Conflict or Strategy? Asymmetric Role Framing of La France insoumise and Rassemblement National in French News Headlines, 2022-2025

A study of 28,592 French news headlines from 2022 to 2025 found that La France insoumise (LFI) is more often framed through conflict, while Rassemblement National (RN) is more often framed through strategic-electoral terms, revealing role asymmetry rather than valence asymmetry. The analysis, conducted by researchers using a three-model LLM pipeline validated against human audits across 25 outlets, found the role gap stable across models, time, and outlet families, though normative judgments varied by outlet.

arXiv:2608.09936v1 Announce Type: new Abstract: 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.