Definition of Six Relational Zones: White, Green, Yellow, Red, Black, Clear
Underlying Philosophical Assumptions (e.g., non-linear, emergent, tactical ethics)
IV. Formal Model
Relational Scoring Function:
Rij(t)=k=1nwkVk,ij(t)+CR_{ij}(t) = \sum_{k=1}^n w_k \cdot V_{k,ij}(t) + C
Mapping Scores to Zones
Variable Definitions, Weights, and Justifications
Adaptation Mechanisms and Temporal Adjustments
V. Simulation and Illustrative Scenarios
Case 1: Organizational Team Dynamics
Case 2: Conflict Recovery in Personal Relationships
Case 3: Leadership in Uncertain Environments
VI. Discussion
The Strategic Use of Zones
Dynamic Reclassification and Behavioral Adaptation
Ethical Considerations: When is manipulation strategic vs. toxic?
Implications for AI-Human Interaction Models
VII. Validation Pathways
Empirical Validation Methods (e.g., longitudinal diary studies, network dynamics)
Computational Agent-Based Simulations
Real-life Application Testing (e.g., in HR, coaching, trauma-informed work)
VIII. Conclusion
Summary of Contributions
Limitations and Scope for Refinement
Integration with AI-based relational intelligence
Appendix
Variable Tables
Sample Calculations
Algorithmic Pseudocode (for practical applications)
I. Introduction
A. Problem Statement: Strategic Ambiguity in Human Relations
In the complex terrain of human social interaction, relationships rarely exist in binary oppositions of friend or foe, ally or enemy. Instead, individuals continuously navigate a landscape marked by strategic ambiguity, where trust is provisional, betrayal is probabilistic, and loyalty is contingent upon context and utility. Social actors operate not merely as rational calculators of benefit and cost, but as adaptive agents negotiating shifting emotional, cultural, and informational ecologies. The lack of a formalized, scalable, and context-sensitive model to interpret these gradations in social dynamics constitutes a profound theoretical and practical problem.
