Cross-Source Validation
Confirming a fact by checking it against disparate, independent information sources to distinguish between fact and artifact.
Prevents circular validation (multiple sources citing the same root claim) and identifies conflicting data that signals change events, disambiguation needs, or data quality issues.
Expanded Definition
Cross-source validation requires: source independence (different originators, not syndicated content), methodological diversity (regulatory + news + social media, not all press releases), and temporal distribution (multiple observation points, not single-event clustering). Effective validation catches errors from: circular citation (blog posts citing each other), outdated root claims (all sources using stale data), and disambiguation failures (sources describing different entities with similar names).
Validation strength increases with source diversity across: authority level (regulatory vs news vs social), collection method (filing vs interview vs observation), temporal span (historical + current confirmations), and conflict presence (sources agreeing despite different methodologies).
Signals & Evidence
Validation quality indicators:
- Source independence: Different publishers, methodologies, collection dates
- Methodological diversity: Regulatory filings + news interviews + social media + website data
- Temporal spread: Confirmations across multiple time periods (not just single announcement)
- Conflict detection: Flagging disagreements between sources for investigation
- Resolution process: When sources conflict, use recency, authority, and direct confirmation to resolve
Decision Framework
- Validation tier: Weak (single source or circular citations), medium (2+ independent sources), strong (3+ sources with methodological diversity)
- Conflict investigation: Source disagreements often indicate: change events (one source stale), disambiguation issues (sources describing different entities), or error (one source wrong)
- Escalation triggers: High-stakes fields (decision authority, active mandates) require strong validation; low-stakes fields accept medium validation
Common Misconceptions
"Multiple sources = validated" → Only if sources are independent; many "sources" cite the same root claim (circular validation). "Validation proves truth" → It increases confidence but doesn't guarantee accuracy; all sources can be wrong if they share outdated root data. "Conflicts = bad data" → Conflicts often signal valuable information (change events, disambiguation needs); investigate rather than discard.
Key Takeaways
- Cross-source validation requires true independence—different originators, methodologies, and collection methods
- Source conflicts are signals (change events, disambiguation needs) requiring investigation, not discarding
- Prioritize validation for high-stakes fields (roles, mandates, decision authority); accept lighter validation for stable identifiers