THE INTERSECTION OF FAMILY-BASED IMMIGRATION AND DOMESTIC VIOLENCE: EXAMINING VAWA SELF-PETITIONS AND THEIR ROLE IN PROTECTING VULNERABLE IMMIGRANTS

Authors

  • Dr. Gopal Krishna Sharma Institute Of Law, Jiwaji University, Gwalior. Author

Keywords:

VAWA, domestic violence, immigration law, self-petition, immigrant rights, family-based immigration, USCIS.

Abstract

This research paper explores the intersection of family-based immigration and domestic violence in the United States, focusing on the role of the Violence Against Women Act (VAWA) self-petition provisions. Family-based immigration often places noncitizen spouses, children, and parents in vulnerable positions where abusers exploit their dependency for legal status to exert control and perpetuate harm. The VAWA self-petition mechanism, introduced in 1994 and expanded through subsequent reauthorizations, enables survivors of domestic violence to independently seek lawful permanent residency without the cooperation or knowledge of their abuser. This paper critically examines the eligibility criteria, evidentiary challenges, and administrative pathways involved in the self-petition process. It highlights the legal and emotional barriers that prevent many survivors from accessing protections, including fear of deportation, lack of awareness, and difficulty in securing documentation. The paper further evaluates the effectiveness of support systems, such as legal aid and nonprofit organizations, and recommends policy interventions to enhance survivor safety and legal empowerment. Ultimately, VAWA self-petitions serve as a vital legal remedy that empowers immigrant survivors to reclaim autonomy, yet continued systemic reforms are necessary to ensure accessibility and justice for all victims of abuse within the immigration system.

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Published

2025-02-05

Issue

Section

Original Research Articles

How to Cite

THE INTERSECTION OF FAMILY-BASED IMMIGRATION AND DOMESTIC VIOLENCE: EXAMINING VAWA SELF-PETITIONS AND THEIR ROLE IN PROTECTING VULNERABLE IMMIGRANTS. (2025). International Journal of Artificial Intelligence, Computer Science, Management and Technology, 2(1), 73-84. https://ijacmt.com/index.php/j/article/view/21