A Diagnostic Framework for Detecting Discursive Divergence in Sustainability Communication

• Abiodun Okunola

  Ladoke Akintola University Technology

  Author

Asset managers increasingly make public commitments to carbon reduction while their portfolios remain carbon-intensive, creating an accountability gap that existing disclosure regimes do not systematically detect. This study addresses the absence of a validated framework for auditing the alignment between fund manager rhetoric and actual portfolio carbon performance. Drawing on performative theories of corporate purpose and diagnostic tools for environmental misrepresentation, this research develops a mixed-methods audit framework that pairs natural language processing of manager communications with portfolio carbon risk scores across a sample of 147 actively managed equity funds over 2022–2024. The framework classifies rhetorical claims into specificity tiers and tests their predictive correspondence with subsequent changes in weighted average carbon intensity (WACI). Results indicate that only 10.6% of fund communications contained claims that were both specific and subsequently validated by portfolio data, yielding a rhetorical–performance concordance rate of 89.4% for non-validated claims when subjected to the divergence detection algorithm. The primary predictor of divergence was the use of absolute or unqualified sustainability language without numerical targets. The study concludes that rhetorical auditing is a feasible and necessary complement to existing climate disclosure frameworks, offering regulators and investors a replicable diagnostic instrument for identifying discursive greenwashing in asset management.

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Copyright (c) 2026 Abiodun Okunola (Author)

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