The phenomenon of 'value extraction' in Open Access.

Abstract

Background: Open Access (OA) agreements were introduced to remove financial barriers to scientific dissemination and promote equity in knowledge access. As Article Processing Charges (APCs) have shifted from individual researchers to institutions, access to OA publishing has become an institutional asset, unevenly distributed across institutions, countries, and career stages.

Purpose: This article introduces and defines value extraction in OA - the use of access to APC coverage as leverage to obtain authorship or corresponding authorship without proportional intellectual contribution - and examines it as a structurally enabled integrity risk distinct from previously described forms of authorship abuse.

Approach: We conduct a conceptual and normative analysis of the mechanisms by which OA agreements interact with metric-driven academic evaluation systems and existing research integrity frameworks, identifying governance gaps and distributional inequities produced by these interactions.

Findings: Value extraction in OA is enabled by the convergence of three factors: centralized APC control within institutions, performance metrics that privilege publication counts and corresponding authorship, and integrity frameworks that treat publishing infrastructure as an ethically neutral background condition. Researchers at less-resourced institutions, early-career researchers, and scholars in the Global South face heightened vulnerability. Existing authorship guidelines fail to address mechanisms in which infrastructural access - rather than hierarchy or prestige - functions as leverage for academic credit.

Conclusions: Safeguards are needed at institutional, publisher, and systemic levels, including procedural firewalls between APC decisions and authorship documentation, publisher-level monitoring of authorship patterns, and reform of evaluation frameworks to decouple infrastructural access from academic credit. Future research should investigate the prevalence of value extraction using bibliometric and network-based screening approaches.