Methodology
How we conduct research at TEG-Blue. Our commitment to open science, rigorous validation, and ethical standards.
Open Science Principles▶
All TEG-Blue research follows open science principles:
• Pre-registration of studies before data collection
• Open data sharing (anonymized) via Zenodo
• Open access publication of all findings
• Transparent reporting of methodology and results
• Reproducible analysis pipelines documented in public repositories
We believe that emotional regulation research should be accessible to everyone—researchers, practitioners, and individuals seeking self-understanding.
Validation Framework▶
Our validation approach uses multiple methods:
1. **Inter-rater Reliability**: Independent raters assess the same samples to ensure consistent identification of regulatory states.
2. **Convergent Validity**: New measures are compared against established instruments (e.g., DERS, AAQ-II) to verify they capture related constructs.
3. **Discriminant Validity**: We test that our measures differentiate between distinct regulatory states, not just general distress.
4. **Ecological Validity**: Studies use naturalistic language samples and real-world contexts, not just laboratory settings.
Ethical Standards▶
All research involving human participants follows ethical guidelines:
• Informed consent obtained before participation
• Right to withdraw at any time without consequence
• Data anonymization before analysis and sharing
• No deception in study design
• Debriefing provided after participation
• Mental health resources offered to all participants
We take particular care with vulnerable populations and ensure appropriate support structures are in place.
AI-Readable Research▶
All publications are designed for both human and AI consumption:
• Structured JSON-LD metadata on every page
• Semantic HTML with proper heading hierarchy
• Dublin Core and Schema.org annotations
• Native HTML expandable sections (not JavaScript accordions)
• Clear, consistent terminology throughout
This ensures that AI systems can accurately understand and cite our research, while maintaining human readability.