An unexpected side effect of the pandemic was the rapid and sustained development of a new set of grassroots checks and balances counterbalancing official scientific health narratives. This was not always obvious, and its nature and effectiveness only became clear gradually. Given the continued development of social media, home working and more sophisticated online working group platforms, and other tools, it may almost look inevitable. But as those involved might say, “Necessity is the mother of invention.” This may prove be one of the enduring legacies of the pandemic as its potential is much wider than a single area of concern.
Apart from anecdotal evidence of this development there is now some research evidence. The research is to be found in a preprint paper by Lee, Yang et al. of Massachusetts Institute of Technology (MIT) entitled “Viral Visualisations: How Coronavirus Skeptics Use Orthodox Data Practices to Promote Unorthodox Science Online“. Much of the content of the study addresses matters surrounding the visual representation of data but it also contains valuable contextual analysis which provides clues to the future of scientific discourse.
The Lee, Yang et al. paper “investigates how pandemic visualisations [of data] circulated on social media, and shows that people who mistrust the scientific establishment often deploy the same rhetorics of data-driven decision making used by experts, but to advocate for radical policy changes”. It refers to the opponents of lockdowns, social-distancing and face masks as “anti-maskers”, which is rather unflattering shorthand, but as part of its overall analysis it clearly shows that a mix of traditionally educated scientists and researchers, along with data specialists and interested members of the general public, have begun to work together systematically. They are using open and closed group social media to enter scientific debates often with a high level of sophistication and increasing credibility.
The study provides good evidence to believe that, at least in some cases, a new collegiate form of narrative is emerging. That is one which is neither non-scientific nor pseudo-scientific but simply an alternative scientific narrative. Alternative, that is, to the one provided by official government-scientific and mainstream media sources. That is partly because it is based on the same data. In the words of Lee, Yang et al. “there is a fundamental epistemological [knowledge related] conflict between maskers [mainstream official viewpoints on science and policy] and anti-maskers [those who question mainstream official viewpoints on science and policy], who use the same data but come to such different conclusions”. (My words in square brackets.)
There is room for alternative viewpoints because “data [or indeed ‘the science’] is not a neutral substrate that can be used for good or for ill. Indeed, anti-maskers often reveal themselves to be more sophisticated in their understanding of how scientific knowledge is socially constructed than their ideological adversaries, who espouse naive realism about the ‘objective’ truth of public health data. Quantitative data is culturally and historically situated; the manner in which it is collected, analysed, and interpreted reflects a deeper narrative that is bolstered by the collective effervescence found within social media communities”. Put differently: “there is no such thing as dispassionate or objective data analysis. Instead, there are stories: stories shaped by cultural logics, animated by personal experience, and entrenched by collective action”. The same, we might add, applies to all matters of presentation and communication.
Furthermore, Lee, Yang et al. observe: “Most fundamentally, the groups we studied believe that science is a process, and not an institution.” That is precisely the point and nature of the scientific method. They add:
While academic science is traditionally a system for producing knowledge within a laboratory, validating it through peer review, and sharing results within subsidiary communities, anti-maskers reject this hierarchical social model. They espouse a vision of science that is radically egalitarian and individualist. This study forces us to see that coronavirus sceptics champion science as a personal practice that prizes rationality and autonomy; for them, it is not a body of knowledge certified by an institution of experts.
Having said this, we might submit that the study has also discovered characteristics which suggest that, whilst the more developed groups are egalitarian, they also mimic “institutional type” checks and balances on their members’ output. One might go so far as to say that they actually are a new form of “collective peer review”. That is so far as they are providing critiques which are supported by the data. That is both internally, within the way this type of group operates, and as an “external examiner” of the work of others outside the group. This should naturally be differentiated from less considered groups which pluck ideas out of nowhere and generate mere propaganda. Some trained scientists and traditional institutions are more open to debate and other engagement than others. It is plausible to suggest that those who choose to engage, in an informal or more structured way, with the more developed groups might find it a positive process rather than a distraction to be avoided.
In the most scientifically/data literate groups, the following characteristics were observed by Lee, Yang et al. which, while linked to visualisations, have much wider application:
There is a commitment to quality:
- “we find that anti-mask groups on Twitter often create polished counter-visualisations that would not be out of place in scientific papers, health department reports, and publications like the Financial Times”.
- “Qualitative analysis of anti-mask groups gives us an interactional view of how these groups leverage the language of scientific rigour – 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.”
- “anti-mask groups practice a form of data literacy in spades. Within this constituency, unorthodox viewpoints do not result from a deficiency of data literacy; sophisticated practices of data literacy are a means of consolidating and promulgating views that fly in the face of scientific orthodoxy”.
We might say that they seek to, and often do, really know their stuff.
There is a commitment to openness:
- “Among other initiatives, these groups argue for open access to government data (claiming that CDC and local health departments are not releasing enough data for citizens to make informed decisions), and they use the language of data-driven decision-making to show that social distancing mandates are both ill-advised and unnecessary.”
- “Critically assessing data representations”. This recognises that “specific types of visualisations can obscure or highlight information”. A simple example given by the study is that in U.S. “state charts, counties with hugely different populations can be next to each other. The smaller counties are always going to look calm even if per capita they are doing the same or worse”.
There is an emphasis on original content – taking matters back to original source material/data – avoiding secondary material/data presentations:
- “Many anti-maskers express mistrust for academic and journalistic accounts of the pandemic, proposing to rectify alleged bias by ‘following the data’ and creating their own data visualisations. Indeed, one Facebook group within this study has very strict moderation guidelines that prohibit the sharing of non-original content so that discussions can be ‘guided solely by the data’.”
- “Some group administrators even impose news consumption bans on themselves so that ‘mainstream’ models do not ‘cloud their analysis’. In other words, anti-maskers value unmediated access to information and privilege personal research and direct reading over ‘expert’ interpretations.”
There is an emphasis on ‘Critically assessing data sources’ .
- “Even as these users learn from each other to collect more data, they remain critical about the circumstances under which the data are collected and distributed. Many of the users believe that the most important metrics are missing from government-released data.”
- Therefore, there is also emphasis within such groups on:
- Which metrics matter e.g. deaths or cases?
- What data has not been provided by the authorities?
- What to do about official datasets constructed in “fundamentally subjective ways” e.g. some is “coded, cleaned, and aggregated… by government data analysts”.
- What to do if there is lack of transparency within official data collection systems.
There is a recognition of context:
- “Even when local governments do provide data, however, these users also contend that the data requires context in order for any interpretation to be meaningful. For example, metrics like hospitalisation and infection rates”.
- This includes keeping the science/data analysis/presentation what we might call grounded. “Applying data to real-world situations. Ultimately, anti-mask users emphasise that they need to apply this data to real-world situations.” That included seeking answers so they could better inform themselves, their families and others.
There is an emphasis on training up others/education:
- “In order to create these original visualisations, users provide numerous tutorials on how to access government health data.”
- “The discussion-based nature of these Facebook groups also give these followers a space to learn and adapt from others, and to develop processes of critical engagement.”
Note: The Lee, Yang et al. study suggests this type of engagement is also sometimes used as a means to achieve “political radicalisation”. That may become an even more interesting observation looking to the future as different groups focus on particular issues including post-pandemic accountability.
There is an attempt to identify bias and politics in data:
- “[Anti-maskers] are… mindful to note that these analyses only represent partial perspectives that are subject to individual context and interpretation.” One is quoted as saying: “That’s why scientists use controls… to protect ourselves from our own biases. And this is one of the reasons why I disclose my biases to you. That way you can evaluate my conclusions in context. Hopefully, by staying close to the data, we keep the effect of bias to a minimum.”
- “these groups seek to identify bias by being critical about specific profit motives that come from releasing (or suppressing) specific kinds of information.”
One of the things which the pandemic has revived interest in is the broad subject area of research bias which includes issues around reporting (or not reporting) and the nexus with the media.
‘Appeals to scientific authority.’
- Many anti-maskers refer to their qualifications, university or publications which might help support their ‘scientific legitimacy’.
This has all been achieved in the face of censorship. The study notes that: “As of this writing, Facebook has banned some of the groups we studied, who have since moved to more unregulated platforms.”
Overall, while still at a relatively early stage of development, this points to a new shape for the mounting of ever more credible challenges to the ‘new orthodoxy’ of lockdowns, social distancing, mask mandates in schools, business closures, and so on. It is a form of inquiry that is not predisposed to cover-ups and will not be restricted by the terms of the promised official public inquiry, or the one after that. It is science as dissent.
Cephas Alain is the pseudonym of a retired lawyer.
