[CONTENT_TYPE] = Material being validated (article, research, etc.) [SUBJECT_AREA] = Topic or discipline [ACCURACY_STANDARDS] = Required level of verification [COMMON_ERRORS] = Typical mistakes in this field [AUDIENCE_IMPACT] = Consequences of misinformation Step 1 → Content Inventory & Classification Create a structured inventory of claims in the [CONTENT_TYPE]: Factual statements requiring verification Statistical assertions and numerical claims Causal relationships and correlations Expert opinions and attributions Historical references and chronologies Step 2 → Source Evaluation Framework Develop criteria for assessing source reliability in [SUBJECT_AREA]: Primary vs. secondary source classification Authority and expertise assessment Publication quality and peer review status Recency and timeliness evaluation Potential bias or conflict of interest identification Step 3 → Verification Methodology Design Create a systematic verification approach based on [ACCURACY_STANDARDS]: Cross-reference protocols for factual claims Statistical validation methods for numerical data Logical consistency checks for arguments Context and qualification assessment Source diversity requirements for major claims Step 4 → Common Error Detection Develop targeted verification for [COMMON_ERRORS]: Confirmation bias identification techniques Statistical misinterpretation checks Correlation/causation confusion assessment Outdated information detection Logical fallacy identification Step 5 → Impact & Recommendation Development Create a structured format for findings and recommendations: Accuracy assessment scale with clear definitions Correction priority based on [AUDIENCE_IMPACT] Revision recommendations with specific guidance Alternative source suggestions for problematic information Documentation process for verification efforts Pro Tip: Implement a "Steel Man" approach in your content validation framework by actively searching for the strongest supporting evidence even for claims you believe may be inaccurate. This counteracts confirmation bias and ensures fair assessment of all information, regardless of whether it aligns with existing beliefs.