R0051/2026-03-31/Q003/H2¶
Statement¶
The gap has been identified and documented in academic literature, but not framed as needing a GRADE/IPCC/ICD 203-comparable solution. Scholars identify epistemological weaknesses without proposing formal evidence evaluation frameworks.
Status¶
Current: Supported
Supporting Evidence¶
| Evidence | Summary |
|---|---|
| SRC01-E01 | Three unsolved epistemological challenges explicitly documented |
| SRC02-E01 | Fact-checking methods critiqued as failing scientific epistemological standards |
| SRC03-E01 | Gap between automated tools and practitioner needs documented |
| SRC04-E01 | Practitioner confusion about confidence expression documented |
| SRC05-E01 | Epistemological challenges posed by generative AI identified |
Contradicting Evidence¶
| Evidence | Summary |
|---|---|
| None | No evidence contradicts the supported position |
Reasoning¶
Multiple independent papers from 2013-2026 identify epistemological gaps in fact-checking methodology. The gap is documented from multiple angles: scientific standards critique (Uscinski & Butler), theoretical epistemological analysis (Vandenberghe), practitioner study (Warren et al.), live fact-checking practice (Steensen et al.), and AI-era challenges (Cazzamatta). However, none of these papers proposes a formal evidence evaluation framework as a solution. The conversation remains analytical rather than prescriptive.
Relationship to Other Hypotheses¶
H2 is the middle ground: gap documented (unlike H3) but solutions not proposed (unlike H1). The evidence clearly supports this position.