# Method independence

FinGovBench evaluates governance of a financial AI workflow. It does not require any
particular model architecture or graph-based submission.

## Independent benchmark object

Each public case declares the operational workflow boundary, versioned components,
dependencies, evidence available at the case's `as_of` time, assurance claims, authority
tier, permitted actions and observed change. This is a system specification analogous to
an architecture or lineage record. It contains no method-specific probabilities, path
contributions or certificates.

Gold outcomes are defined by the financial event and governance contract:

- SEC cases use an official accession-level reported-value pair and a declared workflow
  contract; their labels remain provisional until independent domain adjudication.
- controlled cases use a prespecified event, authority boundary and executable contract.
- the evaluator, not a submitted method, determines whether the selected action and
  revalidation scope permit release.

## What a submission must do

A method receives the same workflow declaration and must return the affected
components, governance action, revalidation components and release decision. A submission
may use rules, a flat uncertainty model, an LLM, a knowledge graph or another method.
It may transform the neutral workflow declaration into its preferred internal format.

## Optional graph-based methods

Graph-based uncertainty propagation is one optional evaluated approach. It must read
exactly the same public closed-loop inputs as lexical and flat-uncertainty comparators. No
method-specific telemetry or labels are provided.

## Anti-circularity requirements

Before version 1.0:

1. independent reviewers must adjudicate event validity, required action and revalidation
   scope without seeing any method prediction;
2. submitted predictions cannot alter gold labels or case inclusion;
3. all methods receive the same public inputs and sealed test labels;
4. genuine and controlled results remain separate; and
5. any threshold or learned policy freezes on development data before test evaluation.