Compensatory Network Capital: A Bourdieusian Conversion Model of Health Literacy

We develop Compensatory Network Capital (CNC) as a sociological framework for understanding how social networks translate potential social support into actual capability within healthcare. Building on Bourdieu's capital theory and Sen's capability approach, we specify social conversion as a meso-micro process that links institutional rules, social network resources, and concrete health actions. Rather than proposing a competing construct, CNC refines social capital, Distributed Health Literacy, and related models by identifying four tie-level mechanisms: Activation, Function-specific Help, Recognition, and Substitution (A-F-R-S) that condition whether support becomes action at the point of need. Drawing on qualitative interviews and two small pilot surveys, we employ abductive analysis to illustrate how these mechanisms can be operationalised through event-level indicators (e.g., booking, attendance, follow-up) and to distinguish between positive, partial, and failed conversions, including harmful or misdirecting network influence. We argue that CNC offers a theoretically grounded and measurable account of when and for whom networks compensate for limited individual health literacy, and how organisational recognition of informal helpers shapes these outcomes. The model contributes to relational public health by identifying key points of intersection where people, social ties, and institutions intersect.