Purpose: The study critically examines how digital platforms, often touted as democratizing forces for entrepreneurship, reinforce and intensify gendered inequalities through algorithmic oppression. It introduces the Online Patriarchy Model to explain how platform design, algorithms, and governance structures replicate and reconfigure patriarchal norms, focusing on the challenges and adaptive strategies of women entrepreneurs operating in digital economies. It also introduces the Intersectional Gender Equity Assessment Framework (IGEAF), a systemic analytical framework designed to evaluate, monitor, and reform algorithmic systems by foregrounding how gendered and intersecting inequalities are produced, sustained, or amplified through digital platforms. Methodology: Employing a mixed-methods approach, the research draws on interdisciplinary literature in digital sociology, gender studies, and platform economics, and synthesizes qualitative evidence from peer-reviewed journal articles and books, as well as a case study of the Gamergate controversy. The study develops and applies the Online Patriarchy Model and the concept of Online Patriarchal Bargains to systematically analyse the interplay between digital platforms and gendered entrepreneurial experiences. Findings: Algorithms trained on biased historical data and designed predominantly by male-dominated teams systematically disadvantage women-led ventures by limiting their visibility, access to funding, and opportunities through data-driven and structural discrimination. Women entrepreneurs respond to these constraints with resilient strategies such as performative self-presentation, algorithmic gaming, digital solidarity networks, and boundary-setting, but these acts often reinforce the gendered codes they seek to overcome. The study argues that digital entrepreneurship, despite its inclusive rhetoric, imposes new forms of emotional and invisible labor on women while demanding conformity with masculinist metrics of success. Research Implications: The research highlights the need for fundamental transformations in platform design, algorithmic auditing, and regulatory governance to address algorithmic oppression. It underscores the necessity of centering women entrepreneurs’ voices and leadership in technology development, policy, and scholarly inquiry, proposing multi-pronged interventions such as gender-aware algorithmic audits and inclusive platform governance mechanisms. Practical Implications: To overcome algorithmic oppression, platform managers and policymakers must embed gender impact assessments, enforce robust anti-harassment systems, and create mechanisms for transparent, accountable, and contestable algorithmic decisions. Tech industry practices must prioritize social justice, inclusive design, and equity over narrow efficiency and profit maximization, while also building competencies in algorithmic equity across the sector. Social Implications: The study reveals how online patriarchal bargains strategic compromises to survive in digital spaces are both symptoms of and responses to platform-mediated inequalities, resulting in heightened costs of emotional labor and self-curation for women. These dynamics not only reinforce gender hierarchies but may also limit the diversity of voices in digital economies and public discourse, calling for collective action to reimagine digital spaces as equitable, empowering environments. Originality/Value: The research makes original theoretical contributions through the Online Patriarchy Model and the Intersectional Gender Equity Assessment Framework (IGEAF). IGEAF integrates intersectionality, participatory governance, and continuous auditing across three iterative phases: pre-deployment assessment, deployment and monitoring, and post-deployment review. These phases enable the identification of allocative, representational, procedural, and emotional harms embedded within data practices, design choices, and governance structures. By combining gender-disaggregated performance metrics, stakeholder co-design, transparency and explanatory audits, and institutional accountability mechanisms, IGEAF reframes algorithmic governance as a socio-technical responsibility rather than a purely technical problem. In doing so, it demonstrates that digital systems do not merely optimise efficiency but actively shape and can be redesigned to advance equity, dignity, and inclusion.
Benu Kesar (Mon,) studied this question.