Interpretive governance
This expertise axis focuses on the explicit bounding of the inference space in order to make machine interpretation more stable, more cross-referenceable, and less vulnerable to default extrapolations.
Interpretive governance does not aim to control systems. It aims to reduce the structural ambiguity that allows inference systems to produce plausible but erroneous interpretations.
This work is defined by interpretive governance and falls under the SSA-E + A2 + Dual Web framework.
Problem
In an interpreted web, the absence of explicit constraints acts as free space: what is not bounded becomes interpretable, and what is not hierarchized becomes interchangeable.
Interpretation errors rarely stem from a “lack of content”. They more often stem from an implicit source hierarchy, undeclared exclusions, and poorly defined relations.
Typical consequences
- Plausible but erroneous inferences about services, roles, capabilities, or perimeters.
- Contradictions between pages, sections, and external sources.
- Unstable responses depending on engines, models, and queries.
- Progressive perimeter shifts, through cumulative extrapolation.
- Difficulty in getting a stable source of truth recognized.
Conceptual levers
- Explicit perimeters: what does, and does not, belong to an entity or corpus.
- Source hierarchies: declared prioritization of truth points.
- Negations and exclusions: prevention of default inferences.
- Canonical references: directional and stable relations between resources.
- Machine-readable rendering: conventions, files, graphs, interpretable entry points.
Canonical references
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