发表机构
Le French News Lab（法国新闻实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究分析2022-2025年法国25家媒体28592条头条，发现新闻对LFI和RN的角色框架不对称，建立分层可靠性框架校准LLM政治文本标注流水线。
AI 中文摘要
法国新闻头条是将左翼民粹主义挑战者和右翼民粹主义挑战者框定为对称的“极端分子”，还是根本不同的政治对手？我们研究了2022年至2025年间25家法语媒体发布的28592条关于不屈法国（La France insoumise，LFI）和国民联盟（Rassemblement National，RN）的头条新闻，这些头条通过一个三层大语言模型（LLM）流水线进行标注，该流水线已通过分层人工审计验证。最明确的发现是角色不对称而非效价不对称：冲突框架和战略博弈框架在所有模型和时间范围内比非合法化框架更稳定，“侵略者（AGGRESSOR）”充当佐证角色句法。LFI在头条中更多通过冲突语域出现，而RN则更多通过战略选举语域出现。这种角色差距在所有三个标注模型中方向稳定，通过自举和置换检验，且在所有媒体家族及2022-2025年的大部分时间内持续存在。次要的道德核算层（谁被指责、被合法化或被塑造成受害者）由媒体而非政党构建，产生的总体零效应掩盖了语料库中一些最两极分化的模式。在方法上，该标注流水线呈现出两层可靠性特征：冲突和战略博弈框架实现最强的人工验证和跨模型稳定性；行动者角色方向稳定但被视为佐证，因为其审计可靠性较低；规范判断结构（合法性、指责）较弱。本文将政治角色分配作为计算框架研究的目标，该研究可分解基于效价的测量所混淆的内容，并建立了一个分层可靠性框架，用于校准政治文本任务中的多数投票LLM标注流水线。
英文摘要
Do French news headlines frame left- and right-populist challengers as symmetric ``extremes,'' or as fundamentally different political adversaries? We examine 28,592 headlines about La France insoumise (LFI) and Rassemblement National (RN) published by 25 French-language outlets between 2022 and 2025, annotated through a three-model LLM pipeline validated against a stratified human audit. The clearest finding is role asymmetry rather than valence asymmetry: conflict framing and strategic-game framing are more robust across models and time than delegitimization, with AGGRESSOR serving as corroborating role syntax. LFI appears in headlines more often through a conflict register and RN through a strategic-electoral register. This role gap is direction-stable across all three annotation models, survives bootstrapping and permutation tests, and persists across outlet families and most of 2022-2025. A secondary moral-accounting layer (who is blamed, legitimized, or cast as a victim) is structured by outlet rather than party, producing aggregate nulls that conceal some of the corpus's most polarized patterns. Methodologically, the annotation pipeline reveals a two-tier reliability profile: conflict and strategic-game framing achieve the strongest human validation and cross-model stability; actor role is direction-stable but treated as corroborating because its audit reliability is lower; normative-judgment constructs (legitimacy, blame) are weaker. The paper contributes political-role assignment as a target for computational framing research that decomposes what valence-based measures conflate, and establishes a construct-stratified reliability framework for calibrating majority-vote LLM annotation pipelines in political text tasks.
Comments19 pages, 3 figures, includes appendices
