HUMMBL-Unified-Tier-Framework

HUMMBL Unified Tier Framework

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


Welcome

The HUMMBL Unified Tier Framework provides a comprehensive system for:


Quick Navigation

📖 Main Documentation

View Complete Framework →

🎯 Core Framework

📚 Application Guides

📖 Reference


Visual Overview

Problem Complexity Tiers

Tier 1: Simple          ━━━━━━━━━━ (0-9 points)
Tier 2: Complicated     ━━━━━━━━━━━━━━ (10-14 points)
Tier 3: Complex         ━━━━━━━━━━━━━━━━━━ (15-19 points)
Tier 4: Wicked          ━━━━━━━━━━━━━━━━━━━━━━ (20-24 points)
Tier 5: Super-Wicked    ━━━━━━━━━━━━━━━━━━━━━━━━━━ (25-30 points)

Learning Progression

Tier 0: Awareness    →  Tier 1: Beginner    →  Tier 2: Intermediate
                                                        ↓
Tier 4: Master       ←  Tier 3: Advanced     ←  [Continue Learning]

Base-N Architecture

Base6   (6 models)   → Foundational
Base12  (12 models)  → Emerging Practitioner
Base24  (24 models)  → Professional Standard
Base36  (36 models)  → Advanced Practitioner
Base42  (42 models)  → Expert/Master Level
BASE120 (120 models) → Complete Framework

Getting Started

For Practitioners

  1. Assess your problem using the 5-question wickedness scoring
  2. Determine tier (0-30 points → Tier 1-5)
  3. Select Base-N level matching your learning tier
  4. Apply systematically using implementation protocols

For Learners

  1. Start with Base6 foundational models
  2. Progress through Base12 and Base24
  3. Follow the learning pathway
  4. Practice with real problems

For Researchers

  1. Review validation evidence
  2. Explore research applications
  3. Consider collaboration opportunities

Framework Components

🎯 Problem Complexity Tiers

Quantitative classification system based on:

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📚 Learning Progression Tiers

Five-stage development path:

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🔢 Base-N Architecture

Structured model selection framework:

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📊 Wickedness Scoring

Quantitative assessment methodology:

Learn More →


Validation & Evidence

BASE120 Mental Model Validation

View Complete Evidence →


Citation

BibTeX

@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}
}

APA

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

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Attribution

DeepSeek AI (October 2025)

Academic Foundations

HUMMBL (2024-2025)

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Resources

Documentation

Community


Version

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

Status: Production Release

Next Version: v2.0 (Target: Q2-Q3 2026)

View Roadmap →


Contact

HUMMBL, LLC
Chief Engineer: Reuben Bowlby


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