Every evidence row now records its derivation (direct, assertion, operator,
external, prediction, consolidation, inference, reflection, dream,
retrieval), its independent-source family (an actor, an integration, an
operator, a prediction) and its root event or memory ids. Confidence
groups evidence by family: the strongest primary item counts in full, each
further primary item adds a quarter, capped at 1.5x, and derived items
count only when the family has no primary member. Three derived
re-expressions of one utterance therefore weigh exactly what the utterance
weighs, while three independent families still add up.
Producers (conversation, association, consolidation, predictions,
metacognition, dreaming, operator and seed input, contradictions) supply
their ancestry. Existing rows are marked legacy_unknown with family =
source; nothing is invented. The belief page shows per-family
contributions and the replay test checks that provenance is reconstructed
identically in the sandbox. Migration 0017 is additive.
Phase 6. Beliefs are propositions with a prior set by epistemic kind and a
confidence computed from typed evidence: sigmoid(logit(prior) + slope ×
(support × diversity − opposition)), where support from a single source
is discounted so repetition cannot manufacture certainty, and bounds keep
the mind away from absolute certainty. Every evaluation stores its
breakdown and appends a version row protected by the append-only
trigger; the belief page shows the arithmetic, evidence for and against,
alternatives, contradictions and history.
Contradiction detection is deterministic first (negation plus token
overlap): a hit emits contradiction_detected, links both beliefs and
makes each counter-evidence for the other so both trend to contested.
Operators can assert beliefs (their statement is the evidence), add
evidence, mark a belief wrong (pinned rejected, history kept) and forbid
an inference; do-not-infer corrections block matching hypotheses.
Retracting a memory retracts the evidence that cited it and re-evaluates
the beliefs concerned.
The associate process proposes low-confidence causal hypotheses from
co-occurring notable observations, and the hypothesis handler turns
admitted ones into beliefs with automatic alternatives, closing demo
scenarios 1 and 2 without any model call.
Andy Dixon