Start Here
A prototype emotional data system — measurable, testable, usable
TEG-Blue is a prototype emotional data system designed to make emotional safety and accountability measurable, testable, and usable across humans and AI. It treats emotions as valid, structured data.
What TEG-Blue is
TEG-Blue is a visual mapping system designed to make emotional patterns measurable, testable, and usable across individuals, relationships, institutions, and AI systems.
It builds on existing research across nervous system regulation, attachment, development, trauma, social psychology, and language.
The originality is not in claiming a new theory for each domain. It is in building an integrated structure that makes the connections explicit, operational, and testable.
What is original: the "1 + 2 = 3" principle
TEG-Blue doesn't invent the building blocks. Polyvagal Theory, Attachment Theory, Affective Neuroscience, Trauma Research — these are established. They are the "1" and the "2".
What TEG-Blue proposes is the "3" — specific connections between these established theories:
- Nervous system regulation → moral perception
- Attachment patterns → social stratification
- Protection → domination as a continuous gradient
- Linguistic complexity → regulatory capacity
The individual theories are validated. The connections are the hypothesis. The scientific community can help determine if "3" holds up.
Status snapshot
This project separates what exists from what is being tested.
Many underlying theories and measures in affective science, clinical psychology, neuroscience, trauma, social psychology, and linguistics.
The full cross-framework mapping. The 'return-to-connection' arc across Frameworks 8–10. The architecture that connects regulation, identity adaptation, and social escalation.
Initial studies and analyses listed in Publications.
Psychometric validation and replication. Construct validity across cultures, contexts, and modalities. External benchmarking against existing instruments.
The core testable claim
Return capacity predicts relational outcomes
The key variable that predicts relational and behavioral outcomes is not a person's current regulatory state, but their capacity to return to Connection when challenged.
This is treated as a testable hypothesis, not a slogan.
Hypothesis: Return capacity predicts relational outcomes.
Operationalization: Measurable in language via complexity markers — accountability without collapse, perspective-taking, repair attempts, emotional differentiation, reduced coercion under stress.
Research need: Replication and cross-context validation. Which markers are reliable? Which are context-dependent? How do they shift across stress load, power dynamics, and attachment history?
Related frameworks: F8 (Repairing Awareness), F9 (Neurodivergence as Nervous System Variation), F10 (Rebuilding Generational Bridges).
Open research directions
The framework opens several lines of inquiry. Each can be pursued independently.
A. Measurement and recognition
Can the Four-Mode Gradient be reliably detected in natural language, transcripts, therapy session excerpts, conflict dialogues, and organizational communication?
Open questions: Inter-rater reliability designs, annotation schemas, construct validation, cross-domain generalization tests.
Inner Compass (M1) →B. Prediction and prevention
How do states shift and escalate across the gradient? Harm often follows predictable progressions from Protection into Control and Domination.
Open questions: Escalation pathway coding, longitudinal tracking designs, behavioral outcome prediction under stress and power asymmetry.
Frameworks → (especially F4–F7)C. Navigation and intervention
Which interventions support systems moving from Control back toward Protection and Connection? Routes back to safety exist — the question is which ones work, and when.
Open questions: Scale design support, factor structure exploration, convergent and discriminant validity plans, bias and fairness evaluation.
Methodology →D. AI alignment and structured schemas
Translating emotional pattern logic into forms AI systems can read safely.
Open questions: Schema design feedback, evaluation protocols, risk analysis, misuse prevention, alignment with existing safety research.
AI Safety →Where to go from here
Contact
If any of these directions match your work, reach out with a short note — your background, which direction interests you, and what you'd want to test or critique first.
research@teg-blue.orgAnna Paretas-Artacho — Independent researcher and systems designer, Barcelona. 25+ years in systems thinking. TEG-Blue developed over two years as an integrative architecture across 139+ established theories. Full background →