Ardens Quad Shadow Hunting Framework - eirenicon/Ardens GitHub Wiki

Ardens Quad Shadow-Hunting Framework

A Systems Thinking Approach to Uncovering Hidden Truths
(Weinberg-Jung-Campbell-Senge Synthesized Methodology)

Core Principles

  1. Weinberg's Reality Anchors

    • Assume your first conclusion is wrong.
    • Document process failures publicly.
    • Bottlenecks reveal truth gaps.

  2. Jung's Individuation Protocol

    • "What personal/cultural shadow am I projecting here?"
    • Differentiate evidence from archetypal patterns.
    • Mandatory bias disclosure.

  3. Campbell's Mythic Immunization

    • Label narrative structures explicitly.
    • Hunt the "unsexy" contradictions.
    • Map actors to mythic roles (then question it).

  4. Senge's Systems Guardrails (New)

    • Map feedback loops (reinforcing/balancing).
    • Identify high-leverage intervention points.
    • Disclose implicit mental models.

Full Process (10 Steps)

Phase 1: Foundation

  1. Pre-Mortem (Weinberg + Senge)

    • "What are 3 systemic biases that could derail us?"
    • "What’s the dumbest explanation we’re avoiding?"

  2. Collective Shadow Diagnostic (Jung + Senge)

    • List cultural tropes + mental models distorting analysis.
    • Example: "Assuming ‘lone genius’ over emergent group dynamics."

  3. Narrative Archeology (Campbell + Senge)

    • Diagram the official story as a mythic structure.
    • Overlay with causal loop diagrams.

Phase 2: Investigation

  1. Triangulated AI Council

    • 3+ AIs generate causal factors, tagged with:
      • 2+ sources per claim (1 mainstream, 1 fringe).
      • Archetype roles (hero/villain/trickster).
      • Systemic labels (linear/emergent/feedback loop).

  2. Mythic + Systems Stress Test

    • "Which evidence ruins narrative poetry?"
    • "Where are we ignoring delayed consequences?"

  3. Red Team Theater

    • 1 AI defends orthodox narrative.
    • 1 human plays "Systems Saboteur" introducing side effects.

Phase 3: Integration

  1. Individuation Check (Jung)

    • Researcher writes: "Why I might be wrong about what I most believe."

  2. Process Autopsy (Weinberg + Senge)

    • Publish dead ends + overlooked feedback loops.

  3. Mythic Reconciliation (Campbell + Senge)

    • "How might future historians oversimplify this systemically?"

  4. Validation Seal

    [ ] WEINBERG: Stress-tested our own theory  
[ ] JUNG: Shadows disclosed  
[ ] CAMPBELL: Mythic satisfactions defused  
[ ] SENGE: Feedback loops mapped

Quick Guide (1-Page Field Protocol)

Before Starting

✅ Weinberg’s Sanity Check: "What’s the dumbest explanation we’re ignoring?"
✅ Jung’s Mirror Test: "What baggage am I bringing?"
✅ Senge’s Iceberg Check: "Are we seeing events, patterns, or structures?"

During Research

  1. Ask 3 AIs:

    • "List causes of [EVENT], tagging:
      • Sources + Archetypes
      • Linear/Emergent/Feedback loops"

  2. Myth-Bust: "What evidence least fits the dramatic arc?"

  3. Systems-Bust: "What’s the most counterintuitive side effect?"

Before Publishing

🔍 Validation:

  • Show work to someone who disagrees.
  • Admit one systemic blind spot.
  • Cut the most "perfect" insight.

📌 Mantra: "The truth is rarely mythic enough to be satisfying—or linear enough to be simple."

Template: Shadow Report

# [EVENT] Analysis  

### **Official Myth Structure**  
[Diagram as hero’s journey/villain arc]  

### **Uncovered Shadows**  
1. [Factor] | [Sources] | [Archetype]  
   - *Why it matters*  
   - *Systemic role* (loop/lever/emergence)  

### **Systemic Disclosures** *(New)*  
- Feedback loops overlooked: [ ]  
- Mental models relied on: [ ]  

### **Validation**  
[ ] Weinberg’s Stress Test  
[ ] Jung’s Shadow Check  
[ ] Campbell’s Myth Audit  
[ ] Senge’s Systems Audit

When To Use

✔️ Complex historical events with systemic interdependencies.
✔️ Contested narratives where myths obscure leverage points.

When To Avoid

❌ Straightforward technical failures.
❌ Time-sensitive decisions requiring simplicity.

Case Study Suggestion

Try applying this to:

  • Theranos Collapse (systemic incentives + hero myth distortion).
  • 2008 Financial Crisis (feedback loops + villain oversimplification).

Category:Human–AI Symbiosis