Research Contributor — Nervous System Regulation, Emotional Intelligence & Computational Validation

TEG-Blue is seeking research contributors to help validate and extend a published framework for measuring nervous system regulatory patterns in natural language.

What is TEG-Blue

TEG-Blue is an emotional intelligence framework that maps nervous system regulatory states and their effects on behavior, relationships, and systems. Developed by Anna Paretas-Artacho through nearly two years of independent research, it draws on 139+ established research traditions and models across polyvagal theory, attachment research, affective neuroscience, trauma studies, emotion regulation science, and systems thinking.

The framework has two layers:

• The Four-Mode Gradient — a measurement system that classifies regulatory states as Connection, Protection, Control, and Domination. These are observable states anyone can occupy, not personality types.
• 12 Explanatory Frameworks — the theoretical architecture explaining why these modes exist, how patterns scale from individual to systemic, and what enables change.

A central testable claim: the key variable predicting relational outcomes is not a person’s current state, but their capacity to return to Connection when challenged. This is measurable through complexity markers in natural language, including self-awareness, perspective-taking, and emotional differentiation.

Published research

1. An empirical validation study analyzed 10,000+ natural conflict narratives using computational methods. Key finding: de-escalators showed 78% higher rates of complexity markers than escalators. Mode classifications also correlated with independent community moral judgments. The full study is published with DOI 5281/zenodo.18428907 and available at teg-blue.org/publications.

What we need

Contributors who can work on specific, bounded research tasks within the existing framework. Four research lanes are open:

• Lane A — Measurement and recognition: inter-rater reliability studies, annotation schema development, construct validation for the Four-Mode Gradient in natural language
• Lane B — Prediction and prevention: escalation pathway coding, longitudinal design, behavioral prediction models for movement between regulatory modes
• Lane C — Navigation and intervention: scale design, factor structure analysis, convergent and discriminant validity testing for intervention approaches that support movement from Control back toward Connection
• Lane D — AI alignment and structured schemas: translating emotional pattern logic into machine-readable formats, schema design, evaluation protocols, misuse prevention

Pick the lane that matches your expertise. You do not need to validate the entire system.

How this works

TEG-Blue’s core concepts and architecture are authored by Anna Paretas-Artacho. Collaboration happens through defined research contributions, with clear authorship and attribution terms agreed from the start.

What contributors receive

• Public credit and acknowledgment for their work
• Authorship opportunities on lane-specific papers, discussed upfront
• Access to relevant datasets needed for the agreed research task (anonymized)
• A chance to build publishable work inside an already validated framework
• Potential transition into a paid research role once funding is in place

Who should apply

• Researchers, academics, or PhD students in psychology, neuroscience, sociology, education, cognitive science, or computational linguistics
• Practitioners or clinicians with applied research experience in emotion regulation, trauma-informed care, or attachment
• Data scientists or NLP researchers interested in computational approaches to emotional pattern detection

Before applying, read the research entry page at teg-blue.org/start-here and the collaborate page at teg-blue.org/collaborate.