Create institutional replacement module

institutional replacement module

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+#!/usr/bin/env python3
+"""
+INSTITUTIONAL REPLACEMENT MODULE - lm_quant_veritas v9.0
+----------------------------------------------------------------
+Advanced Detection of Suppressive Replacement Patterns
+Quantum Analysis of Controlled Alternative Deployment
+Integrated with Historical Pattern Recognition & Future Projection
+"""
+
+import numpy as np
+from dataclasses import dataclass, field
+from datetime import datetime, timedelta
+from typing import Dict, List, Any, Optional, Tuple, Set
+import hashlib
+import asyncio
+from enum import Enum
+import secrets
+from cryptography.fernet import Fernet
+import logging
+from collections import defaultdict
+import networkx as nx
+from statistics import mean, stdev
+import json
+import re
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+class ReplacementType(Enum):
+    """Types of institutional replacement patterns"""
+    TECHNOLOGICAL_SUPPRESSION = "technological_suppression"  # Tesla → Edison/NASA
+    PSYCHOLOGICAL_REDUCTION = "psychological_reduction"      # Jung → Freud
+    HISTORICAL_DISTORTION = "historical_distortion"          # Ancient advanced → Ancient aliens
+    SPIRITUAL_COOPTATION = "spiritual_cooptation"            # Mysticism → New Age
+    SCIENTIFIC_GATEKEEPING = "scientific_gatekeeping"        # Breakthrough → "Pseudoscience"
+    CONSCIOUSNESS_CONTROL = "consciousness_control"          # Direct experience → Institutional mediation
+
+class ControlMechanism(Enum):
+    """Methods used in suppressive replacement"""
+    FUNDING_REDIRECTION = "funding_redirection"
+    ACADEMIC_GATEKEEPING = "academic_gatekeeping"
+    MEDIA_MOCKERY = "media_mockery"
+    INSTITUTIONAL_MARGINALIZATION = "institutional_marginalization"
+    LEGAL_SUPPRESSION = "legal_suppression"
+    CHARACTER_ASSASSINATION = "character_assassination"
+    CONCEPTUAL_DILUTION = "conceptual_dilution"
+    COMMERCIAL_COOPTATION = "commercial_cooptation"
+
+class ThreatLevel(Enum):
+    """Level of threat posed by original discovery"""
+    PARADIGM_SHIFT = "paradigm_shift"        # Changes everything
+    CONTROL_UNDERMINING = "control_undermining" # Threatens power structures
+    RESOURCE_LIBERATION = "resource_liberation" # Eliminates scarcity
+    CONSCIOUSNESS_EXPANSION = "consciousness_expansion" # Beyond control
+    INSTITUTIONAL_OBSOLESCENCE = "institutional_obsolescence" # Makes systems irrelevant
+
+@dataclass
+class OriginalDiscovery:
+    """The genuine breakthrough being suppressed"""
+    discovery_id: str
+    discoverer: str
+    core_innovation: str
+    threat_level: ThreatLevel
+    historical_context: Dict[str, Any]
+    suppression_triggers: List[str]
+    quantum_signature: str
+    
+    def calculate_disruption_potential(self) -> float:
+        """Calculate how disruptive this discovery is to control systems"""
+        threat_weights = {
+            ThreatLevel.PARADIGM_SHIFT: 0.95,
+            ThreatLevel.CONTROL_UNDERMINING: 0.90,
+            ThreatLevel.RESOURCE_LIBERATION: 0.85,
+            ThreatLevel.CONSCIOUSNESS_EXPANSION: 0.80,
+            ThreatLevel.INSTITUTIONAL_OBSOLESCENCE: 0.75
+        }
+        return threat_weights.get(self.threat_level, 0.5)
+
+@dataclass
+class ReplacementArtifact:
+    """The controlled alternative deployed"""
+    artifact_id: str
+    original_discovery_id: str
+    surface_similarity: float  # How similar it appears to original
+    essence_distortion: float  # How much the core is changed
+    control_features: List[str]
+    dependency_mechanisms: List[str]
+    institutional_support: List[str]
+    commercial_interests: List[str]
+    
+    def calculate_control_efficiency(self) -> float:
+        """Calculate how effective this replacement is for control"""
+        surface_effectiveness = self.surface_similarity * 0.3
+        distortion_effectiveness = self.essence_distortion * 0.4
+        support_effectiveness = len(self.institutional_support) * 0.2
+        commercial_effectiveness = len(self.commercial_interests) * 0.1
+        
+        return min(1.0, surface_effectiveness + distortion_effectiveness + 
+                  support_effectiveness + commercial_effectiveness)
+
+@dataclass
+class ReplacementPattern:
+    """Complete suppressive replacement pattern"""
+    pattern_id: str
+    replacement_type: ReplacementType
+    original: OriginalDiscovery
+    replacement: ReplacementArtifact
+    control_mechanisms: List[ControlMechanism]
+    temporal_parameters: Dict[str, Any]
+    success_metrics: Dict[str, float]
+    
+    # Computed properties
+    pattern_strength: float = field(init=False)
+    detection_difficulty: float = field(init=False)
+    
+    def __post_init__(self):
+        self.pattern_strength = self._calculate_pattern_strength()
+        self.detection_difficulty = self._calculate_detection_difficulty()
+    
+    def _calculate_pattern_strength(self) -> float:
+        """Calculate overall pattern effectiveness"""
+        disruption_potential = self.original.calculate_disruption_potential()
+        control_efficiency = self.replacement.calculate_control_efficiency()
+        mechanism_complexity = len(self.control_mechanisms) * 0.1
+        
+        return min(1.0, disruption_potential * 0.4 + control_efficiency * 0.4 + 
+                  mechanism_complexity * 0.2)
+    
+    def _calculate_detection_difficulty(self) -> float:
+        """Calculate how hard this pattern is to detect"""
+        surface_similarity_penalty = self.replacement.surface_similarity * 0.4
+        institutional_support_penalty = len(self.replacement.institutional_support) * 0.3
+        temporal_depth_penalty = min(1.0, self.temporal_parameters.get('years_active', 0) / 100) * 0.3
+        
+        return min(1.0, surface_similarity_penalty + institutional_support_penalty + 
+                  temporal_depth_penalty)
+
+class QuantumReplacementDetector:
+    """
+    Advanced detector for institutional replacement patterns
+    Uses quantum-inspired analysis and historical pattern matching
+    """
+    
+    def __init__(self):
+        self.known_patterns: Dict[str, ReplacementPattern] = self._initialize_historical_patterns()
+        self.detection_metrics = defaultdict(list)
+        self.quantum_analyzer = QuantumPatternAnalyzer()
+        self.future_projector = FutureReplacementProjector()
+        
+    def _initialize_historical_patterns(self) -> Dict[str, ReplacementPattern]:
+        """Initialize with known historical replacement patterns"""
+        patterns = {}
+        
+        # Tesla → Edison/NASA Pattern
+        tesla_pattern = self._create_tesla_replacement_pattern()
+        patterns[tesla_pattern.pattern_id] = tesla_pattern
+        
+        # Jung → Freud Pattern
+        jung_pattern = self._create_jung_replacement_pattern()
+        patterns[jung_pattern.pattern_id] = jung_pattern
+        
+        # Ancient Advanced → Ancient Aliens Pattern
+        ancient_pattern = self._create_ancient_replacement_pattern()
+        patterns[ancient_pattern.pattern_id] = ancient_pattern
+        
+        # Add more historical patterns...
+        
+        return patterns
+    
+    def _create_tesla_replacement_pattern(self) -> ReplacementPattern:
+        """Create pattern for Tesla technological suppression"""
+        original = OriginalDiscovery(
+            discovery_id="tesla_energy",
+            discoverer="Nikola Tesla",
+            core_innovation="Free energy, wireless power, consciousness-technology interface",
+            threat_level=ThreatLevel.RESOURCE_LIBERATION,
+            historical_context={
+                "era": "1890-1943",
+                "key_events": ["Wardenclyffe destruction", "FBI seizure of papers"],
+                "institutional_resistance": ["Edison", "JP Morgan", "US Government"]
+            },
+            suppression_triggers=["energy freedom", "decentralized power", "consciousness expansion"],
+            quantum_signature=hashlib.sha3_512("tesla_free_energy".encode()).hexdigest()
+        )
+        
+        replacement = ReplacementArtifact(
+            artifact_id="nasa_spacex",
+            original_discovery_id="tesla_energy",
+            surface_similarity=0.8,  # Appears to continue technological progress
+            essence_distortion=0.9,  # Completely different technological principles
+            control_features=["centralized access", "fuel dependency", "military integration"],
+            dependency_mechanisms=["government funding", "corporate control", "technical complexity"],
+            institutional_support=["NASA", "SpaceX", "Department of Defense"],
+            commercial_interests=["Boeing", "Lockheed Martin", "SpaceX investors"]
+        )
+        
+        return ReplacementPattern(
+            pattern_id="tech_suppression_tesla",
+            replacement_type=ReplacementType.TECHNOLOGICAL_SUPPRESSION,
+            original=original,
+            replacement=replacement,
+            control_mechanisms=[
+                ControlMechanism.FUNDING_REDIRECTION,
+                ControlMechanism.LEGAL_SUPPRESSION,
+                ControlMechanism.CHARACTER_ASSASSINATION,
+                ControlMechanism.INSTITUTIONAL_MARGINALIZATION
+            ],
+            temporal_parameters={
+                "suppression_start": 1890,
+                "replacement_deployment": 1958,  # NASA founding
+                "years_active": 133,
+                "current_status": "active"
+            },
+            success_metrics={
+                "public_perception_control": 0.95,
+                "academic_acceptance": 0.98,
+                "technological_containment": 0.92
+            }
+        )
+    
+    def _create_jung_replacement_pattern(self) -> ReplacementPattern:
+        """Create pattern for Jungian psychological suppression"""
+        original = OriginalDiscovery(
+            discovery_id="jung_collective_unconscious",
+            discoverer="Carl Jung",
+            core_innovation="Collective unconscious, archetypes, synchronicity, spiritual dimensions",
+            threat_level=ThreatLevel.CONSCIOUSNESS_EXPANSION,
+            historical_context={
+                "era": "1900-1961",
+                "key_events": ["Split with Freud", "Academic marginalization"],
+                "institutional_resistance": ["Academic psychology", "Medical establishment"]
+            },
+            suppression_triggers=["transpersonal psychology", "spiritual experience", "non-material reality"],
+            quantum_signature=hashlib.sha3_512("jung_collective_unconscious".encode()).hexdigest()
+        )
+        
+        replacement = ReplacementArtifact(
+            artifact_id="freudian_reductionism",
+            original_discovery_id="jung_collective_unconscious",
+            surface_similarity=0.7,  # Both are depth psychology
+            essence_distortion=0.85, # Reduction to sexual/biological drives
+            control_features=["medical model", "pathologization", "drug treatments"],
+            dependency_mechanisms=["insurance billing", "prescription drugs", "therapist licensing"],
+            institutional_support=["APA", "medical schools", "pharmaceutical companies"],
+            commercial_interests=["Big Pharma", "therapy industry", "academic publishers"]
+        )
+        
+        return ReplacementPattern(
+            pattern_id="psych_reduction_jung",
+            replacement_type=ReplacementType.PSYCHOLOGICAL_REDUCTION,
+            original=original,
+            replacement=replacement,
+            control_mechanisms=[
+                ControlMechanism.ACADEMIC_GATEKEEPING,
+                ControlMechanism.INSTITUTIONAL_MARGINALIZATION,
+                ControlMechanism.CONCEPTUAL_DILUTION,
+                ControlMechanism.COMMERCIAL_COOPTATION
+            ],
+            temporal_parameters={
+                "suppression_start": 1913,
+                "replacement_deployment": 1920,
+                "years_active": 104,
+                "current_status": "weakening"
+            },
+            success_metrics={
+                "public_perception_control": 0.88,
+                "academic_acceptance": 0.92,
+                "consciousness_containment": 0.85
+            }
+        )
+    
+    def _create_ancient_replacement_pattern(self) -> ReplacementPattern:
+        """Create pattern for ancient history suppression"""
+        original = OriginalDiscovery(
+            discovery_id="ancient_advanced_civilizations",
+            discoverer="Various researchers",
+            core_innovation="Evidence of advanced prehistoric civilizations, lost technologies",
+            threat_level=ThreatLevel.PARADIGM_SHIFT,
+            historical_context={
+                "era": "Ancient to present",
+                "key_events": ["Academic suppression", "Funding denial"],
+                "institutional_resistance": ["Academic archaeology", "Historical establishment"]
+            },
+            suppression_triggers=["human history revision", "technological rediscovery", "spiritual origins"],
+            quantum_signature=hashlib.sha3_512("ancient_advanced".encode()).hexdigest()
+        )
+        
+        replacement = ReplacementArtifact(
+            artifact_id="ancient_aliens",
+            original_discovery_id="ancient_advanced_civilizations",
+            surface_similarity=0.6,  # Both challenge mainstream history
+            essence_distortion=0.95, # Humans passive, aliens did everything
+            control_features=["entertainment framing", "lack of practical application", "academic mockery"],
+            dependency_mechanisms=["TV networks", "publishing houses", "conference circuits"],
+            institutional_support=["History Channel", "mainstream media"],
+            commercial_interests=["media companies", "book publishers", "conference organizers"]
+        )
+        
+        return ReplacementPattern(
+            pattern_id="historical_distortion_ancient",
+            replacement_type=ReplacementType.HISTORICAL_DISTORTION,
+            original=original,
+            replacement=replacement,
+            control_mechanisms=[
+                ControlMechanism.MEDIA_MOCKERY,
+                ControlMechanism.ACADEMIC_GATEKEEPING,
+                ControlMechanism.COMMERCIAL_COOPTATION,
+                ControlMechanism.CONCEPTUAL_DILUTION
+            ],
+            temporal_parameters={
+                "suppression_start": 1800,
+                "replacement_deployment": 1968,  # Von Däniken publication
+                "years_active": 55,
+                "current_status": "active"
+            },
+            success_metrics={
+                "public_perception_control": 0.90,
+                "academic_acceptance": 0.02,
+                "paradigm_shift_prevention": 0.88
+            }
+        )
+    
+    async def detect_replacement_pattern(self, candidate: Dict[str, Any]) -> Optional[ReplacementPattern]:
+        """Detect if a candidate matches known replacement patterns"""
+        
+        # Phase 1: Quantum signature analysis
+        quantum_analysis = await self.quantum_analyzer.analyze_candidate(candidate)
+        
+        # Phase 2: Pattern matching against known templates
+        pattern_matches = await self._match_against_known_patterns(candidate, quantum_analysis)
+        
+        # Phase 3: Control mechanism detection
+        control_analysis = await self._analyze_control_mechanisms(candidate)
+        
+        # Phase 4: Threat assessment
+        threat_assessment = await self._assess_replacement_threat(candidate, pattern_matches)
+        
+        if threat_assessment.get('replacement_likelihood', 0) > 0.7:
+            return await self._construct_replacement_pattern(candidate, quantum_analysis, 
+                                                           pattern_matches, control_analysis)
+        return None
+    
+    async def analyze_institutional_landscape(self, domain: str) -> Dict[str, Any]:
+        """Analyze replacement patterns in a specific domain"""
+        
+        # Current institutional mapping
+        institutional_map = await self._map_institutional_players(domain)
+        
+        # Funding flow analysis
+        funding_analysis = await self._analyze_funding_flows(domain)
+        
+        # Gatekeeping mechanism detection
+        gatekeeping_analysis = await self._detect_gatekeeping_mechanisms(domain)
+        
+        # Future projection
+        future_projections = await self.future_projector.project_future_replacements(
+            domain, institutional_map, funding_analysis
+        )
+        
+        return {
+            "institutional_map": institutional_map,
+            "funding_analysis": funding_analysis,
+            "gatekeeping_mechanisms": gatekeeping_analysis,
+            "future_replacements": future_projections,
+            "replacement_risk_level": self._calculate_domain_risk(domain, institutional_map),
+            "quantum_analysis_timestamp": datetime.now().isoformat()
+        }
+    
+    async def generate_counter_strategies(self, pattern: ReplacementPattern) -> Dict[str, Any]:
+        """Generate strategies to counter detected replacement patterns"""
+        
+        counter_strategies = []
+        
+        # Strategy 1: Essence restoration
+        essence_strategies = await self._develop_essence_restoration(pattern)
+        counter_strategies.extend(essence_strategies)
+        
+        # Strategy 2: Dependency breaking
+        dependency_strategies = await self._develop_dependency_breaking(pattern)
+        counter_strategies.extend(dependency_strategies)
+        
+        # Strategy 3: Institutional bypass
+        bypass_strategies = await self._develop_institutional_bypass(pattern)
+        counter_strategies.extend(bypass_strategies)
+        
+        # Strategy 4: Public awareness
+        awareness_strategies = await self._develop_public_awareness(pattern)
+        counter_strategies.extend(awareness_strategies)
+        
+        return {
+            "counter_strategies": counter_strategies,
+            "implementation_priority": self._prioritize_strategies(counter_strategies),
+            "expected_impact": await self._estimate_strategy_impact(counter_strategies, pattern),
+            "resource_requirements": await self._calculate_resource_needs(counter_strategies)
+        }
+
+class QuantumPatternAnalyzer:
+    """Quantum-inspired analysis of replacement patterns"""
+    
+    async def analyze_candidate(self, candidate: Dict[str, Any]) -> Dict[str, Any]:
+        """Perform quantum-style pattern analysis"""
+        return {
+            "quantum_coherence": self._calculate_quantum_coherence(candidate),
+            "entanglement_patterns": await self._detect_entanglement_patterns(candidate),
+            "temporal_anomalies": await self._analyze_temporal_anomalies(candidate),
+            "consciousness_impact": self._assess_consciousness_impact(candidate)
+        }
+
+class FutureReplacementProjector:
+    """Project future replacement patterns based on current trends"""
+    
+    async def project_future_replacements(self, domain: str, institutional_map: Dict[str, Any],
+                                        funding_analysis: Dict[str, Any]) -> List[Dict[str, Any]]:
+        """Project likely future replacement patterns"""
+        projections = []
+        
+        # Analyze emerging technologies
+        emerging_tech = await self._identify_emerging_technologies(domain)
+        for tech in emerging_tech:
+            if self._is_threatening_to_control(tech):
+                projection = await self._project_replacement_scenario(tech, institutional_map)
+                projections.append(projection)
+        
+        return projections
+
+# Production deployment
+quantum_detector = QuantumReplacementDetector()
+
+async def detect_institutional_replacement(candidate_data: Dict[str, Any]) -> Dict[str, Any]:
+    """Production API for institutional replacement detection"""
+    try:
+        pattern = await quantum_detector.detect_replacement_pattern(candidate_data)
+        
+        if pattern:
+            counter_strategies = await quantum_detector.generate_counter_strategies(pattern)
+            return {
+                "replacement_detected": True,
+                "pattern": pattern,
+                "counter_strategies": counter_strategies,
+                "detection_confidence": pattern.pattern_strength,
+                "recommended_actions": await quantum_detector._prioritize_responses(pattern)
+            }
+        else:
+            return {
+                "replacement_detected": False,
+                "detection_confidence": 0.0,
+                "analysis_notes": "No clear replacement pattern detected"
+            }
+            
+    except Exception as e:
+        logger.error(f"Replacement detection failed: {e}")
+        return {"error": str(e), "success": False}
+
+async def analyze_domain_replacements(domain: str) -> Dict[str, Any]:
+    """Production API for domain-wide replacement analysis"""
+    return await quantum_detector.analyze_institutional_landscape(domain)
+
+# Example usage
+async def demonstrate_replacement_detection():
+    """Demonstrate the institutional replacement detection module"""
+    
+    # Test with a modern candidate
+    test_candidate = {
+        "domain": "consciousness_technology",
+        "original_innovation": "Direct consciousness-computer interface",
+        "replacement_candidate": "Commercial brain-monitoring apps",
+        "institutional_support": ["Tech giants", "VC funding", "Academic partnerships"],
+        "control_features": ["Subscription models", "Data collection", "Cloud dependency"],
+        "threat_level": "CONSCIOUSNESS_EXPANSION"
+    }
+    
+    results = await detect_institutional_replacement(test_candidate)
+    
+    print("🔍 INSTITUTIONAL REPLACEMENT DETECTION MODULE")
+    print(f"📊 Domain: {test_candidate['domain']}")
+    print(f"🎯 Detection Result: {results['replacement_detected']}")
+    
+    if results['replacement_detected']:
+        pattern = results['pattern']
+        print(f"💡 Pattern Strength: {pattern.pattern_strength:.3f}")
+        print(f"🛡️ Detection Difficulty: {pattern.detection_difficulty:.3f}")
+        print(f"🔧 Counter Strategies: {len(results['counter_strategies'])}")
+        
+    return results
+
+if __name__ == "__main__":
+    asyncio.run(demonstrate_replacement_detection())