Topics: data collaboratives

Paper by Alexander Kroll: “Traditionally, performance metrics and data have been used to hold organizations accountable. But public service provision is not merely hierarchical anymore. Increasingly, we see partnerships among government agencies, private or nonprofit organizations, and civil society groups. Such collaborations may also use goals, measures, and data to manage group efforts, however, the application of performance practices here will likely follow a different logic. This Element introduces the concepts of “shared measures” and “collective data use” to add collaborative, relational elements to existing performance management theory. It draws on a case study of collaboratives in North Carolina that were established to develop community responses to the opioid epidemic. To explain the use of shared performance measures and data within these collaboratives, this Element studies the role of factors such as group composition, participatory structures, social relationships, distributed leadership, group culture, and value congruence…(More)”.

Article by Bridget A. Fahey: “Private markets for individual data have received significant and sustained attention in recent years. But data markets are not for the private sector alone. In the public sector, the federal government, states, and cities gather data no less intimate and on a scale no less profound. And our governments have realized what corporations have: It is often easier to obtain data about their constituents from one another than to collect it directly. As in the private sector, these exchanges have multiplied the data available to every level of government for a wide range of purposes, complicated data governance, and created a new source of power, leverage, and currency between governments.

This Article provides an account of this vast and rapidly expanding intergovernmental marketplace in individual data. In areas ranging from policing and national security to immigration and public benefits to election management and public health, our governments exchange data both by engaging in individual transactions and by establishing “data pools” to aggregate the information they each have and diffuse access across governments. Understanding the breadth of this distinctly modern practice of data federalism has descriptive, doctrinal, and normative implications.

In contrast to conventional cooperative federalism programs, Congress has largely declined to structure and regulate intergovernmental data exchange. And in Congress’s absence, our governments have developed unorthodox cross-governmental administrative institutions to manage data flows and oversee data pools, and these sprawling, unwieldy institutions are as important as the usual cooperative initiatives to which federalism scholarship typically attends.

Data exchanges can also go wrong, and courts are not prepared to navigate the ways that data is both at risk of being commandeered and ripe for use as coercive leverage. I argue that these constitutional doctrines can and should be adapted to police the exchange of data. I finally place data federalism in normative frame and argue that data is a form of governmental power so unlike the paradigmatic ones our federalism is believed to distribute that it has the potential to unsettle federalism in both function and theory…(More)”.