用大模型分析200年英国议会辩论,发现反女权言论更偏激,支持者则多用温柔型歧视。
Two Centuries of Sexism in British Parliament: A Computational Analysis of Women's Representation in the Hansard Corpus
- 用大语言模型识别议员对女性参政的立场,结合性别歧视为分析框架
- 反对女性参政的演讲中54%含性别歧视,支持者仅21%,且类型不同
- 女性议员支持女性权利比例高达93%,男性为70%,差距在选举权后缩小
立法机构讨论女性权利时,即便持支持态度,其语言仍系统性地蕴含性别偏见,跨越两个世纪。本文利用大语言模型分析1803至2005年间英国议会记录(Hansard)中的6,531篇演讲,分类发言者对女性选举权及政治代表性的立场,并从“矛盾性别观量表”视角解析议会中的性别歧视话语。研究发现,54%反对女性参政的演讲包含性别歧视内容,而支持者中仅21%存在此类表述;反对派同时使用敌意与温和型性别偏见,支持者则主要表现为温和型歧视。女性议员支持女性政治权利的比例达93%,男性仅为70%,该差距仅在女性获得选举权后逐渐缩小。结果验证了矛盾性别观理论在政治话语中的适用性。
原文摘要 · Abstract (English)
The language a legislature uses to debate women's rights, even in favour of them, encodes systematic patterns of sexism that persist across two centuries. In this work, we analyse 6,531 speeches over 200 years of UK parliamentary debate (Hansard, 1803-2005) by using large language models to classify a speaker's perspective towards women's suffrage and political representation, as well as analyse sexist speech in parliament from the lens of the Ambivalent Sexism Inventory. We also release this parliamentary dataset, an organized and metadata-enriched version of the publicly available Hansard Corpus optimized for computational social science research, with 6.7 million speeches across 1.2 million debates, with 89% gender-matching for speeches by MPs from the House of Commons. We find that 54% of speeches opposing women's representation contain sexist content, compared to 21% of speeches that are for the cause, and that the two sides use fundamentally different types of sexism: anti-suffrage rhetoric combines hostile and benevolent framing, while pro-suffrage sexism is overwhelmingly benevolent. Female MPs support women's political rights at 93% compared to 70% for male MPs, a gap that closes only after enfranchisement. Our findings are evidence that benevolent and hostile sexism are used in different rhetorical contexts in a manner consistent with the theory of Ambivalent Sexism.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。