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Vulnerability of democratic electoral systems

Tomasz Raducha, Jarosław Klamut, Roger Cremades, Paul Bouman, Mateusz Wiliński

Abstract

The two most common types of electoral systems (ES) used in electing national legislatures are proportional representation and plurality voting. When they are evaluated, most often the arguments come from social choice theory and political sciences. The former overall uses an axiomatic approach including a list of mathematical criteria a system should fulfill. The latter predominantly focuses on the trade-off between proportionality of apportionment and governability. However, there is no consensus on the best ES, nor on the set of indexes and measures that would be the most important in such assessment. Moreover, the ongoing debate about the fairness of national elections neglects the study of their vulnerabilities. Here we address this research gap with a framework that can measure electoral systems' vulnerability to different means of influence. Using in silico analysis we show that plurality voting systems are less stable than proportional representation. They are also more susceptible to political agitators and media propaganda. A review of real-world ES reveals possible improvements in their design leading to lower susceptibility. Additionally, our simulation framework allows computation of popular indexes, as the Gallagher index or the effective number of parties, in different scenarios. Our work provides a new tool for dealing with modern threats to democracy that could destabilize voting processes. Furthermore, our results add an important argument in a long-standing discussion on evaluation of ES.

Vulnerability of democratic electoral systems

Abstract

The two most common types of electoral systems (ES) used in electing national legislatures are proportional representation and plurality voting. When they are evaluated, most often the arguments come from social choice theory and political sciences. The former overall uses an axiomatic approach including a list of mathematical criteria a system should fulfill. The latter predominantly focuses on the trade-off between proportionality of apportionment and governability. However, there is no consensus on the best ES, nor on the set of indexes and measures that would be the most important in such assessment. Moreover, the ongoing debate about the fairness of national elections neglects the study of their vulnerabilities. Here we address this research gap with a framework that can measure electoral systems' vulnerability to different means of influence. Using in silico analysis we show that plurality voting systems are less stable than proportional representation. They are also more susceptible to political agitators and media propaganda. A review of real-world ES reveals possible improvements in their design leading to lower susceptibility. Additionally, our simulation framework allows computation of popular indexes, as the Gallagher index or the effective number of parties, in different scenarios. Our work provides a new tool for dealing with modern threats to democracy that could destabilize voting processes. Furthermore, our results add an important argument in a long-standing discussion on evaluation of ES.
Paper Structure (14 sections, 3 equations, 7 figures)

This paper contains 14 sections, 3 equations, 7 figures.

Figures (7)

  • Figure 1: Simulation of elections and basic differences between electoral systems. (a) Changes over time of the fraction of voters supporting each of 3 parties in the simulation, which directly translates into the fraction of votes. An exemplary day of election is indicated together with the fraction of votes each party would obtain on that day. (b) Vote share distribution of party $a$ obtained over 4000 simulated elections, the average fraction of votes is equal $0.332\pm0.065$. (c) Seat share distribution of party $a$ obtained in the same elections under PR (blue) and PV (red) ES. The average fraction of seats is equal $0.331\pm0.085$ for PR and $0.33\pm0.17$ for PV. (d) Histogram of the Gallagher index for the two ES, the average value is equal $0.022\pm0.011$ for PR and $0.124\pm0.058$ for PV. (e) Histogram of the effective number of parties for the two ES, the average value is equal $2.83\pm0.15$ for PR and $2.43\pm0.38$ for PV; All histograms obtained over 4000 elections. Simulations were ran for $\varepsilon=0.005$, $k=12$, $r=0.002$, $N=10^4$ divided into 100 equal communities. Each electoral district corresponding to a community has 5 seats assigned, giving 500 seats in total. See Supplementary Information Fig. S1-S3 for different ES and the Loosemore–Hanby index.
  • Figure 2: Influence of zealots on electoral outcomes. (a) Seat share distribution of the zealot party $a$ under PR (blue) and PV (red) ES for $0.26$% of zealots in the population. The solid line indicates the average fraction of seats obtained in the neutral case with no zealots (1/3), while dashed lines indicate average values of shifted distributions: $0.602\pm 0.072$ for PR and $0.845\pm0.097$ for PV. (b) The average seat share of the zealot party $a$ vs percentage of zealots in the population for three ES: PV, PR, and PR-G. The colored shade indicates results within one standard deviation from the average. The dashed line marks the average fraction of seats obtained with no zealots (1/3). (c) The average value of the Gallagher index vs percentage of zealots in the population for the three ES. (d) The average value of the effective number of parties vs percentage of zealots in the population for the three ES; All results obtained over 500 elections with $N=10^4$, $q=100$, $qs=5$, $k=12$, $r=0.002$, $\varepsilon=0.005$, and $n=3$ parties. See Supplementary Information Fig. S12 and S13 for other values.
  • Figure 3: Influence of biased media on electoral outcomes. (a) Seat share distribution of the media party $a$ under PR (blue) and PV (red) ES for a media bias of $0.27$. The solid line indicates the average fraction of seats obtained in the case of neutral media (1/3), while dashed lines indicate average values of shifted distributions: $0.558\pm0.088$ for PR and $0.77\pm0.14$ for PV. (b) The average seat share of the media party $a$ vs media bias for three ES: PV, PR, and PR-G. The colored shade indicates results within one standard deviation from the average. The vertical dashed line indicates the simulation with neutral media, and the horizontal one marks the average fraction of seats obtained that case (1/3). (c) The average value of the Gallagher index vs media bias for the three ES. (d) The average value of the effective number of parties vs media bias for the three ES; All results obtained over 1000 elections with $N=10^4$, $q=100$, $qs=5$, $k=12$, $r=0.002$, $\varepsilon=0.005$, and $n=3$ parties. See Supplementary Information Fig. S14 and S15 for other values.
  • Figure 4: Constructing a network for simulations of the Poland's Sejm. (a) Map of Poland with division into 16 voivodeships, i.e. the biggest administrative districts of the country. The capital of each of 41 electoral districts applied in elections to the Sejm is indicated with a colored marker. (b) Network of $41 \times 10^3$ nodes generated for simulations of elections to the Poland's Sejm. Nodes are centered around the capital of the constituency. The bigger the population of a constituency, the more spread are the nodes.
  • Figure 5: Influence of zealots and biased media on the elections to the Poland's Sejm. (a) The average seat share of the zealot party $a$ vs percentage of zealots in the population for the five considered ES. The colored shade indicates results within one standard deviation from the average. The dashed line marks the average fraction of seats obtained with no zealots (1/5). (b) The average value of the Gallagher index vs percentage of zealots in the population for the five ES. (c) The average value of the effective number of parties vs percentage of zealots in the population for the five ES; All results with zealots were obtained over 200 elections. (d) The average seat share of the media party $a$ vs media bias for the five considered ES. The vertical dashed line indicates the simulation with neutral media, and the horizontal one marks the average fraction of seats obtained that case (1/5). (e) The average value of the Gallagher index vs media bias for the five ES. (f) The average value of the effective number of parties vs media bias for the five ES; All results with media bias were obtained over 1000 elections. The network has $41 \times 10^3$ nodes, with the average degree $k=12$, divided into 41 communities corresponding to the actual electoral districts. There is 460 seats to gain in total, $n=5$ parties, and the noise rate $\varepsilon=0.002$. See Supplementary Information Fig. S16-S18 for more details and results for the Poland's Sejm.
  • ...and 2 more figures