Lucas, David S.David S.LucasScheve, ClaraClaraScheveGehman, JoelJoelGehman2026-07-292026-07-292026-07-22Journal of Business Research 217: 116376 (2026)https://hdl.handle.net/11420/64108Governments worldwide have increasingly established new legal forms intended to empower and govern hybrid organizations’ dual pursuit of economic and social value. Mandatory impact reporting is a centerpiece of these legal innovations, yet little is known about how hybrid organizations navigate the often-ambiguous reporting requirements these laws stipulate. Drawing on a unique dataset of all mandatory impact reports filed from 2016 to 2024 by the population of benefit corporations incorporated in Minnesota, we introduce a novel, human-derived scale of benefit report quality, encompassing five dimensions. Developing and applying a rubric-guided LLM scoring protocol to rate each report against the scale, we find that third-party certification by B Lab increases both the length and quality of benefit reports, thereby revealing a nuanced interdependence between state and private regulation. Our study highlights the limits and possibilities of mandatory disclosure regimes within hybrid legal forms while demonstrating the potential of rubric-guided LLMs to enhance content analysis.en0148-2963Journal of business research2026ElsevierB CorporationsBenefit corporationsCertificationHybrid organizationsImpact reportingPublic policySocial Sciences::320: Political ScienceTechnology::650: Management, Public RelationsMandatory ambiguity: a hybrid human–AI analysis of impact reporting by benefit corporationsJournal Article10.1016/j.jbusres.2026.116376