Consensus simulation for in-person voting

Megan E Kern¹, Catherine J Mohr², Natalie Mohr³, Paul Mohrª

Institutional email: catherine.mohr@intu-surg.com
Permanent email: catherine.mohr@gmail.com

¹Laurel Studio, Portland, ME
²Intuitive Foundation, Sunnyvale, CA
³University of …
ªMohr Consulting LLC

Abstract

Intended Audience

The target audience for this work are professionals familiar with nominal group techniques, voting theory, and intelligence analysis. We have made the complete Matlab code available on github. Here you can reproduce our results and make use of these scripts in your own work.

Peer Review status

Pre-print published October 9, 2024 (This article is not yet peer reviewed)

Cite as: Kern ME, Mohr N, Mohr P, Mohr C. Consensus Simulation for In-Person Group Voting. [Online].; 2024. Available from: https://www.intuitive-foundation.org/self/consensus-simulation/.

Introduction

Results

Discussion

Acknowledgements

The authors would like to thank the Intuitive Foundation, Sunnyvale, CA and Laurel Studio, Portland, ME for funding this work.

Appendix

All code is available on github.

References

  1. Johnson MD, Awtrey E, Ong WJ. Verdicts, elections, and counterterrorism: When teams take unofficial votes. Academy of Management Discoveries. 2023 Dec; 9(4): p. 429–439, https://doi.org/10.5465/amd.2021.0099. 
  2. Heuer RJ, Pherson RH. Structured analytic techniques for intellegence analysis Press C, editor. Thousand Oaks, CA: Sage; 2021. 
  3. Diamond IR, Grant RC, Feldman BM, Pencharz PB, Ling SC, Moore AM. Defining consensus: a systematic review recommends methodologic criteria from reporting Delphi studies. Journal of Clinical Epidemiology. 2014 April; 67(4): p. 401-9.