检测气候话语中的宗教语言
Detecting Religious Language in Climate Discourse
AI总结：
本研究提出基于规则和零样本大语言模型的双重方法，检测气候话语中的显性和隐性宗教语言，发现规则方法标记更多宗教句子，揭示宗教语言定义中词汇与语境的张力。
摘要：
宗教语言持续渗透当代话语，即使在环境行动主义和气候变化辩论等表面世俗的领域也是如此。本文研究了世俗和宗教非政府组织（NGOs）所产出的气候相关文本中，显性和隐性宗教语言的出现方式。我们引入了一种双重方法论：一种基于规则的方法，使用源自生态神学文献的宗教术语层级树，以及在大语言模型（LLMs）在零样本设置下运行。利用一个包含超过880,000个句子的数据集，我们比较了这些方法如何检测宗教语言，并分析了它们的一致点和分歧点。结果表明，基于规则的方法始终比LLMs将更多句子标记为宗教性。这些发现不仅突显了计算检测宗教语言的方法论挑战，还揭示了关于宗教语言应仅由词汇还是上下文意义来定义的更广泛张力。本研究通过展示分析神圣性如何在气候话语中持续存在的方法的潜力和局限性，为宗教研究中的数字方法做出了贡献。
英文摘要：
Religious language continues to permeate contemporary discourse, even in ostensibly secular domains such as environmental activism and climate change debates. This paper investigates how explicit and implicit forms of religious language appear in climate-related texts produced by secular and religious nongovernmental organizations (NGOs). We introduce a dual methodological approach: a rule-based model using a hierarchical tree of religious terms derived from ecotheology literature, and large language models (LLMs) operating in a zero-shot setting. Using a dataset of more than 880,000 sentences, we compare how these methods detect religious language and analyze points of agreement and divergence. The results show that the rule-based method consistently labels more sentences as religious than LLMs. These findings highlight not only the methodological challenges of computationally detecting religious language but also the broader tension over whether religious language should be defined by vocabulary alone or by contextual meaning. This study contributes to digital methods in religious studies by demonstrating both the potential and the limitations of approaches for analyzing how the sacred persists in climate discourse.
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