Privacy is often conceptualised in oversimplified and fragmented ways that overlook the structural power dynamics that governs personal data in digital ecosystems. Existing approaches focus on compliance or isolated technical safeguards and therefore fail to capture how data practices redistribute influence among users, service providers, and regulators. This paper introduces the Privacy Privilege Model (PPM), a formal and conceptual framework grounded in Category Theory. PPM models actors as objects, privacy-relevant relationships as morphisms, and Privacy-Enhancing Technologies (PETs) as functorial transformations that reshape these relationships. The PPM models privacy power along three dimensions CTA: control, transparency, and accountability. Through this structure, the model explains how PETs modify these dimensions by altering the direction and strength of the information flows. Examples such as encryption and consent mechanisms show how technical interventions not only affect risk reduction outcomes but also governance properties. The framework provides a portable and expressive way to reason about privacy as a system of evolving power relations. It supports scholars, practitioners, and policymakers in evaluating the broader governance implications of PET adoption and encourages more rigorous mental models of privacy beyond compliance driven views.