| Sumario: | Content analysis is a common method in media studies, but its reliance on visual and spatial tools often excludes blind and visually impaired researchers. Drawing from personal experience as a blind media scholar, the author highlights challenges with tools like spreadsheets, coding software, and data visualizations. While assistive technologies such as screen readers and optical character recognition (OCR) have improved access to text, they are insufficient for complex datasets or visual materials. Many emerging content analysis tools, including NVivo, R, and Python libraries, lack accessibility features, hindering independent participation. The absence of institutional support and inclusive training worsens these barriers. This reflects a deeper epistemic injustice, where research tools assume sight as the norm. To promote equity, there is an urgent need for accessible-by-design technologies and structural support through communities and inclusive software development. Coding should be based on critical thinking and categorization, not visual ability. POINTS OF INTEREST: Barriers in Traditional Content Analysis – How visual assumptions in coding, spreadsheets, and software limit participation for blind researchers. Limits of Assistive Technologies – Screen readers, OCR, and AI tools improve access but remain inadequate for complex datasets and visual content. Human and Structural Costs – Increased time, isolation, and cognitive burden faced by blind researchers due to inaccessible methods. Pathways to Inclusion – Recommendations for accessible-by-design tools, institutional support, and community-building to ensure methodological justice.
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