SCIENCE is good. The use of the scientific method was first found in Babylonian texts and was filtered through the mind of Aristotle. It travelled, gaining definition and seriousness, via Arab physicists and the Somerset monk and Oxford scholar Roger Bacon. From there it bounced through the minds of Galileo, Descartes and Newton until finally becoming codified and universally accepted as: (1) observation and experiment, (2) hypothesis, (3) verification by fresh observation and experiment.
The government today claims that it is led by data, not dates. The government’s policies on lockdown and Covid are not political but strictly ‘based on the science’. Government information films are fronted by scientific high priests. Never in the history of the UK has public policy been so outsourced to the men and women in lab coats.
Ranged against them are the rag-tag, amateur and by definition ignorant ranks of the lockdown sceptics, baffled by numbers and complaining about ongoing restrictions in the face of mutations and variants.
Researchers at MIT set out to find out the way that US lockdown sceptics, and in particular mask sceptics, were using data, what data they were using and what primary colours they were using for their fingerpaints.
They were taken aback. The study, ‘Viral Visualizations: How Coronavirus Skeptics Use Orthodox Data Practices to Promote Unorthodox Science Online’ instead proves that those sceptical of a raft of government policies introduced to fight Covid are not making anything up with the science. In many cases, they are far more attuned to the meanings of the available data than those promoting the government lines. So much so that at one point the MIT team suggest that far from allowing greater public access to the data, the data should be made more difficult to find:
‘These findings suggest that the ability for the scientific community and public health departments to better convey the urgency of the US coronavirus pandemic may not be strengthened by introducing more downloadable datasets . . .
‘In other words, our paper introduces new ways of thinking about “democratizing” data analysis and visualization.
‘Convincing anti-maskers to support public health measures in the age of COVID-19 will require more than “better” visualizations, data literacy campaigns, or increased public access to data. Rather, it requires a sustained engagement with the social world of visualizations and the people who make or interpret them.’
What the MIT team has discovered is not what was assumed, mostly by government-supporting scientists, that the general public were, ‘data illiterate’: far from it. Allowing them unhindered access to the data, instead of undermining lockdown-sceptics, strengthens their hand. They sound baffled by the sceptics who ‘often reveal themselves to be more sophisticated in their understanding of how scientific knowledge is socially constructed than their ideological adversaries, who espouse naïve realism about the “objective” truth of public health data’.
Dismissing the sceptics is problematical because to do so, as many in politics do, threatens to undermine basic trust in science. The public policy establishment finds itself in opposition to those who ‘value unmediated access to information and privilege personal research and direct reading over “expert” interpretations. Its members value individual initiative and ingenuity, trusting scientific analysis only insofar as they can replicate it themselves by accessing and manipulating the data firsthand’.
This sceptical approach has focused upon certain methods used by the government, particularly its focus on raw death data. Any death, where an individual has Covid, is counted as a Covid death. Under sceptic-led scrutiny, recent reports accept that at least 30 per cent of Covid deaths are not Covid deaths at all, but that the key vector has been other health concerns. New studies suggest that in parts of the country upwards of 30 per cent of Covid infections leading to death were caught within hospitals, causing even more relevant questions to be asked.
The key aspect of the Government’s approach to its data which triggers the more sceptical observers has been the appearance of certainty. As the scientific method has become the guiding light for using empirical evidence to drive policy, then certainty in the field of science should and must be used with extreme caution. That has not been how the establishment have played things. They have pushed forward with what appears to be absolute knowledge. They think that the people are stupid and key figures in the establishment scientific community ‘often do not believe that people will understand and be able to interpret results that communicate uncertainty’. The problem is that pretending they know more than they do and suppressing doubt allows those who already lack trust in the Government to point to obvious inaccuracies. This creates a strong belief that the authorities are a ‘paternalistic, condescending elite that expects intellectual subservience rather than critical thinking from the lay public’.
The paper accepts that the groups of data-based sceptics ‘espouse a vision of science that is radically egalitarian and individualist. This study forces us to see that coronavirus skeptics 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’.
Then comes the pay-off. For some reason the MIT researchers, obviously so disgusted by finding out that ordinary people are rigorous and not nearly as stupid as generally thought, compare them to the tobacco lobby and the January Capitol Hill protesters.
By engaging in such wild and unreasonable ad hominems they merely look as if they are trying to be acceptable in the MIT common room, despite their findings. Those findings are clear that if anybody is applying the traditional idea behind the scientific method, it is not those supporting the Government’s approach to lockdown policy, but those questioning it.