This record archives the public, review-facing documentation for the Public Diplomacy Simulation Lab (PDSL), a deterministic, theory-constrained simulation framework developed to support structured scenario reasoning in digitally mediated public diplomacy and algorithmic governance contexts. PDSL provides a regime-based interpretive architecture for examining how structured analytical inputs—such as exposure intensity, identity salience, and threat framing—interact within controlled environments. The framework translates these inputs into three governed outcome channels: Algorithmic Persuasion Risk (APR), Identity Alignment Shift (IAS), and Policy Support via Threat Framing (PST). These outputs are conceptual constructs designed for disciplined comparative reasoning, training, and strategic policy analysis. They do not represent empirical measurements, predictive forecasts, causal inference models, or automated decision systems. The present release (v0.1.2-review-ready) contains the documentation layer of the framework, including the Model Card, Methods Note, Review Protocol, governance structure, and policy-facing interpretive guidance. The simulation engine, parameter thresholds, and proprietary operational logic are intentionally excluded to preserve research integrity and prevent operational misuse. Positioned at the intersection of public diplomacy, digital soft power, identity formation, and algorithmic influence studies, PDSL offers a structured environment for analyzing narrative saturation effects, regime transitions, and identity-alignment dynamics in computationally mediated information ecosystems. The framework is anchored in peer-reviewed theoretical foundations and documented in:Damas, F. (2025). TikTok's Algorithmic Influence and American Youth Support for U.S. Public Diplomacy. International Journal of Science and Research, 14(10), 716–725. https://doi.org/10.21275/SR251012173109 Release anchor: v0.1.2-review-readyRepository: https://github.com/damasconsultingservices-lang/pdsl-docs