Straight to the point

Crucial amongst classical liberalism’s advantages is that it conforms to the principles of what Mark Pennington has called ‘robustness’ (Pennington 2010, p. 2). A policy, policy-making process, or policy-making institution is ‘robust’ when it takes account of two human imperfections: 

1. Our cognitive limits – even the most perceptive, erudite people will remain ignorant about the vast majority of the complex societies within which they are embedded, including about most other people’s particular needs, desires, projects, concerns, and self-conceptions. However sophisticated our models or big our data become, these limitations cannot be exceeded and are a feature of the human condition (Pennington 2021, p. 206).
2. Our competing conceptions of the good – in all social fields, be it politics, business, or friendship, we have to negotiate competing understandings of what is right and desirable. Sometimes these conceptions are shared or overlapping, but sometimes they are irreconcilable. And though they can be public-spirited or self-sacrificing, they can also be selfish and mercenary. On the whole we are neither saintly nor irredeemably evil, just different and complex.

In the simplest terms, a policy or policy-making institution is robust when it remains beneficial even when used or run by human beings at their most stupid and venal. In principle, liberalism guarantees robustness by defending our rights to property and freedom of dis/association and by favouring market solutions to political problems like education, housing, or public health (Pennington 2010, p. 4). 

This means that, in general, liberalism favours policies that allow individual people to each pursue what they judge to be most desirable, given their conception(s) of the good and circumstances. And people are able to do more-or-less what they want with what they own and to collaborate with or distance themselves from whomever they want. As such, liberalism favours policies that modestly rely on each person’s local knowledge of their own needs and conditions rather than on a group of people (like the state) having an impossibly expansive understanding of how each of its citizens lives and of what they need – thus accounting for our cognitive limits.

Similarly, because one always has the option to dissociate oneself from anyone else and to pursue one’s own projects, no one is ever made captive to anyone else’s conception of the good. Under liberalism, there are hard limits on what sort of power a person, or group thereof (again, like the state), can exercise over another. 

Of course, liberalism as briefly described here is a philosopher’s idyll rather than an accurate description of any single political system currently in existence. Nonetheless, it is frequently appealed to (or, depending on your perspective, lip-serviced) by politicians and commentators, and can provide us with a polestar in our debates over policy- and institutional design. In light of this, the recent global pandemic response has made undeniable what only few, usually fringe, writers (e.g. Feyerabend 1978) had noticed – that science itself has come to pose a threat to the ideals of liberalism and the robustness of modern states. 

This threat is a consequence of what could be called science’s ‘socio-political’ characteristics – that is, the ways in which science’s claims, techniques, and technologies interact with and affect other aspects of our social reality, including, most pertinently here, politics and policy-making. 

In modern states, scientific and other expert disciplines form what Nikolas Rose and Peter Miller call “enclosures” around particular areas of policy (Rose and Miller 1992, p. 188). Which area of policy a discipline encloses will depend on the specifics of its expertise (economics encloses welfare policy; seismology encloses earthquake planning; and epidemiology and public health encloses pandemic policy) but in each case it will enjoy a quasi-hegemonic authority over its area.

Crucially, this doesn’t mean that a particular group of government-appointed experts enjoy total authority over the contents of the policy being made – instead, it means that a particular discipline sets the bounds within which the policy debate takes place. It sets the terms and techniques and concepts with which a person needs to work for their proposals to be taken seriously. 

To illustrate this, consider the UK government’s move to close schools early on in the Covid-19 pandemic. The virus erupted into a space already tightly, even jealously, enclosed by the disciplines of public health – epidemiology, virology, immunology etc. There are well-established ways of making sense of and eventually dealing with this novel threat, such as through case monitoring, computer modelling (including the now-notorious SIR model), and pandemic planning.

In the UK, this included the Influenza Pandemic Preparedness Strategy 2011, written in response to 2009’s Swine flu which said that while school closures carried heavy costs and weren’t to be defaulted to, they could nonetheless be imposed when peak ICU demand was predicted to exceed ICU capacity (ECDC 2011; House et al. 2011; UK IPPS 2011). It also specifies that such closures would need to be prolonged to be effective.

Two things are relevant here – first, that these were the terms used to justify school closures in early 2020 and second, that they belonged to the scientific disciplines of public health alone. 

School closures were first evoked by the UK’s Scientific Advisory Group for Emergencies (SAGE) in early February when it was assessed that the effects of shutting schools were unknown (4th SAGE 2020). They were then modelled and discussed throughout the rest of February and early March, but SAGE did not make any recommendations until the 16^th of March when it stated that school closures may become necessary to push demand on ICU beds below NHS capacity (16th SAGE 2020).

Then, on March 18^th, the hammer fell and they wrote that: “the modelling now supports school closures on a national level and that the effect would be greatest if instituted early” (17th SAGE 2020). The same day, Boris Johnson announced that when the school day ended that Friday, their gates would remain shut indefinitely (Sparrow and Campbell 2020). 

Science – in this case, epidemiology – provides policy with a cosmology. It makes a target system – in this case, schools – legible by rendering it with a finite number of concepts and indicators which it then stitches together using a couple of simple relations. Schools become a site of disease transmission; pupils viral vectors; and both thus contribute to overall case numbers and pressure on ICU capacity. And, in framing the world in such terms, epidemiology gives policy-makers a way of thinking about the problem that implies its own solutions – for e.g., if you want to preserve hospital beds, you can close schools. It may not be sufficient (as SAGE did note) but on the terms given it will help. 

Though the epidemiological cosmology makes the articulation of and debate over particular policy options (such as closing schools? When? And for how long?) possible, it doesn’t determine them – as evidenced by the variety of school-closure policies across the world (UIS 2022). It does, however, delimit them. In identifying certain properties of the target system as most essential and relevant, a scientific cosmology makes these properties the policy-maker’s central concern and so sidelines strategies and proposals that do not accord them the same importance.

So, in identifying schools as essentially sites of disease transmission, epidemiology made it seem self-evident that schools could be closed if demand on ICU beds required it. It legitimised school closures as an exercise of state power – and made proposals that didn’t directly address concerns about case numbers or ICU beds seem wrongheaded or absurd. This was particularly significant in early 2020 as the epidemiological cosmology had come to eclipse all others, including other public-health related ones like education psychology (Woolhouse 2022, p. 67).

Now, while such essentialising claims are not in-and-of themselves problematic (it is hard to see how science could proceed without making at least provisional ones), they threaten both of robustness’ aspects when institutionalised at the level of policy. 

In the first instance, essentialising claims risks obscuring the intractable limits to human understanding mentioned above. Such claims are universal – in identifying some property or aspect of a thing as essential to what that thing is, they pretend to have understood what it is like for all people in all places. This, in turn, lays the ground for totalising value judgements and policy prescriptions of the sort that a robust liberalism rejects.

Returning to schools, in identifying schools as essentially a site of disease transmission, epidemiology made it possible to imagine that all experienced schools in this way and so held disease transmission as their chief concern. This tendency is exacerbated by the depiction of science and scientific analysis as ‘objective’ and shorn of the value judgements that it makes possible (Pennington 2023, p. 132). Scientific cosmologies risk obscuring the plurality in human experiences of any given event or thing, and that a person’s central concern need not be the one identified as essential. 

It is, for example, not clear that people wouldn’t have chosen to send their kids to school if they had been given the option to do so – even if they’d been informed of the risks posed by schools to ICU capacity. Schools are sites of disease transmission certainly, but they are also crucial to safeguarding, socialisation, kinship, education, and even a sense of normality that some might have felt to be crucial at a time of heightened uncertainty or panic (Bristow and Gilland 2020; Cole and Kingsley 2022). However, rather than note the limits of their capacity to understand the complexity of human experience and need and affording citizens the freedom to negotiate their own risks and priorities, the UK government, under the aegis of an epidemiological cosmology, shut schools completely – with far-reaching and unjust consequences (Cole and Kingsley 2022).

In the second instance, allowing science to enclose swathes of policy debate gives scientists (and other expertly people) a great deal of political and moral power over our lives. To reiterate, “enclosing” does not imply that a specific group of scientific individuals are put in charge of policy. SAGE is – and was – principally an advisory body. Rather, it means that working within a particular scientific cosmology is the price of entry to serious policy discussion.

However, in practice, this means that scientists and credentialed people de facto enjoy greater influence over the shape of policy than laymen, thus giving the former a hierarchical power over the latter that threatens the strictures of robustness. Laymen will never find it as easy as credentialed scientists to position themselves within a scientific cosmology and so will never be taken as seriously in enclosed policy debates. 

Importantly, this hierarchy spills over the bounds of formal policy-making and out in the more nebulous (but more important!) realm of public debate and social norms. In their discussions over pandemic policy, news reporters and daytime television shows mostly platformed members of the public health establishment – doctors, epidemiologists, biostatisticians, behavioural scientists etc. I don’t, for example, recall ever seeing a representative of the Haredi Jewish community being invited onto TV to debate the legitimacy of the Covid-19 measures, even though many were seemingly opposed to them (Magid 2020; Murphy-bates and Wallis Simons 2020). And, even if non-scientists and Rabbis had been widely invited to give their angle on the policies, it is unlikely that they would have been taken seriously, either by the journalists or the viewing public. Seemingly, the only perspectives that most of us considered morally relevant to policy discussions were the ones with public health credentials trailing their names. 

Faced with the techno-scientification of everything, those of us wedded to the ideals of liberalism urgently need to recognise this threat. We need to recognise that though it is often useful, science cannot transcend the human condition. However much opportunity it brings, it cannot save us from being the limited, complex creatures that we are. 

Bibliography

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Source: Brownstone Institute Read the original article here: https://brownstone.org/