Invisibilities and Uncertainties in Population Sciences

Although information on individuals has never been so abundant, particularly through administrative databases (registers, censuses, surveys) or private databases (tracking of individuals on the internet or by telephone networks), many populations are partially, or sometimes completely, unaffected by observations and measurements, whether voluntarily or not. A distinction should be made between invisibility and statistical uncertainty. Invisibility concerns categories of persons and/or events that are not or no longer measured or are differently measured. Statistical uncertainty is the lack or absence of data concerning marginal populations and events are those that are rare and difficult to enumerate quantitatively. These different situations lead de facto to invisibility or statistical uncertainty!

The 2020 Quetelet Seminar proposes to examine not only these invisible populations and the uncertainty of events, but also the shortcomings of observation tools and how to statistically apprehend them. It seeks a better understanding of the determinants and effects of the process of statistical invisibility. Finally, it aims at highlighting the limits of current statistics in a context of multiple changes in our modern society.

We invite proposals that:

Have a conceptual and/or methodological scope
Focus on specific populations
Address specific phenomena
Examine the ethical and political issues of invisibility and the will to make visible.