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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.11752 |
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| _version_ | 1866909149102604288 |
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| author | Sankaran, Aditya Narayan Shankaran, Vigneshwaran Lonka, Sampath Sharma, Rajesh |
| author_facet | Sankaran, Aditya Narayan Shankaran, Vigneshwaran Lonka, Sampath Sharma, Rajesh |
| contents | Rhymes and poems are a powerful medium for transmitting cultural norms and societal roles. However, the pervasive existence of gender stereotypes in these works perpetuates biased perceptions and limits the scope of individuals' identities. Past works have shown that stereotyping and prejudice emerge in early childhood, and developmental research on causal mechanisms is critical for understanding and controlling stereotyping and prejudice. This work contributes by gathering a dataset of rhymes and poems to identify gender stereotypes and propose a model with 97% accuracy to identify gender bias. Gender stereotypes were rectified using a Large Language Model (LLM) and its effectiveness was evaluated in a comparative survey against human educator rectifications. To summarize, this work highlights the pervasive nature of gender stereotypes in literary works and reveals the potential of LLMs to rectify gender stereotypes. This study raises awareness and promotes inclusivity within artistic expressions, making a significant contribution to the discourse on gender equality. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_11752 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Revisiting The Classics: A Study on Identifying and Rectifying Gender Stereotypes in Rhymes and Poems Sankaran, Aditya Narayan Shankaran, Vigneshwaran Lonka, Sampath Sharma, Rajesh Computation and Language Rhymes and poems are a powerful medium for transmitting cultural norms and societal roles. However, the pervasive existence of gender stereotypes in these works perpetuates biased perceptions and limits the scope of individuals' identities. Past works have shown that stereotyping and prejudice emerge in early childhood, and developmental research on causal mechanisms is critical for understanding and controlling stereotyping and prejudice. This work contributes by gathering a dataset of rhymes and poems to identify gender stereotypes and propose a model with 97% accuracy to identify gender bias. Gender stereotypes were rectified using a Large Language Model (LLM) and its effectiveness was evaluated in a comparative survey against human educator rectifications. To summarize, this work highlights the pervasive nature of gender stereotypes in literary works and reveals the potential of LLMs to rectify gender stereotypes. This study raises awareness and promotes inclusivity within artistic expressions, making a significant contribution to the discourse on gender equality. |
| title | Revisiting The Classics: A Study on Identifying and Rectifying Gender Stereotypes in Rhymes and Poems |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2403.11752 |