R0029/2026-03-27/Q001/H2¶
Statement¶
No structured attribution frameworks exist; the field has only binary disclosure requirements (used AI / did not use AI).
Status¶
Current: Eliminated
Multiple structured proposals clearly go beyond binary disclosure. The IBM AI Attribution Toolkit captures contribution type, amount, and review process. The AIA icon system proposes graduated visual indicators. The CHI 2025 research demonstrates that attribution requires granularity across multiple dimensions.
Supporting Evidence¶
No evidence supports this hypothesis. Every source examined shows work beyond binary disclosure.
Contradicting Evidence¶
| Evidence | Summary |
|---|---|
| SRC01-E01 | Research demonstrates attribution requires granularity beyond binary disclosure policies |
| SRC02-E01 | Working toolkit with structured multi-dimensional attribution |
| SRC03-E01 | Graduated icon system for AI authorship disclosure |
Reasoning¶
The evidence comprehensively eliminates this hypothesis. While many publishers still use binary disclosure (see Q003), the research community has clearly moved beyond this to propose structured, multi-dimensional attribution frameworks.
Relationship to Other Hypotheses¶
H2 represents the null hypothesis — that no structured work exists. The evidence clearly refutes this, supporting both H1 (partially) and H3 (fully).