Statistical Imaginaries, State Legitimacy: Grappling with the Arrangements Underpinning Quantification in the U.S. Census

TL;DR

This paper examines how different statistical methods used in the U.S. census influence public trust and legitimacy by analyzing controversies rooted in competing visions of data and the role of statistical imaginaries.

Contribution

It introduces the concept of statistical imaginaries to explain controversies over census methods and compares reactions to methods aimed at improving accuracy and confidentiality.

Findings

Contested imaginaries affect trust in census data.

Different methods evoke divergent stakeholder responses.

The credibility of the Census Bureau depends on stabilizing statistical imaginaries.

Abstract

Over the last century, the adoption of novel scientific methods for conducting the U.S. census has been met with wide-ranging receptions. Some methods were quietly embraced, while others sparked decades-long controversies. What accounts for these differences? We argue that controversies emerge from $\textit{arrangements of statistical imaginaries}$, putting into tension divergent visions of the census. To analyze these dynamics, we compare reactions to two methods designed to improve data accuracy (imputation and adjustment) and two methods designed to protect confidentiality (swapping and differential privacy), offering insight into how each method reconfigures stakeholder orientations and rhetorical claims. These cases allow us to reflect on how technocratic efforts to improve accuracy and confidentiality can strengthen -- or erode -- trust in data. Our analysis shows how the credibility of the Census Bureau and its data stem not just from empirical evaluations of quantification, but also from how statistical imaginaries are contested and stabilized.