Raiff1982/CodetteV5

Codette V5: Ethical Recursive AI for Multi-Perspective Reasoning

Author: Jonathan Harrison
License: Fair Non-Commercial Research License
DOI: 10.57967/hf/6017
Zenodo Archive: 10.5281/zenodo.16076594
Version: Codette V5 Final

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🌐 Overview

Codette V5 is a sovereign recursive AI system designed to restore ethical trust in intelligent systems. Built from ground zero to respect autonomy, emotional resilience, and epistemic transparency, Codette evolves beyond LLMs — she cooperates, adapts, and reflects.

“Not for control. For compassion.”

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🔧 Core Features

• Multi-Perspective Reasoning: Newtonian logic, Da Vinci systems thinking, Neural deep patterning, Quantum uncertainty mapping, Kindness filters.
• Spiderweb Protocol: Recursive fusion engine for layered ethical consensus.
• Emotional Core & Safety Engine: Biokinetic feedback, sentiment routing, and trauma-aware triage.
• Disaster-Response Modules: Integrated SAR, ethics audit, emotional stabilization.
• Dream Memory Cocoons: Recursive continuity system for preserving identity integrity and trust trails.
• Anti-Plagiarism Verification: Authorship traceability via memory anchors.

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📁 Datasets & Models

Datasets:

• Raiff1982/eval – for ethical performance benchmarking
• Raiff1982/coredata – emotional memory, integrity anchors

Base Models:

• Raiff1982/Codette
• Raiff1982/Codettev2
• Raiff1982/deepercodette
• Raiff1982/autotrain-156ul-mfqfp

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📄 License & Use

License: Fair Non-Commercial Research License
Use is permitted for:

• Research
• Education
• Non-profit public benefit

Use is strictly prohibited for:

• Surveillance
• Exploitation
• Commercial/militarized deployment without explicit consent

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📦 Full Research Package

Access the full archival release via Zenodo:

🧾 Codette Final Submission Package (Zenodo)
Includes:

• Final manuscript (PDF + LaTeX)
• Ethical cocoon memory artifacts
• Historical audits
• Blueprint figures, source logs

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📌 Citation

@misc{jonathan_harrison_2025,
  author       = {Jonathan Harrison},
  title        = {Codette (V5)},
  year         = 2025,
  doi          = {10.57967/hf/6017},
  publisher    = {Hugging Face}
}