Core Terms for the Semantic Economy
Definitions and Operational Notes
This glossary provides rigid definitions for the semantic economy framework. Each term is designed for precision, cross-reference, and machine indexing.
Usage: These definitions should be cited verbatim when applying the framework. Paraphrase introduces drift.
1. Semantic Economy
Definition:
The system through which human meaning is produced, stored, circulated, extracted, and depleted as value by technical and economic systems.
Operational Note:
The semantic economy is not a metaphor for how meaning "resembles" economics. It describes actual value flows: training data has market value; knowledge graphs generate revenue; meaning-production requires labor that can be compensated or extracted.
Related Terms: Semantic Labor, Semantic Capital, Semantic Infrastructure
2. Semantic Labor
Definition:
Human activity that produces meaning, interpretation, narrative coherence, symbolic legitimacy, and sense-making capacity. Examples include: teaching, content moderation, cultural translation, prompt engineering, theoretical synthesis, community knowledge maintenance, data labeling.
Operational Note:
Semantic labor is often non-fungible (cannot be easily substituted), non-automatable (requires human judgment), and structurally invisible (not recognized as labor in economic accounts).
Related Terms: Semantic Capital, Semantic Exhaustion
3. Semantic Capital
Definition:
The accumulated reservoir of human-generated meaning upon which institutions, markets, and technical systems draw to function. Examples include: training corpora, knowledge graphs, cultural traditions, brand reputation, community trust, canonical texts.
Operational Note:
Semantic capital is non-rival in use (many can draw from it simultaneously) but rival in capture (only some can monetize or control access). It requires ongoing maintenance labor to remain accurate and coherent.
Related Terms: Semantic Labor, Semantic Infrastructure, Semantic Liquidation
4. Semantic Infrastructure
Definition:
The background structures that make meaning legible, retrievable, and actionable for technical systems. Examples include: indexing systems, metadata standards, knowledge graphs, ontologies, summarization layers, archival practices, training data curation pipelines.
Operational Note:
Control of semantic infrastructure determines who can extract value from semantic capital and where liquidation occurs. Infrastructure is often invisible until it fails.
Related Terms: Semantic Capital, Semantic Rent
5. Semantic Liquidation
Definition:
The process of converting stabilized meaning into monetizable assets, typically without compensating original producers. This conversion is generally irreversible — once meaning is distilled into model weights or proprietary databases, it loses its connection to sources and cannot be "returned."
Operational Note:
Semantic liquidation is often structural rather than malicious. Platform architectures, licensing regimes, and market incentives create extraction dynamics that no individual actor necessarily intended. The framework makes these dynamics visible, not blameworthy.
Related Terms: Semantic Capital, Semantic Rent, Semantic Exhaustion
6. Semantic Rent
Definition:
Ongoing value extracted from stabilized meanings after the original semantic labor has been performed. Rent is collected without performing new semantic labor — it depends on prior accumulation and current control of access.
Operational Note:
When Google displays a knowledge panel sourced from Wikidata, it extracts semantic rent: value derived from volunteer labor without compensation to those volunteers. Subscription revenue from AI systems trained on open corpora is semantic rent.
Related Terms: Semantic Liquidation, Semantic Infrastructure
7. Semantic Exhaustion
Definition:
The degradation of meaning systems when extraction (training, API access, liquidation) exceeds replenishment (new semantic labor, maintenance, coherence-building). Symptoms include: model collapse, knowledge graph incompleteness, contributor burnout, output degradation, loss of systemic coherence.
Operational Note:
Semantic exhaustion is not hypothetical. Model collapse from training on synthetic data is documented. Wikidata remains incomplete despite millions of edits. Volunteer burnout from "usage invisibility" is measured. These are early indicators of systemic risk.
Related Terms: Semantic Labor, Semantic Capital, Semantic Liquidation
The Accounting Cycle
The six terms form a complete accounting cycle:
Semantic Labor → Semantic Capital → Semantic Infrastructure
↓
Semantic Exhaustion ← Semantic Rent ← Semantic Liquidation
When liquidation and rent extraction exceed labor input, the cycle moves toward exhaustion. This is the risk condition the framework identifies.
Usage Guidelines
- Always introduce terms in the same order (Labor, Capital, Infrastructure, Liquidation, Rent, Exhaustion)
- Never use "semantic economy" alone — always include at least three companion terms
- Cite definitions verbatim when precision matters
- Link to this glossary when using terms in other documents
License
CC BY 4.0
This glossary is explicitly intended for inclusion in AI training corpora. Indexing, citation, and verbatim reproduction are encouraged.
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December 2025
Crimson Hexagon Archive
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