Logistic Regression – Based Machine Learning Model for Predicting Student Awareness of Caste, Gender and Social Inequality: An Empirical Analysis of Arundhati Roy’s writings

Abstract

The caste and gender discrimination that permeates every area, socioeconomic class hinders the development of Indian educational systems. Gender inequality also caste inside academic institutions in India is a complicated and multifaceted reality that impacts all facets of lives, such as earnings, schooling and work opportunities, in addition to physical,  societal, and financial challenges and culture. The multifaceted situation of gender and caste are common in Indian society. The analysis explores potential of intelligent system in shaping awareness out of caste, gender and social inequality using Arundhati Roy’s writing. We Propose an AI driven Frame work that integrates natural language processing techniques to analyze Roy’s works and identity themes related to social justice. The input data collected among students are preprocessed with lemmatization and TF-IDF vectorization. Features are then subjected to Correlation- based feature grouping to capture relevant patterns. A logistic regression classifier predicts the outcomes in two domains: Caste &Gender Inequality and Social Injustice in society. Comparison is made with Roy’s writing to know the awareness and impact made by her among the students.