9 Contextual Integrity as a Gauge for Governing Knowledge Commons Yan Shvartzshnaider, 1 Madelyn Rose Sanfilippo, 2 and Noah Apthorpe 3 9.1 introduction This chapter describes our approach to combine the Contextual Integrity (CI) and Governing Knowledge Commons (GKC) frameworks in order to gauge privacy expectations as governance. This GKC-CI approach helps us understand how and why different individuals and communities perceive and respond to information flows in very different ways. Using GKC-CI to understand consumers’ (sometimes incongruent) privacy expectations also provides deeper insights into the driving factors behind privacy norm evolution. The CI framework (Nissenbaum, 2009) structures reasoning about the privacy implications of information flows. The appropriateness of information flows is defined in context, with respect to established norms in terms of their values and functions. Recent research has operationalized CI to capture users’ expectations in varied contexts (Apthorpe et al., 2018; Shvartzshnaider et al., 2016), as well to analyze regulation (Selbst, 2013), establish research ethics guidelines (Zimmer, 2018), and conceptualize privacy within commons governance arrangements (Sanfilippo, Frischmann, and Strandburg, 2018). The GKC framework examines patterns of interactions around knowledge resources within particular settings, labeled as action arenas, by identifying back- ground contexts; resources, actors, and objectives as attributes; aspects of govern- ance; and patterns and outcomes (Frischmann, Madison, and Strandburg, 2014). Governance is further analyzed by identifying strategies, norms, and rules-in-use through an institutional grammar (Crawford and Ostrom, 1995). According to GKC, 1 Assistant Professor/Faculty Fellow in the Courant Institute of Mathematical Sciences, NYU; Visiting Associate Research Scholar at the Center for Information Technology Policy (CITP), Princeton University. 2 Assistant Professor, School of Information Sciences, University of Illinois at Urbana-Champaign; Affiliate Scholar, The Vincent and Elinor Ostrom Workshop in Political Theory and Policy Analysis, Indiana University, Bloomington. Ph.D., Indiana University, Bloomington; M.I.S., Indiana University, Bloomington; B.S., University of Wisconsin-Madison. 3 Assistant Professor, Department of Computer Science, Colgate University; Ph.D., Department of Computer Science, Princeton University; Graduate Student Fellow, Center for Information Technology Policy, Princeton University. 220 https://doi.org/10.1017/9781108749978.010 Published online by Cambridge University Press