confidence-engine/docs/v0.6-ambiguity-generalisation.md

v0.6 Ambiguity Generalisation

Hypothesis

If the selector truly handles unjustified contradiction ties generically, it should return ambiguity across multiple domains without preferring one explanation by wording alone.

Scenarios

1. Revenue increased by 18%, but cash in the bank fell over the same period.
2. Customer satisfaction scores increased, but complaints also increased.
3. Average delivery time decreased by 25%, but order cancellations increased.
4. Website traffic doubled, but sales remained unchanged.
5. Production output increased by 30%, but quality defects also increased.

Observed behaviour

All five fixtures produced the same pattern:

• candidate count: 2
• selector status: ambiguous
• tie reason: No justified distinction between leading unknowns.
• no explanation was favoured
• one broad investigation question was produced from the central contradiction
• neutral label renaming did not collapse ambiguity into a winner

Repeated failure patterns

None observed across two or more scenarios.

The current ambiguity handling generalised cleanly across the five contradiction fixtures.

Corrections

No production correction was required in this task.

Lessons learned

• The current ambiguity path appears domain-agnostic when structure and semantic weights remain intentionally non-discriminating.
• Central-statement-based tie questions are broad enough to avoid prematurely backing one branch.
• The most useful regression signal is whether ambiguity survives neutral relabelling, not whether one label sorts ahead of another in display order.