Comparative Observational Report on Turn-Taking, Cognitive Stability, and Response Regulation in Large Language Models
Authors/Creators
Description
This record documents a comparative observational study of multiple large language models (including GPT, Perplexity, GenSpark, Grok, and Gemini) under controlled interaction conditions.
The report focuses on turn-taking behavior, response interruption, cognitive continuity, and stability during extended human interaction, both with and without structured cognitive frameworks.
The objective is not to evaluate model performance metrics, but to document qualitative behavioral differences relevant to human safety, mental health contexts, and ethical AI deployment.
This record is complementary to the institutional positioning of the TCF/TBF framework and does not disclose proprietary or methodological implementation details.
Abstract (English)
This qualitative observational study documents behavioral changes in multiple AI systems when interacting with structured textual logic derived from TCF / TFB (Teoria da Crença Fundamental / Theory of Fundamental Belief) and procedural content. Without algorithmic integration or model tuning, the study analyzes how layered textual structures influence responsibility, containment, and stability of AI responses. Results indicate that logic-first structuring alone can regulate interpretative expansion and reinforce safety signaling, suggesting broader implications for AI behavioral governance.
Notes (English)
Files
Observational ManuscriptV2.pdf
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(100.6 kB)
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Additional details
Dates
- Issued
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2026-01-18Version 2 of a qualitative observational report documenting AI behavioral responses to structured textual logic based on TCF / TFB (Teoria da Crença Fundamental / Theory of Fundamental Belief). This update includes additional observations on interaction modality (written vs. audio), progressive containment effects across layered content configurations (TCF/TFB alone, combined with The 11 Steps, and additional structured texts), and scope clarification regarding logic-based behavior without algorithmic enforcement. All referenced frameworks and observational materials are formally registered under copyright.