Selection → Policy¶
This workflow defines how a selected forecast is transformed into an authoritative policy decision suitable for downstream execution.
In Electric Barometer, selection identifies which forecast to consider. Policy determines what actions are allowed. These are not the same step, and they are never collapsed.
Objective¶
The objective of the Selection → Policy workflow is to issue a binding governance outcome that declares:
- admissible interpretation semantics,
- readiness adjustment allowability,
- and execution constraints,
given a selected forecast and its evaluated diagnostics.
This workflow terminates interpretation. Once complete, no further diagnostic reasoning is admissible downstream.
Inputs¶
This workflow consumes:
1. Selected forecast¶
The output of Evaluation → Selection.
The selected forecast is treated as fixed and unmodified.
2. Evaluation diagnostics¶
The full diagnostic bundle associated with the selected forecast, including: - readiness metrics, - responsiveness observations, - and structural diagnostic outputs.
All diagnostics are assumed to be evaluated under authoritative unit semantics.
3. Structural compatibility diagnostics¶
Governance-relevant diagnostics, including: - Demand Quantization Compatibility (DQC), - Forecast Primitive Compatibility (FPC).
These diagnostics constrain policy allowability.
4. Governance parameters¶
Explicit thresholds and policy rules governing: - tolerance interpretation, - readiness adjustment constraints, - and admissibility rules.
These parameters are declared inputs, not tunable preferences.
Workflow steps¶
Step 1: Resolve authoritative representation¶
Governance declares the single admissible representation under which policy is evaluated.
Based on DQC: - raw-unit interpretation may be permitted, or - grid-aligned snapping may be mandatory.
This declaration is exclusive. Mixed representations are not allowed.
Step 2: Assess readiness adjustment allowability¶
Using authoritative representation semantics, governance evaluates Forecast Primitive Compatibility (FPC) to determine whether readiness adjustment is:
- Allowed,
- Conditionally allowed (under explicit constraints),
- or Disallowed.
This determination is structural, not performance-based.
Step 3: Declare policy outcome¶
Governance encodes the outcome as an explicit policy declaration, including: - interpretation semantics, - snapping requirements (if any), - readiness adjustment allowability, - and any binding constraints.
No optimization or negotiation occurs at this stage.
Step 4: Issue governance decision artifact¶
The workflow emits a single Governance Decision artifact containing: - the governing unit system, - tolerance interpretation rules, - readiness policy status, - and explicit reasoning statements.
This artifact is authoritative and binding.
Outputs¶
This workflow produces:
1. Governance decision artifact¶
The terminal output of the workflow pipeline.
Downstream systems must consume this artifact directly and may not reinterpret or override it.
2. Policy metadata¶
A structured record linking the policy decision to: - the evaluation context, - the selected forecast, - and the diagnostics used.
This metadata supports audit and reproducibility.
Scope and non-goals¶
This workflow does not:
- adjust forecasts,
- select among alternative policies,
- optimize operational outcomes,
- or override upstream diagnostics.
Policy declares admissibility; execution determines outcomes.
Governance notes¶
Governance enforces decision closure.
If required diagnostics are missing, inconsistent, or inadmissible: - no policy is issued, - the workflow fails explicitly, - and downstream execution is prohibited.
Graceful degradation is intentionally disallowed.
Summary¶
The Selection → Policy workflow ensures that:
- readiness decisions are structurally valid,
- assumptions are explicit and enforceable,
- and execution systems receive unambiguous guidance.
It is the boundary where evaluation ends and responsibility begins.