Trajectory-Based Credibility under Symbol Inflation

As symbolic surfaces become compatible with increasingly heterogeneous production histories, the evidential basis of credibility can migrate from isolated outputs toward temporally extended histories. This paper develops trajectory-based credibility to analyze that migration. A trajectory situates a present surface within an event-structured history of action, revision, interaction, commitment, and consequence, preserving distinctions about development and agency that a terminal output may underdetermine. Trajectory evidence occupies an intermediate position between scalable symbolic inference and costly direct co-experience, making relational bandwidth a central constraint. The framework develops historical resistance, agency legibility, credibility depth, institutional translation, record burden, and trajectory inequality as target-relative dimensions of this evidential architecture. It further shows how strategic adaptation can convert trajectory systems into new symbolic infrastructures subject to renewed diagnostic pressure. Generative AI enters as one accelerator within the broader condition of symbol inflation. The paper concludes with an empirical program for measuring when trajectory evidence improves target-relevant discrimination and when its burdens, inequalities, or strategic distortions exceed that evidential gain.