JOURNAL ARTICLE
The Perpetuation of Muslim–Hindu Divide in British India Through the (Ab)Use of Historical Memory.
Published In: Journal of Asian & African Studies (Sage Publications, Ltd.), 2025, v. 60, n. 5. P. 3168 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Belmekki, Belkacem 3 of 3
Abstract
This article examines how historical narratives shaped the relationship between Muslims and Hindus in British India, emphasizing that the religious communalization of the 19th century was influenced significantly by colonial reinterpretations of the past and Hindu communalist activism. It highlights that prior to British rule, Muslims and Hindus had a long history of cultural intermingling despite religious differences, but colonial scholars framed Indian history in religiously polarized terms, portraying Muslim rule negatively to justify British dominance. Hindu communalists, notably proponents of Hindutva, adopted and amplified these colonial narratives to mobilize Hindu identity against Muslims, contributing to societal division. The article also discusses scholarly debates on the extent and origins of Muslim–Hindu tensions, noting that while some conflicts predated colonialism, British policies such as religion-based censuses intensified communal identities. Ultimately, it argues that the interplay of colonial historiography and communalist ideology played a central role in the eventual bifurcation of Indian society along religious lines.
Additional Information
- Source:Journal of Asian & African Studies (Sage Publications, Ltd.). 2025/08, Vol. 60, Issue 5, p3168
- Document Type:Article
- Subject Area:History
- Publication Date:2025
- ISSN:0021-9096
- DOI:10.1177/00219096241228939
- Accession Number:186747066
- Copyright Statement:Copyright of Journal of Asian & African Studies (Sage Publications, Ltd.) is the property of Sage Publications Inc. 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.)
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