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The scientific-political milieu of Covid-19 encompasses numerous fraught debates. Among them, arguments about targeting restrictions at older people have animated many in our gerontological community. While hermetically sealing an age-group from society is unrealistic[1], ongoing debate regarding “chronological quarantine” offers an opportunity to reflect on the relations between ageism, evidence and discrimination. To this end, my recent paper[2] questions the place of ageism within the maelstrom of public health, policy and protest that has amassed around the idea of age-based restrictions.

The academic debate on this issue will be familiar to most readers. On the one hand, commentators have argued that the implementation of restrictions based on chronological age is ageist, particularly in disregarding heterogeneity among older people, and should therefore not be pursued. On the other hand, advocates have contended that such an approach represents a pragmatic public health response to risks that are heavily associated with older age. This echoes other age-based public health restrictions, e.g. banning alcohol sales to under-18s.

The debate creates a binary of value-laden ageism against evidence-based age-discrimination. I suggest that neither stance is wrong and that this binary is misleading.

Ageism is an enigmatic concept, often invoked with more passion than precision. Inspired by Bytheway, I treat ageism as the assumption of shared characteristics based on age, besides age itself and certain legal attributes, and the conduct of action based on those assumptions. Some categorical age claims are not ageist, e.g. “80 year olds are of pensionable age”; but many are ageist, e.g. “80 year olds have cognitive decline.” I can support the latter claim with robust analyses showing that 80 year olds do, on average, experience cognitive decline. I can hence make an evidence-based ageist claim. I could use this evidence-based ageism to inform tailored services. Nonetheless, I would remain ageist in making assumptions about people’s cognitive abilities by virtue of their birth dates, irrespective of their particular circumstances.

In part, this is an epistemological issue. Population-level analyses struggle to account for heterogeneous persons. The struggle is pronounced when it comes to older people because heterogeneity tends to increase over time, making older people especially diverse in many respects. As a result, an older individual’s actual cognitive ability can be far removed from his or her age-associated cognitive ability. Sometimes, abstract population observations can apply to almost no actual persons. While British women give birth to 1.9 children on average, few British women give birth to 1.9 children. Assumed age-associated Covid-19 risks manifest the same problem.

Does reliance on age-based abstraction undermine the external validity of age-associated Covid-19 risk? Not really. The risk exists, albeit in abstraction. In the context of public health, this abstraction can be helpful. Population-level observations can be at odds with each and every person’s circumstances (e.g. the woman with 1.9 children), but that does not preclude the usefulness of those observations as they relate to public policy (e.g. forecasting future school capacity). In chronological quarantine, the assumption is that a real 80 year old’s risk is shared with the abstract 80 year old’s risk because they share an age. That assumption is flawed, but it is also useful in particular circumstances.

The evidence/ageism binary is further blurred because age assumptions shape the creation of evidence. Research is always situated in specific belief systems, and age-related research inevitably relies on certain assumptions to investigate the world. In the case of institutional gerontology, much research relies on the assumption that age (however conceived) denotes meaningful types of person. Covid-19 risk was always going to be stratified by age because we “know” (intuitively, conventionally, professionally) to investigate age associations, within research infrastructures that centre on age as a meaningful variable. The meaningfulness of age colours innumerable aspects of our lives, including our empirical conventions.

The link between empiricism and ageism goes further still because our assumptions can fuel looping effects. We assume the meaningfulness of age in part because those before us have made it meaningful, and our assumption of meaning generates, sustains and perpetuates meaning. Every paper that begins with an appeal to the meaningfulness of ageing – e.g. “X% of people will be aged >X in 2050” or “older people face prejudice” – simultaneously acknowledges and contributes to the meaningfulness of age, ageing and agedness. Again, this ageism is not necessarily bad. A sensitivity to population structures and prejudices can, in the right circumstances, inspire and inform positive action.

While not completely undermining age-discriminated public health, entanglements of ageism and empiricism do require us to acknowledge our epistemic circumstances. We know that chronological age is a flawed variable. It crudely indicates numerous legal, political, economic, cultural, psychological and biological statuses. When we use age as an analytic tool, we know that we are typically imposing a metaphor and making assumptions about the people we study. This is especially evident with numerical age, but similarly applies to other categorisations – “older adults”, “third agers”, “baby boomers”, etc. This does not preclude the analytic usefulness of assuming meaning, but we should always remember that we create and sustain these categorisations.

Some critics suggest that chronological age is an especially problematic abstraction, and appeal to biological age as a potential solution. However, biological age is potentially more dangerous in some respects.[3] The risk is that exposures (often socially determined) and chance are depicted as individualised molecular attributes, inscribed into our bones, neurones and wombs. While chronological age is a relatively blunt social location, biological age is unequally distributed according to various (dis)advantages, zeroing-in on inequalities. Restrictive policies based on biological age would hence disproportionately penalise disadvantaged groups of older people.

Certain issues amplify questions of populations, individuals, ageism, empiricism and discrimination. Consider the mass state-enforced institutionalisation of younger people in the education system, sometimes against their will, manifesting culturally and historically dependent imaginings of childhood. Likewise, the age-discrimination of alcohol sales to teenagers represents an amalgam of age assumptions, evidence and restrictive policy. There are various ageisms at play here. Notions of youth irresponsibility are entwined with epidemiological evidence regarding early life development. Most people (perhaps not the teenagers themselves) happily go along with this. Such examples suggest that a purist anti-ageism approach would profoundly reimagine our societies, and gerontology, in ways that would both benefit and harm us all.

Ultimately, chronological quarantine provides a compelling provocation to reflect on the complex nature of ageism in every aspect of our lives. It is a simultaneously salutogenic and pathogenic social force. It begets an ageist evidence-base but does not necessarily preclude the value of that evidence. With this in mind, the question of whether a particular thing is ageist can sometimes be disconnected from, and less important than, the social justice implications of that thing.

[1] There are >12 million older people in the UK, with around 15 million cohabitants, and an additional >2 million high-risk disabled people – almost half the population before we consider other risk groups and their vital contacts. During isolation, boilers would break, teeth would need emergency dentistry, partners would become abusive, chip-pans would set alight, etc. The seal would break in innumerable ways. Beyond statistical and mundane impracticalities, the systemic feasibility is no better, as grimly exemplified by the inefficacy of the “iron ring” around care homes. The state has neither the infrastructure nor the competence to orchestrate anything like a chronological quarantine.

[2] Fletcher, J.R. (2020) Chronological quarantine and ageism: Covid-19 and gerontology’s relationship with age categorisation. Ageing & Society doi:10.1017/S0144686X20001324

[3] Fletcher, J.R. (2020) Anti-ageing technoscience & the biologisation of cumulative inequality: affinities in the biopolitics of successful ageing. Journal of Aging Studies, doi:10.1016/j.jaging.2020.100899