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“Scientific Bias” is a book category focused on how biases—cognitive, methodological, statistical, institutional, cultural, and financial—shape what science studies, how studies are conducted, and which findings are believed and disseminated. Titles in this genre examine incentives and structures such as funding, peer review, publication pressures, and media dynamics, exploring issues like confirmation and publication bias, p-hacking, underpowered studies, and the reproducibility crisis. They combine case studies and historical episodes with philosophy and sociology of science to show how assumptions, power dynamics, and demographics influence research questions, data interpretation, and scientific consensus. Many works also offer practical reforms and tools—preregistration, replication, open data, robust statistics, and bias mitigation—to strengthen reliability and trust. The category serves researchers, students, policymakers, and informed readers seeking to understand both the vulnerabilities and the self-correcting mechanisms of scientific practice and its impact on society and policy.

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