Comparative Study of Mythological Women in the Fiction of Chitra Banerjee Divakaruni and Kavita Kane for Gender Inclusive Learning.

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Title: Comparative Study of Mythological Women in the Fiction of Chitra Banerjee Divakaruni and Kavita Kane for Gender Inclusive Learning.
Authors: R., Swathi Gudipati1 swathi.devi2011@gmail.com, S., Rajeswari2 rajishankar96@gmail.com, Sailaja Eswara3 sailu.eswara@gmail.com, Y., Raghunath Rao4 yraghunath1@gmail.com, S., Farhad5 farhad.anu21@gmail.com
Source: International Journal of Special Education. 2026 Special Issue, Vol. 41, p967-974. 8p.
Subject Terms: *Gender studies, *Authors, *Discourse analysis, Digital humanities, Narration, Goddesses
People: Divakaruni, Chitra Banerjee, 1956-
Abstract: This study develops a computationally grounded comparative framework to examine mythological female representations in the fiction of Chitra Banerjee Divakaruni and Kavita Kane, addressing a measurable gap in gender-inclusive literary pedagogy. A corpus-driven analysis integrating natural language processing, sentiment modelling, and narrative agency indexing reveals that only 28% of prior curriculum-linked studies quantify female narrative centrality. The findings indicate statistically significant differences (p < 0.05) in agency distribution, voice intensity, and resistance constructs across the two authors’ works. Divakaruni’s narratives demonstrate higher dialogic plurality, while Kane’s texts exhibit deeper internalized agency reconstruction. The study proposes a novel Gender-Inclusive Literary Analytics Model (GILAM) that operationalizes inclusivity through quantifiable discourse metrics. This model enables scalable curriculum integration, offering a replicable methodological contribution to digital humanities and gender studies, and advancing evidence-based inclusive learning design. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Special Education is the property of International Journal of Special Education 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.)
Database: Education Research Complete
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  Data: *&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Gender+studies%22&quot;&gt;Gender studies&lt;/searchLink&gt;&lt;br /&gt;*&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Authors%22&quot;&gt;Authors&lt;/searchLink&gt;&lt;br /&gt;*&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Discourse+analysis%22&quot;&gt;Discourse analysis&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Digital+humanities%22&quot;&gt;Digital humanities&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Narration%22&quot;&gt;Narration&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Goddesses%22&quot;&gt;Goddesses&lt;/searchLink&gt;
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  Data: This study develops a computationally grounded comparative framework to examine mythological female representations in the fiction of Chitra Banerjee Divakaruni and Kavita Kane, addressing a measurable gap in gender-inclusive literary pedagogy. A corpus-driven analysis integrating natural language processing, sentiment modelling, and narrative agency indexing reveals that only 28% of prior curriculum-linked studies quantify female narrative centrality. The findings indicate statistically significant differences (p &lt; 0.05) in agency distribution, voice intensity, and resistance constructs across the two authors’ works. Divakaruni’s narratives demonstrate higher dialogic plurality, while Kane’s texts exhibit deeper internalized agency reconstruction. The study proposes a novel Gender-Inclusive Literary Analytics Model (GILAM) that operationalizes inclusivity through quantifiable discourse metrics. This model enables scalable curriculum integration, offering a replicable methodological contribution to digital humanities and gender studies, and advancing evidence-based inclusive learning design. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of International Journal of Special Education is the property of International Journal of Special Education and its content may not be copied or emailed to multiple sites without the copyright holder&#39;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.&lt;/i&gt; (Copyright applies to all Abstracts.)
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      – Code: eng
        Text: English
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      – SubjectFull: Gender studies
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      – SubjectFull: Authors
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      – SubjectFull: Discourse analysis
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      – SubjectFull: Digital humanities
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      – SubjectFull: Goddesses
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      – SubjectFull: Divakaruni, Chitra Banerjee, 1956-
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      – TitleFull: Comparative Study of Mythological Women in the Fiction of Chitra Banerjee Divakaruni and Kavita Kane for Gender Inclusive Learning.
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              Text: 2026 Special Issue
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