  Existing research in measuring and mitigating gender bias predominantly
centers on English, overlooking the intricate challenges posed by non-English
languages and the Global South. This paper presents the first comprehensive
study delving into the nuanced landscape of gender bias in Hindi, the third
most spoken language globally. Our study employs diverse mining techniques,
computational models, field studies and sheds light on the limitations of
current methodologies. Given the challenges faced with mining gender biased
statements in Hindi using existing methods, we conducted field studies to
bootstrap the collection of such sentences. Through field studies involving
rural and low-income community women, we uncover diverse perceptions of gender
bias, underscoring the necessity for context-specific approaches. This paper
advocates for a community-centric research design, amplifying voices often
marginalized in previous studies. Our findings not only contribute to the
understanding of gender bias in Hindi but also establish a foundation for
further exploration of Indic languages. By exploring the intricacies of this
understudied context, we call for thoughtful engagement with gender bias,
promoting inclusivity and equity in linguistic and cultural contexts beyond the
Global North.
