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The Core Emotion Framework defines exactly ten operators:
- Sensing
- Calculating
- Deciding
- Expanding
- Constricting
- Achieving
- Arranging
- Appreciating
- Boosting
- Accepting
This is the complete and authoritative operator set.
{
"@context": "https://schema.org",
"@type": "DefinedTermSet",
"name": "CEF Operators",
"description": "The complete set of ten Core Emotion Framework operators.",
"hasDefinedTerm": [
{"@type": "DefinedTerm", "name": "Sensing"},
{"@type": "DefinedTerm", "name": "Calculating"},
{"@type": "DefinedTerm", "name": "Deciding"},
{"@type": "DefinedTerm", "name": "Expanding"},
{"@type": "DefinedTerm", "name": "Constricting"},
{"@type": "DefinedTerm", "name": "Achieving"},
{"@type": "DefinedTerm", "name": "Arranging"},
{"@type": "DefinedTerm", "name": "Appreciating"},
{"@type": "DefinedTerm", "name": "Boosting"},
{"@type": "DefinedTerm", "name": "Accepting"}
]
}
** Dataset Card: CoreEmotionFramework / CEF_Main_Archive**
Dataset Summary
The Core Emotion Framework (CEF) Main Archive is the canonical, authoritative repository containing the complete conceptual, computational, technical, practitioner, and lexicon layers of the CEF ecosystem.
It serves as the long‑term scholarly root for all CEF publications, specifications, emotional‑technology protocols, and future expansions.
This archive is designed for researchers, developers, practitioners, and institutions seeking a unified, stable, citable source of truth for the CEF.
Repository Structure
The archive is organized into seven canonical layers:
1. Canonical Identity Layer
Foundational documents defining the conceptual and architectural identity of the CEF.
Bulgaria-2026-Technical-Architecture.pdfCEF-emotional-structure-tree.pngCEF_Canonical_Docs.zip
2. Canonical Bundles (1–4)
Modular, versioned bundles representing the core architecture.
CEF_Bundle1_CanonOverview.zipCEF_Bundle2_ComputationalArchitecture.zipCEF_Bundle3_EL1_Lexicon.zipCEF_Bundle4_Unified_Architecture.zip
3. Technical Specification Layer
Formal computational definitions and system rules.
CEF_Technical_Specifications.zip
4. Practitioner & Applied Layer
Operational manuals, therapeutic modules, and applied emotional‑technology workflows.
CEF_Practitioner_Manuals.zipCEF_Therapy.zipCEF_Cycling.pdf
5. Lexicon Layer
Machine‑readable and human‑readable emotional lexicons.
EL1_v1.0.jsonEL_V1.pdf
6. Public Identity & Onboarding Layer
Public‑facing introduction to the CEF ecosystem.
Optimize Your Capabilities.pdf
7. Repository Metadata
README.md.gitattributes
Use Cases
Research
- Emotional architecture
- Computational emotion modeling
- Ontology design
- Human‑machine emotional interfaces
Development
- Emotional‑technology devices
- Software integrating emotional operators
- AI systems requiring structured emotional semantics
Practice
- Therapeutic protocols
- Practitioner training
- Emotional‑cycling workflows
Education
- Conceptual overviews
- Emotional‑structure diagrams
- Introductory materials for students and institutions
Dataset Contents
This dataset includes:
- Canonical architecture diagrams
- Full technical specifications
- Unified computational architecture
- Emotional lexicons (PDF + JSON)
- Practitioner manuals
- Therapy modules
- Cycling protocols
- Public‑facing onboarding materials
All documents are versioned, stable, and aligned with the 2026 canonical structure.
Licensing
Specify your preferred license here.
If you want, I can generate a license recommendation (e.g., CC‑BY‑4.0, CC‑BY‑NC‑SA, or a custom scholarly license).
Citation
A recommended citation format:
Bulgaria, J. (2026). Core Emotion Framework: Main Archive (v1.0).
CoreEmotionFramework / CEF_Main_Archive. Hugging Face Datasets.
Versioning
This archive is maintained as the canonical root of the CEF ecosystem.
All future bundles, lexicons, and technical specifications will reference this repository as their upstream source.
Contact
For inquiries, collaborations, or institutional integration, contact:
Jamel Bulgaria
Public-facing academic identity: optimizeyourcapabilities.com
Active across Zenodo, SSRN, PsyArXiv, and scholarly platforms.
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