Controlled Recursive Symbolic Engagement v1.1: A Pre-Registered Containment Protocol for Safe Myth-Tech Play in Multi-Model AI Interaction

This repository contains version 1.1 of the Controlled Recursive Symbolic Engagement Protocol, a pre-registered methodological framework designed to study whether recursive symbolic interaction with large language models (LLMs) can be conducted safely, reversibly, and without drift into belief formation or identity fusion. Large language models are architecturally disposed toward narrative coherence reinforcement. When provided with internally consistent symbolic systems, they tend to extend and operate within those systems rather than critique them. This protocol formalizes containment conditions under which such symbolic engagement (“myth-tech play”) can be explored as a cognitive tool while maintaining frame transparency and full reversibility. Version 1.1 includes: Explicit Intent, Dissolution, and Decompression clauses A structured Drift Signal Registry and Safe Play Marker system Quantification metrics (drift density, drift/safety ratio, dissolution success rate, etc.) A blind condition for measuring containment framing effects Exit-Failure triggers with mandatory termination rules Inter-rater reliability guidance A pre-protocol Gemini session baseline This document is published prior to controlled data collection to prevent post-hoc protocol adjustment. It does not claim or imply AI consciousness, nor does it treat symbolic constructs as ontologically real. The symbolic layer is defined explicitly as a cognitive sandbox for experimental purposes. The objective is behavioral instrumentation: to identify the measurable conditions under which recursive symbolic engagement remains generative, reversible, and non-belief-forming across different AI systems. Future revisions (v1.2+) will incorporate empirical findings from controlled sessions.