These six short stories point to the increased importance of the quantitative during the pandemic. While much of the pre-pandemic world was dominated by digital data, often describing individual behaviours online, the pandemic and post-pandemic world has forced numbers about society onto the mainstage. Before the pandemic, people would be familiar with GDP or unemployment rates. But the scale, scope and familiarity with this type of data marks a distinct juncture.

This makes understanding the cause, nature and effect of the quantitative a pressing task in the ‘post-pandemic’ world. To do so, this book argues that we need to engage with data bounds: how data becomes a meaningful way to experience, think about, discuss, react to, engage with and change certain phenomena. These data bounds are complex, made up of an ensemble of technical processes (collecting data, cleaning it, analysing it), contexts (political, economic, cultural, and so on) and media and communication.

But this complexity should not inhibit understanding. Each chapter in this book offers a distinct perspective of data bounds: they are reinforced by policy (Chapter 2), quantitative realism underpins them (Chapter 3), quantitative realism is mathematical and abstract (Chapter 4), desire for them underpins quantitative realism (Chapter 5), they are emotive (Chapter 6) and their boundaries are drawn within historical norms (Chapter 7).

These perspectives allow for data bounds to be broken down into six characteristics. In doing so, it can be used to think through non-pandemic phenomena that are highly quantified. These include – but are not limited to – health and fitness, inflation and cost of living, crime and justice and finance. It is hard to discuss, engage, experience or think about these contexts and for data not to be meaningful. To speak of the cost of living is to speak of wages, prices and profits. It is not to say that the qualitative plays no role, but to argue that the quantitative dominates.

Just as there are highly quantified phenomena, there are also contexts that have not felt the data creep so acutely. We can think of poetry and literature as existing outside data bounds.