This study, titled “Algorithmic Governance and the Creator Economy: Exploring Visibility and Economic Disparities with Meta‑Journalism,” investigates how algorithmic systems shape content creators’ visibility, income distribution, and public accountability across major social media platforms. Anchored in Actor‑Network Theory, which conceptualizes algorithms as non‑human actors co‑producing socio‑economic realities with creators and audiences, the research adopts a convergent mixed‑methods design with quantitative emphasis. Data were generated through platform metrics (reach, impressions, engagement), income distribution analysis, and meta‑journalistic content mining. Findings reveal a statistically significant correlation between engagement rate and income (R² ≈ 0.62), with TikTok exhibiting the steepest inequality (Gini = 0.68), where the top 10% of creators capture over 60% of revenue. Meta‑journalism frames algorithmic governance predominantly through bias (35%) and precarity (28%), underscoring its role as a reflexive actor in shaping accountability discourses. The study concludes that algorithmic governance entrenches disparities unless re‑engineered toward transparency and equity. Recommendations specify that platforms should implement visibility dashboards for creators, regulators should enforce fair monetization policies, and media organizations should diversify accountability frames. Overall, the research delivers a verdict that the sustainability of the creator economy depends on transparent, equitable, and accountable algorithmic frameworks capable of supporting diverse voices in the evolving digital landscape.