Skip to content

hummbl-dev/HUMMBL-Unified-Tier-Framework

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

32 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

HUMMBL Unified Tier Framework v1.0

Version License Status Documentation Markdown Lint Spell Check Link Checker CI

Integrating Problem Complexity, Learning Progression, and Base-N Architecture

A comprehensive framework for classifying problem complexity, mapping learning progression, and selecting appropriate mental model combinations for systematic problem-solving.


🎯 Overview

The HUMMBL Unified Tier Framework provides:

  • Dual-Tier System: Problem Complexity Tiers (1-5) and Learning Progression Tiers (0-4)
  • Quantitative Wickedness Scoring: 5-question assessment methodology (0-30 points)
  • Base-N Selection Framework: Structured approach to mental model subset selection
  • Empirical Foundation: Built on BASE120 validation (120 models at 9.1/10 quality)

Key Features

Problem Classification: Quantitative tier assessment from simple to super-wicked problems
Learning Pathways: Structured progression from awareness to mastery
Model Selection: Guidance for choosing appropriate mental model combinations
Validation Evidence: Transparent confidence levels and empirical grounding
Practical Application: Implementation protocols and decision trees


📚 Documentation

Main Document: HUMMBL_Unified_Tier_Framework_v1.0.md

Quick Navigation


🚀 Quick Start

For Practitioners

  1. Assess your problem using the 5-question wickedness scoring methodology
  2. Determine tier classification (0-30 points → Tier 1-5)
  3. Select Base-N level matching your learning tier and problem complexity
  4. Choose specific models from the validated BASE120 collection
  5. Apply systematically using implementation protocols

For Learners

  1. Start with Base6 foundational models (Tier 1: Tool User)
  2. Progress through Base12 and Base24 as you gain experience
  3. Follow the learning pathway recommendations
  4. Practice with real problems and reflect on outcomes

For Researchers

  1. Review validation evidence and confidence levels
  2. Explore research applications
  3. Consider collaboration on planned empirical studies (Q1-Q2 2026)

📊 Framework Components

Problem Complexity Tiers

Tier Classification Score Range Characteristics
Tier 1 Simple 0-9 points Clear solutions, predictable outcomes
Tier 2 Complicated 10-14 points Expert-solvable, many interdependent parts
Tier 3 Complex 15-19 points Emergent behavior, adaptive approaches needed
Tier 4 Wicked 20-24 points Stakeholder disagreement, no clear solutions
Tier 5 Super-Wicked 25-30 points Time running out, no central authority

Learning Progression Tiers

Tier Level Focus Base-N Alignment
Tier 0 Pre-Learning (Awareness) Recognition of value Pre-Base6
Tier 1 Tool User (Beginner) Single-model application Base6
Tier 2 Integrator (Intermediate) Multi-model synthesis Base12-Base24
Tier 3 Architect (Advanced) Framework design Base24-Base36
Tier 4 Creator (Master) Model innovation Base36-BASE120

Base-N Architecture

Base-N Model Count Target User Problem Tier Alignment
Base6 6 models Beginner Tier 1-2 (Simple/Complicated)
Base12 12 models Intermediate Tier 2-3 (Complicated/Complex)
Base24 24 models Professional Tier 3-4 (Complex/Wicked)
Base36 36 models Advanced Tier 4-5 (Wicked/Super-Wicked)
Base42 42 models Expert Tier 5 (Super-Wicked)
BASE120 120 models Master/Researcher All tiers (complete coverage)

🔬 Validation & Evidence

BASE120 Mental Model Validation (October 31, 2025)

Confidence Levels

  • HIGH: BASE120 mental models, model definitions, automated quality metrics
  • ⚠️ MEDIUM: Base-N framework design, tier definitions, wickedness scoring
  • ⚠️ LOW: Tier-to-Base mapping (planned empirical validation Q1-Q2 2026)

See Validation Evidence for complete details.


📖 Citation

If you use this framework in your work, please cite:

@techreport{bowlby2025hummbl,
  title={HUMMBL Unified Tier Framework v1.0: Integrating Problem Complexity, Learning Progression, and Base-N Architecture},
  author={Bowlby, Reuben},
  year={2025},
  institution={HUMMBL, LLC},
  url={https://github.com/hummbl-systems/hummbl-unified-tier-framework}
}

APA Format: Bowlby, R. (2025). HUMMBL Unified Tier Framework v1.0: Integrating Problem Complexity, Learning Progression, and Base-N Architecture. HUMMBL, LLC.


🙏 Attribution

DeepSeek AI Contributions (October 2025)

  • Problem Tier descriptive language (Tier 1-4)
  • Learning Progression labels and characterizations
  • Alternative categorization schemes
  • Pedagogical framework insights

Academic Foundations

  • Super-Wicked Problems Concept: Levin, K., Cashore, B., Bernstein, S., & Auld, G. (2012). Overcoming the tragedy of super wicked problems: constraining our future selves to ameliorate global climate change. Policy Sciences, 45(2), 123-152.
  • Wicked Problems Concept: Rittel, H. W. J., & Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4(2), 155-169.

HUMMBL Proprietary Components

  • Tier 5 (Super-Wicked) operationalization and quantitative criteria
  • 5-question wickedness scoring methodology
  • Base-N architecture and mathematical foundations
  • BASE120 validation framework and empirical evidence
  • Priority model system and learning progression algorithms
  • Implementation protocols and assessment tools

📋 License

Copyright © 2025 HUMMBL, LLC. All Rights Reserved.

This framework is proprietary intellectual property. See LICENSE.md for complete terms.

Key Restrictions:

  • ✅ Educational and research use permitted with attribution
  • ✅ Personal problem-solving applications allowed
  • ❌ Commercial use requires explicit licensing
  • ❌ Redistribution without attribution prohibited
  • ❌ Claiming proprietary components as original work prohibited

For Commercial Licensing:
Contact: Reuben Bowlby, Chief Engineer
Email: Contact via GitLab


🗺️ Roadmap

v1.0 (Current - November 2025)

✅ Complete unified framework with all 8 sections + appendices
✅ BASE120 validation evidence integrated
✅ Quantitative wickedness scoring methodology
✅ Base-N selection framework (architectural design)
✅ Complete attribution and IP protection

v2.0 (Target: Q2-Q3 2026)

  • Base-N empirical testing study (Q1-Q2 2026)
  • Tier-specific coverage validation (larger sample sizes)
  • Additional worked examples and case studies
  • Interactive assessment tools
  • API specifications for integration
  • Peer review submission preparation

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Contribution Types:

  • 📝 Documentation improvements
  • 🐛 Issue reporting (errors, inconsistencies)
  • 💡 Use case examples and case studies
  • 🔬 Empirical validation data
  • 🌐 Translations

📞 Contact

HUMMBL, LLC
Chief Engineer: Reuben Bowlby


📜 Version History

See CHANGELOG.md for complete version history.

Current Version: v1.0.0 (November 1, 2025)


Built with rigor. Validated with evidence. Designed for impact. 🎖️

About

Problem complexity classification and learning progression framework with quantitative wickedness assessment methodology. Features 5 problem tiers (Simple→Super-Wicked), Base-N architecture (Base6→BASE120), and empirical validation from HUMMBL mental models research. Includes automated quality control and community templates.

Topics

Resources

License

Unknown, Unknown licenses found

Licenses found

Unknown
LICENSE
Unknown
LICENSE.md

Code of conduct

Contributing

Security policy

Stars

Watchers

Forks

Packages

 
 
 

Contributors

Languages