Glossary: sustainability, debt, correction
This family groups the notions that describe the real cost and discipline needed to maintain a canonical truth over time, in a web interpreted by AI systems.
The issue is not merely to “correct” a response: it is to prevent regression, avoid inertia, and make correction sustainable.
Each entry links to:
a canonical definition (if it exists), a framework (if applicable), and related pages for moving from diagnosis to execution.
Quick access
Terms in the “sustainability, debt, correction” family
Interpretive debt
Accumulation of gaps between a canon (declared truth) and the interpretation returned by AI systems, until correction becomes costly, slow, or unstable.
- Definition: Interpretive debt
- Framework: Interpretive debt: accumulation dynamics and extinction
Interpretive sustainability
Capacity of a system (and a corpus) to maintain a canonical truth without letting correction and maintenance costs explode.
- Definition: Interpretive sustainability
Correction budget
Recurring effort required to prevent regressions, correct drifts, and stabilize outputs over time (rather than a one-time effort).
- Doctrine: Version power
Interpretive correction (resorption)
Process of resorbing canon-output gaps, with evidence discipline, prioritization, and anti-regression mechanisms.
Canonical fragility
Vulnerability of a canon when its truth depends on too few surfaces, formats, or artifacts: a local break suffices to cause global interpretation drift.
- Definition: Canonical fragility
- Doctrine: Endogenous governance and Exogenous governance
Version power
Principle that interpretive correction must be maintained and versioned like software: without version discipline, corrections regress and ambiguities reappear.
- Definition: Version power
- Doctrine: Version power in a web interpreted by AI
Related frameworks and pages (recommended)
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