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PreprintCC BY 4.0arXiv

The Geometry of Alliances: Vote Transfer Modelling in French Two-Round Elections

Abstract

Two-round legislative elections are decided not only by first-round vote shares, but by how voters whose preferred party did not advance redistribute their votes among the surviving candidates. We develop a principled model of this transfer process, grounded in multi-dimensional ideological embeddings derived from the Chapel Hill Expert Survey, and apply it to French legislative elections. Calibrated on the 2017 and 2022 elections, the model is evaluated on the unusually complex 2024 contest, in which three ideologically distinct blocs reached the second round simultaneously, achieving 90.34 percent constituency-level accuracy. We show that ideological proximity alone explains the large majority of vote transfers, that a simple left-right axis is insufficient to capture the relevant distances, and that the structural configuration of the 2024 electorate was far less favorable to the far right than pre-election forecasts suggested.

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BibTeX
@misc{omont2026geometry,
  title = {{The Geometry of Alliances: Vote Transfer Modelling in French Two-Round Elections}},
  author = {Emmanuel Omont},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.23734},
  eprint = {2609.23734},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.23734},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - The Geometry of Alliances: Vote Transfer Modelling in French Two-Round Elections
AU  - Emmanuel Omont
PY  - 2026
DA  - 2026/09/20
PB  - arXiv
DO  - 10.48550/arxiv.2609.23734
UR  - https://arxiv.org/abs/2609.23734
AB  - Two-round legislative elections are decided not only by first-round vote shares, but by how voters whose preferred party did not advance redistribute their votes among the surviving candidates. We develop a principled model of this transfer process, grounded in multi-dimensional ideological embeddings derived from the Chapel Hill Expert Survey, and apply it to French legislative elections. Calibrated on the 2017 and 2022 elections, the model is evaluated on the unusually complex 2024 contest, in which three ideologically distinct blocs reached the second round simultaneously, achieving 90.34 percent constituency-level accuracy. We show that ideological proximity alone explains the large majority of vote transfers, that a simple left-right axis is insufficient to capture the relevant distances, and that the structural configuration of the 2024 electorate was far less favorable to the far right than pre-election forecasts suggested.
ER  -