Skip to content
DraconiticResearch
Search Sources API
206,690 studies31 sourcesUpdated 20 min ago
PreprintarXiv licencearXiv

Risk-Limiting Audits for Parliamentary Majorities

Abstract

Existing methods for risk-limiting audits typically focus on certifying individual contests. In parliamentary elections, however, the politically relevant outcome is often whether a party has won enough seats to form government, not whether every reported seat outcome is correct. Extending on the work of Mohanty et al. (2019), we formulate the certification of a parliamentary majority as a partial conjunction testing problem: it is enough to verify that the reported winning party truly won at least a majority of its reported seats. Building on the SHANGRLA auditing framework, we construct a sequential audit statistic for the majority outcome by combining seat-level statistics. We then propose adaptive sampling strategies that allocate auditing effort across seats, including variants that learn to avoid spending excessive effort on seats that appear unlikely to have been truly won. Using simulations based on synthetic and real data, from the 2014 Indian Lok Sabha election, we show that auditing the parliamentary majority can substantially reduce the number of ballots inspected (by almost a thousand-fold) compared to certifying every reported winning seat.

Versions

Related

  1. Fisher-Glass Learning: Classification Bounds and Subpopulation Audits
    El Mustapha Mansouri
    arXivPreprintCC BY 4.0Full textStatisticsarXiv
  2. Choosing an Appropriate Outlier-Detection Method When Comparing Institutional Performances in Clinical Audits.
    Anqi Sui, Gareth Ambler, Rumana Z Omar +2
    Biometrical journal. Biometrische ZeitschriftPeer-reviewedCC BYFull textStatisticsEurope PMC
  3. The geometry of AI validation: From structural blindness to reusable audits
    Ricardo Fitas
    arXivPreprintCC BY 4.0Full textStatisticsarXiv
  4. Multi-Sensitive Distributional Fairness: Joint Wasserstein Audits and Shapley Allocation
    Agathe Fernandes Machado, Charlotte Jamotton, Arthur Charpentier
    arXivPreprintCC BY-NC-ND 4.0Full textStatisticsarXiv
  5. Recovering Hidden Wildlife--Vehicle Collisions from Existing Crash Data: A Cross-State Framework for Detection, Prevalence Estimation, and Under-Reporting Audits
    Rasheed Bello, Judith Mwakalonge, Vaighese Vaidyan +4
    arXivPreprintCC BY 4.0Full textStatisticsarXiv
BibTeX
@misc{freestone2026risklimiting,
  title = {{Risk-Limiting Audits for Parliamentary Majorities}},
  author = {Jack Freestone and Dennis Leung and Damjan Vukcevic},
  howpublished = {arXiv},
  year = {2026},
  month = jul,
  doi = {10.48550/arxiv.2607.21082},
  eprint = {2607.21082},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.21082},
}
RIS
TY  - UNPB
TI  - Risk-Limiting Audits for Parliamentary Majorities
AU  - Jack Freestone
AU  - Dennis Leung
AU  - Damjan Vukcevic
PY  - 2026
DA  - 2026/07/23
PB  - arXiv
DO  - 10.48550/arxiv.2607.21082
UR  - https://arxiv.org/abs/2607.21082
AB  - Existing methods for risk-limiting audits typically focus on certifying individual contests. In parliamentary elections, however, the politically relevant outcome is often whether a party has won enough seats to form government, not whether every reported seat outcome is correct. Extending on the work of Mohanty et al. (2019), we formulate the certification of a parliamentary majority as a partial conjunction testing problem: it is enough to verify that the reported winning party truly won at least a majority of its reported seats. Building on the SHANGRLA auditing framework, we construct a sequential audit statistic for the majority outcome by combining seat-level statistics. We then propose adaptive sampling strategies that allocate auditing effort across seats, including variants that learn to avoid spending excessive effort on seats that appear unlikely to have been truly won. Using simulations based on synthetic and real data, from the 2014 Indian Lok Sabha election, we show that auditing the parliamentary majority can substantially reduce the number of ballots inspected (by almost a thousand-fold) compared to certifying every reported winning seat.
ER  -