Legal Mechanisms for Digital Content Moderation on HR Tech Platforms

This essay examines the legal mechanisms of digital content moderation on HR tech platforms as an integral element of contemporary regulation of the digital labor market. In the context of digital transformation, online platforms increasingly move beyond the role of purely technical intermediaries and assume functions of private regulation. Within this framework, content moderation becomes a key instrument shaping the legal environment of interactions between employers and job seekers. The purpose of this study is to identify the legal nature of digital moderation on HR tech platforms, to determine its place within the system of legal regulation, and to substantiate its role as a form of preventive law enforcement in a private digital environment. On a doctrinal basis, the essay examines relevant provisions of Russian law, including rules on the status and liability model of the “information intermediary,” and compares them with foreign regulatory approaches, notably the EU Digital Services Act and the United Kingdom’s Online Safety Act. The analysis is complemented by a review of platform user agreements and moderation policies, enabling the identification of operational models of pre-moderation, post-moderation, algorithmic filtering, and appeals procedures. The essay demonstrates that the introduction of specific statutory obligations for operators of online classified services transforms the traditional model of information intermediary liability and objectively requires the implementation of proactive content moderation mechanisms. It is argued that digital moderation on HR tech platforms cannot be reduced to technical filtering; rather, it constitutes a mechanism of primary legal qualification of factual circumstances, the results of which entail legal consequences for platform users. Special attention is paid to the dual legal nature of job vacancy postings, which may fall under different legal regimes depending on their content, and to algorithmic moderation adapted to the sectoral specifics of labor relations. The study further argues that the principle of full transparency of moderation decisions is not universal and, in certain contexts, may undermine the effectiveness of fraud prevention and the stability of platform ecosystems. The essay substantiates the permissibility of limited transparency models, provided that accessible appeal mechanisms and error-correction procedures are maintained. The findings of this research may be applied in the development of user agreements, internal moderation policies, and algorithmic moderation systems of HR tech platforms.

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