0140-6736(20)31142-9
https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)31142-9/fulltext
Vincent Yi-Fong Su, Yung-Feng Yen, Kuang-Yao Yang, Wei-Juin Su, Kun-Ta Chou, Yuh-Min Chen, and Diahn-Warng Perng. 2020. Masks and medical care: Two keys to Taiwan’s success in preventing COVID-19 spread. Travel Medicine and Infectious Disease (June 2020), 101780. https://doi.org/10.1016/j.tmaid.2020. 101780
https://www.sciencedirect.com/science/article/pii/S1477893920302702?via%3Dihub
Smith SM, Sonego S, Wallen GR, Waterer G, Cheng AC, Thompson P. Use of non-pharmaceutical interventions to reduce the transmission of influenza in adults: A systematic review. Respirology. 2015;20(6):896-903. doi:10.1111/resp.12541
https://pubmed.ncbi.nlm.nih.gov/25873071/
Cowling BJ, Zhou Y, Ip DK, Leung GM, Aiello AE. Face masks to prevent transmission of influenza virus: a systematic review. Epidemiol Infect. 2010;138(4):449-456. doi:10.1017/S0950268809991658
https://pubmed.ncbi.nlm.nih.gov/20092668/
Xiao J, Shiu E, Gao H, et al. Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings—Personal Protective and Environmental Measures. Emerging Infectious Diseases. 2020;26(5):967-975. doi:10.3201/eid2605.190994.
https://pubmed.ncbi.nlm.nih.gov/32027586/
MIT has a “data feminism” lab, if you can grit your teethe and get through it. The home page is incredibly annoying so I gave up: https://dataplusfeminism.mit.edu/