JOURNAL ARTICLE
Finding Gender Inequality among Indian States through the Construction of a Gender Inequality Index.
Published In: Artha Vijnana, 2024, v. 66, n. 4. P. 403 1 of 3
Database: Sociology Source Ultimate 2 of 3
Authored By: Veena, R. Senthamizh 3 of 3
Abstract
In India, gender inequality manifests in the form of socially constructed, predefined gender roles for men and women that are deeply embedded in Indian cultural and historical roots. This paper is an attempt to examine the extent of gender inequality among the states of India across the socio-economic and political spheres of the country. To this end, a Gender Inequality Index (GII) is constructed, measuring inequality in six dimensions: health and nutrition, education, Information and Communication Technology (ICT), economic participation, household empowerment, and political participation. The GII incorporates 18 parameters at the sub-national level. For constructing the GII, this study has followed the methodology adopted by UNDP in developing the Human Development Index. The results reveal that Kerala exhibits the lowest level of gender inequality among Indian states, while Bihar fares the worst. Overall, the study advocates for a multi-sectoral, holistic approach to uplift women in all states, particularly those identified as "below average performers." It emphasizes that empowering women and treating them on par with men is not an additional privilege but rather a fundamental human right and a prerequisite for a peaceful and prosperous world. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Artha Vijnana. 2024/12, Vol. 66, Issue 4, p403
- Document Type:Article
- Subject Area:Women's Studies and Feminism
- Publication Date:2024
- ISSN:0971-586X
- Accession Number:182234910
- Copyright Statement:Copyright of Artha Vijnana is the property of Gokhale Institute of Politics & Economics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.