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Trust layer severity model

Severity classifier

Not every metric definition change is equal. Cosmetic edits shouldn't reset trust. Structural rewrites should. This classifier shows how the trust layer responds proportionally, and why consumption confidence is the lever that makes it work.

What changed?

Select one or more definition changes. Blast radius and consumption confidence response update below.

Blast radius
No change selected
Select one or more changes to see the blast radius.
Lineage

Upstream sources and transformations

Unaffected
Freshness

Recency of the underlying data

Unaffected
Ownership

Accountable human or team

Unaffected
Discoverability

Name, description, tags, docs

Unaffected
Consumption confidence response

A governed metric with baseline consumption confidence of 92%. Watch how the trust layer responds when you publish the selected changes.

Before92%
After92%
No change selected. Consumption confidence stays at baseline.
The proportionality principle

Trust is a living signal. When the underlying definition shifts, consumers need to recalibrate, but only as much as the change actually warrants.
Cosmetic nudges. Moderate resets. Structural full stops. Nothing in between.

Severity covers the time-gap place. See calibration for the two places upstream that almost nobody audits.

Part of: Stage 04 · Catching Drift

Back to the map

A definition changes on a Tuesday and every downstream number quietly means something else. The layer classifies the change by blast radius and responds in proportion, instead of sounding one binary alarm, and watches the consumer, because a VP who hesitates is a faster signal than any dashboard.

Read the essay