This workshop is part of the series “Statistics for the Public Good – Infrastructure Decision Making, Research and Discourse”, which introduces participants to public statistics as a process in which the design, production and communication of information (statistics) are an integral part. As with other products (architecture, furniture, food, cars, smartphones, etc.), the aim is to optimize the design (form) in relation to the use (function) of the products (“form follows function”).
There has been a marked surge in the way in which data and evidence are being used in new ways to inform policy in the United States. Although many blue ribbon committees are established whose recommendations are ignored, the U.S. Commission on Evidence-based Policymaking (Evidence Commission) has been one notable exception.Established in 2016, 11 of the 22 recommendations were enacted into law in 2018, including establishing or reinforcing leadership positions, planning processes, data sharing authorities, and privacy protections necessary to modernize the national evidence-building infrastructure. An advisory committee established in the law currently is mulling how to implement the rest, given the twin goals of increasing the value of data for evidence building through access while also ensuring the continued trust of data providers – trust that the access to data will generate evidence that improves policies, and trust that privacy will be respected and confidentiality will be protected.[1] Yet, the interest and need is so great, exciting activities are already underway.
Historically, states in the U.S. have been remarkably effective in their use of data. As far back as 1932, U.S. Supreme Court Justice Louis Brandeis argued that states could be “laboratories” of experimentation; that is, states could test the effects of different policies, determine what worked and what didn’t, and lead the way to national programs [2]. States have proven Justice Brandeis right time and again – from Massachusetts’s experiment with health care reform to California’s pollution controls. Now states are innovating and experimenting with ideas about how to best use data to produce evidence and inform policy. A recent conference “Multi-State Data Collaboratives: from Projects to Products to Practice” provided a glimpse into a future of new types of collaborations, new types of measurement and new ways of protecting privacy. The impact of many state programs – training, human services, criminal justice, and education – is often measured by the labor market outcomes of the individuals they serve, yet each state’s data ends at state lines. That situation has posed problems for states that know their residents often cross state lines to go to school, work, and unfortunately, become incarcerated, particularly when population centers are near to state borders.
However, a secure data sharing platform, established with federal dollars as a possible blueprint to inform the Evidence Commission at the start of its deliberations, has proven to be wildly successful in providing the opportunity for states to share highly sensitive data across state lines. With additional philanthropic and state funding, the data sharing platform provided the core infrastructure needed to enable the establishment of a MidWest state collaborative in 2018 [3] and a series of cross-state data collaborations. It is a blueprint, based on a five safes framework, that can serve as a roadmap to additional collaborative activities to propel evidence-building forward at an accelerated pace – and how they can lead to new, critically-needed measurements resulting from the massive changes in the economy and society.
This workshop will provide a discussion of the five safes framework in helping conceptualize and implement the joint determination of risk and utility. It will describe the Coleridge Initiative’s use of the US FedRAMP framework, as well as the FedRAMP approach in more detail, in terms of minimizing risk. It will then work through the role of training classes in creating value.
The workshop will feature hands-on examples of how the training class worked with active discussions of what might or might not be applied to the German context.
