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Score voting

![Electoral-systems-gears.svg.png][float-right] Score voting, also known as range voting, is a cardinal electoral system for selecting winners in single-winner elections, wherein each voter assigns an independent numerical score to every candidate, typically from 0 (worst) to a fixed maximum such as 5 or 10 (best), with the candidate receiving the highest sum or average of scores declared the winner. Unlike ordinal systems like plurality or ranked-choice voting, score voting elicits the intensity of voter preferences, allowing for more granular expression of support or opposition. Proponents argue that score voting outperforms traditional methods in aggregating voter utilities by minimizing incentives for insincere voting under certain assumptions, though empirical implementations remain limited, primarily in non-governmental contexts such as organizational decisions or experimental simulations rather than large-scale public elections. It satisfies criteria like independence of irrelevant alternatives in theory but can encourage tactical exaggeration of scores to influence outcomes, a vulnerability shared with other systems yet amplified by its continuous scale. Distinct from cumulative voting, where voters allocate a fixed pool of points across candidates, score voting permits unbounded per-candidate ratings without total constraints, enabling fuller preference revelation. While score voting has been analyzed in academic literature for its potential to elect candidates closer to utilitarian optima—maximizing total voter satisfaction—real-world adoption is sparse, with examples including niche applications in participatory budgeting and online communities, but no widespread governmental use due to concerns over ballot complexity and strategic manipulation. Simulations suggest it reduces spoiler effects compared to plurality voting, yet lacks the Condorcet guarantee of pairwise majorities, highlighting trade-offs in criteria satisfaction that favor expressiveness over pairwise dominance.

Definition and Mechanics

Ballot Design and Voter Input

In score voting, ballots list all candidates vertically, with an adjacent rating scale for each, enabling voters to assign independent numerical scores reflecting preference intensity. Scales commonly range from 0 (minimal or no support) to 5 (strong support), leveraging familiarity from consumer rating systems like stars, or extend to 0-10 for additional granularity without excessive complexity. Wider ranges, such as 0-9 or 0-99, permit finer distinctions but risk voter fatigue or inconsistent usage, as empirical simulations indicate diminishing returns beyond 0-10 for preference expression accuracy. Paper ballots typically feature bubble grids or blank fields beside each candidate for marking scores via pencil, with optical scan variants using pre-printed rows of score options (e.g., columns labeled 0 through 9) that voters fill or punch to indicate selection. Mechanical or punch-card systems adapt similarly, with levers or perforations aligned to score positions, ensuring compatibility with existing infrastructure while minimizing invalid ballots through clear labeling. Electronic interfaces, such as touchscreens, employ sliders, dropdowns, or segmented bars for score input, often defaulting unrated candidates to 0 to simplify completion. Voters input scores by assessing candidates individually, awarding higher values to those deemed more meritorious without mandatory ranking or pairwise comparisons, which facilitates honest cardinal evaluations over strategic ordinal trade-offs. Some designs include a "no opinion" marker (e.g., "X"), treated as the minimum score or excluded in aggregation to avoid penalizing abstention on unfamiliar options. This input method empirically reduces vote wastage compared to plurality systems, as voters can support multiple candidates proportionally, though strategic exaggeration remains possible if voters anticipate others' score distributions.

Aggregation and Winner Determination

In score voting, voter scores for each candidate are aggregated by computing the sum of ratings assigned across all ballots, with unrated candidates implicitly receiving the minimum score (typically zero) from that ballot. The candidate achieving the highest total score is selected as the winner, a process that directly operationalizes utilitarian aggregation by maximizing the collective numerical expression of preferences. This summation method assumes scores reflect comparable intensities of support, enabling the system to account for both the breadth and strength of voter approval, unlike rank-based systems that discard magnitude information. Computationally, aggregation requires tallying scores in linear time relative to the product of voters and candidates, making it scalable for large electorates via simple addition without iterative pairwise comparisons. While sums are the standard for winner determination, some implementations compute averages to mitigate biases from incomplete ballots or varying participation rates, though rankings remain identical when all voters evaluate all options. In multi-candidate contests, normalization (e.g., dividing by the maximum possible score per ballot) can prevent scale inflation, but unnormalized sums suffice for relative comparisons. Ties, occurring when totals match, are resolved by predefined rules such as random selection, auxiliary plurality tallies, or runoff mechanisms, ensuring a determinate outcome without altering core aggregation. Empirical simulations indicate this method resists strategic exaggeration under honest voting assumptions, as over-scoring one candidate depletes resources for others on bounded scales.

Historical Development

Pre-20th Century Precursors

In the Republic of Venice, the election of the Doge from 1268 to 1797 featured a multi-stage process culminating in a scoring mechanism by 41 selected electors. Following nominations from this group, each elector assigned scores of +1, 0, or -1 to candidates on secret ballots, with totals aggregated to identify the winner, who required at least 25 net positive votes to prevail. This range-3 variant aimed to balance elite input against factional dominance, incorporating randomization via lots in prior stages to select participants and nominees. The procedure, formalized after the 1268 constitutional reforms to curb oligarchic intrigue following the controversial election of Doge Raimondo of San Polo, endured through the republic's dissolution by Napoleon in 1797, yielding 120 Doges. Voting theory analyses interpret this final ballot as an early implementation of score aggregation, where electors expressed nuanced support or opposition across options rather than selecting a single preference. Earlier analogs appear in ancient Sparta's selection of Gerousia members (circa 700–371 BCE), where candidates over age 60 were presented sequentially to the assembly, which approved via acclamatory shouting; magistrates judged shout volume to rank support, filling 28 seats iteratively. This intensity-based endorsement, described in Plutarch's Life of Lycurgus, functioned as a binary-to-graded approval proxy but lacked explicit numerical scales, distinguishing it from formalized score voting while prefiguring multi-candidate evaluation. No evidence indicates widespread pre-Hellenistic use of direct scoring in public elections, with most ancient systems relying on pebbles, shouts, or plurality counts.

20th and 21st Century Formalization

In the mid-20th century, score voting gained theoretical traction within social choice theory as a cardinal method capable of addressing limitations of ordinal preference aggregation exposed by Kenneth Arrow's 1951 impossibility theorem, which demonstrated that no non-dictatorial social welfare function could satisfy unanimity, independence of irrelevant alternatives, and non-dictatorship when restricted to ordinal rankings. John C. Harsanyi contended in the early 1950s that Arrow's result did not extend to systems incorporating cardinal utilities, where voters express preference intensities via numerical scores, allowing utilitarian summation to produce collective outcomes without violating the specified axioms. This perspective aligned score voting with Benthamite utilitarianism, formalized mathematically as the aggregation of voter-assigned real-valued utilities (or discretized scores) to maximize total welfare, though interpersonal utility comparisons remained debated. By the late 20th century, related cardinal systems received rigorous analysis, with approval voting—a special case of score voting using binary (0-1) scores—formalized as a practical alternative to plurality and runoff methods. Steven J. Brams and Peter C. Fishburn's 1983 monograph Approval Voting provided axiomatic foundations, proving its satisfaction of properties like monotonicity and positivity under sincere voting, while empirical simulations showed reduced spoiler effects compared to single-mark plurality; the authors extended these insights to broader scoring rules where voters assign integer scores from a fixed range. Concurrently, Peter C. Fishburn explored additive voting procedures in papers such as his 1974 analysis of weighted scoring systems, deriving conditions under which summed scores elect majority-preferred alternatives with high probability under impartial culture assumptions. In the 21st century, computational advances enabled quantitative evaluations of score voting's performance. Warren D. Smith introduced Bayesian regret metrics in 1999–2000, simulating millions of elections under probabilistic voter preference models (e.g., impartial culture and spatial distributions) to compare systems; score voting exhibited the lowest average regret—defined as the expected utility loss relative to the optimal winner—outperforming Condorcet, Borda, and approval methods across diverse scenarios with 3–25 candidates. Smith's framework formalized score voting (termed range voting) with discrete scales (e.g., 0–9 or 0–99), normalizing scores to mitigate strategic exaggeration while preserving expressiveness; these results were disseminated via RangeVoting.org, founded with Jan Kok in 2005, which also proposed adaptations for existing optical-scan machines using approval-style ballots with score granularity. Further theoretical work, such as Claude Hillinger's 2004 advocacy for utilitarian voting, reinforced score aggregation's alignment with economic rationality by incorporating preference intensities absent in ordinal systems. These developments positioned score voting as strategically robust, with equilibrium strategies converging to honest score assignment under large electorates, though vulnerable to tactical compression in finite discrete ranges.

Applications

Political Elections

Historical Implementations

Score voting has not been documented as a formal method in historical political elections. Proponents occasionally cite ancient systems, such as the selection processes in Sparta, where elders may have evaluated candidates through comparative assessments akin to ratings, or the multi-stage elections for the Doge in the Venetian Republic (1268–1797), which involved approval-like mechanisms among electors to prevent factional dominance. However, these processes relied on nominations, lotteries, supermajority approvals, and binary votes rather than independent numerical scores for each candidate, diverging from modern score voting definitions. No verified pre-20th-century political election aggregated scores across a full slate of candidates to determine winners via summation or averaging.

Modern and Experimental Uses

Score voting remains largely experimental in political contexts, with no widespread adoption in governmental elections as of 2025. A key trial occurred during the first round of the 2012 French presidential election on April 22, when 2,340 voters at select polling stations participated in an in-situ experiment using "evaluative voting," grading 10 candidates on a 0–20 scale, with the winner determined by total scores. This parallel vote alongside the official two-round system showed François Hollande winning under both methods, but with different margins and rankings for fringe candidates, highlighting score voting's potential to reduce strategic incentives compared to plurality. The experiment, conducted by researchers from institutions including the Paris School of Economics, demonstrated feasible ballot implementation but noted challenges like scale exhaustion, where 15–20% of grades were zero across candidates. Despite advocacy from groups like the Center for Election Science, no sovereign or major subnational jurisdiction has enacted score voting for public office. Proposals have surfaced in U.S. cities and states, often conflated with approval voting (a 0–1 variant), but rejections, such as Seattle's 2022 ballot measure favoring ranked-choice over approval, indicate resistance amid debates on complexity and voter education. Experimental simulations and academic trials continue, but implementation lags due to entrenched plurality systems and concerns over ballot design clarity.

Historical Implementations

Score voting, in its modern form requiring voters to assign numerical scores across a range to multiple candidates, has not been implemented in any governmental political elections throughout history. Proponents occasionally cite ancient precedents as precursors, but these involved binary approval or acclamation rather than granular scoring. For example, in ancient Sparta around the 8th to 4th centuries BCE, selection of elders for the Gerousia relied on acclamation by shouting in assembly, where the volume of support for nominees determined winners—a process akin to collective approval voting but lacking numerical differentiation. The Republic of Venice employed a multi-stage electoral system for choosing the Doge from the 7th to 18th centuries CE, culminating in votes by a Great Council where electors could approve up to a limited number of nominees from a shortlist, effectively a capped approval mechanism to prevent factional dominance. This evolved after 1268 CE to include safeguards against oligarchic capture, but participants voted yes/no per candidate without assigning varied scores. No records indicate adoption of full score voting in subsequent eras, such as during Enlightenment reforms or 19th-20th century electoral experiments, where plurality, runoff, or early ranked systems predominated. Public elections worldwide have favored methods like first-past-the-post or proportional representation, with score voting confined to theoretical advocacy, simulations, and non-governmental applications.

Modern and Experimental Uses

An in situ experiment during the first round of the 2012 French presidential election on April 22 tested evaluative voting, a form of score voting where participants rated candidates on scales such as 0-1, -1/0/1, 0/1/2, or 0-20, with winners determined by aggregated scores. Conducted across polling stations in Saint-Étienne, Louvigny, and Strasbourg, it involved 2,340 participants from 4,319 invited voters, with results weighted to approximate national turnout demographics for comparison against the official plurality outcomes. Key findings revealed scale-dependent voter behavior: negative grades on ternary scales like -1/0/1 inflated scores for fringe candidates (e.g., +321% for Jacques Cheminade) compared to non-negative scales, while longer scales like 0-20 showed similar rankings to shorter positive ones but increased ballot complexity. Evaluative voting shifted rankings toward "inclusive" candidates with broad appeal over "exclusive" ones polarizing support, altering positions such as Marine Le Pen dropping from 5th to 8th on certain scales, though inconsistencies with official results ranged from 3.41% to 8.9% across sites. No evidence of widespread strategic manipulation emerged, but the method highlighted how score aggregation rewards utilitarian preferences over plurality's winner-take-all dynamic. Beyond this trial, score voting lacks formal adoption in sovereign political elections, with subsequent research confined to laboratory simulations or theoretical modeling rather than binding implementations. Experimental data from the 2012 study underscore potential for reduced extremism in outcomes but also sensitivity to scale design, informing advocacy for pilot programs in lower-stakes contests.

Non-Political Contexts

Score voting has been applied in various organizational settings for collective decision-making, such as selecting leisure activities or prioritizing tasks in agile teams. In a 2017 study, researchers developed a group decision support system called LetsDoIt, which incorporated range voting—allowing participants to assign scores from 0 to 5 to proposed leisure options—to facilitate choices among friends or small groups based on social network preferences. Similarly, in agile software development environments, range voting enables team members to score multiple options for project decisions, distributing points across proposals to reflect intensity of preference and aggregate toward consensus without exhaustive discussion.

Organizational and Online Voting

In decentralized autonomous organizations (DAOs), score voting variants, including range voting, support governance by letting token holders assign numerical scores to proposals, enabling nuanced expression of support for resource allocation or protocol changes in blockchain-based entities. These systems aggregate scores to determine outcomes, often integrated into platforms for quadratic or token-weighted voting hybrids, though pure score implementations emphasize cardinal preferences over binary approval. Group decision tools have also employed score voting for non-hierarchical choices, such as rating alternatives in collaborative expert systems where participants score options within a range to inform consensus under uncertainty.

Academic and Simulation-Based Trials

Academic research frequently employs simulations to evaluate score voting's properties in controlled, non-political scenarios, generating synthetic voter preferences to test outcomes against criteria like strategic vulnerability or expressiveness. A 2025 Carnegie Mellon University study simulated score voting alongside ranked systems using Monte Carlo methods on diverse preference distributions, finding it resilient to certain paradoxes in hypothetical multi-option selections. Similarly, simulations in voting procedure assessments model collective choice profiles—such as uniform or clustered utilities—to compare score aggregation's efficiency in revealing social utilities, demonstrating advantages in scenarios with expressive ballots over ordinal methods. These trials, often using probabilistic models of evaluations, highlight score voting's capacity to minimize regret in abstract decision environments, though results vary with assumed voter independence.

Organizational and Online Voting

PollUnit, an online polling platform launched around 2015, supports range voting (a form of score voting) for organizational and community decision-making, allowing participants to assign numerical scores or star ratings to options within a predefined interval, such as 0 to 5 or 1 to 10. This feature aggregates scores by averaging to identify preferred choices, making it suitable for non-binding votes on proposals, task prioritization, or content evaluation in virtual teams, associations, or online forums. For example, organizations use it to rate ideas for workshops, distribute tasks among members, or conduct photo contests where entries receive scored feedback without requiring voter registration. In organizational contexts, score voting via such platforms enables nuanced preference expression, contrasting with binary yes/no polls by quantifying support intensity, which aids in selecting initiatives or resources in collaborative environments like non-profits or remote workgroups. PollUnit's implementation includes real-time visualization of results through diagrams and tables, facilitating transparent aggregation for groups up to 20 participants on free accounts, with premium options for larger scales. Adoption remains niche, primarily in informal or experimental settings rather than formal corporate boards, where traditional plurality or consensus methods predominate. Online communities leverage score voting for scalable input on diverse topics, such as rating event dates or free-text suggestions, with PollUnit's tools supporting anonymous or registered participation to encourage broad engagement. This approach mitigates issues like vote splitting seen in ranked systems, as voters can score multiple options independently, promoting sincere expression in decentralized groups. While platforms like PollUnit demonstrate practical utility, broader institutional use in organizations is limited, often confined to ad-hoc polls rather than governance structures.

Academic and Simulation-Based Trials

In computer simulations assessing voting methods via Bayesian regret—a metric quantifying expected societal utility loss from suboptimal winners—score voting demonstrated superior performance. Simulations from 1999–2000 evaluated roughly 30 methods across 720 scenarios, varying factors such as voter counts (from dozens to millions), candidate numbers (3–25), utility generators (impartial culture, spatial models), and voter behaviors (honest, strategic, or mixed). Score voting yielded the lowest average Bayesian regret under both honest and strategic assumptions, outperforming alternatives like plurality, approval, Borda count, and instant-runoff voting, while exhibiting robustness to parameter changes and no bias toward centrist or extremist candidates. Theoretical extensions in the random normal election model and YN model further substantiate these findings, proving score voting's Bayesian regret inferior to all rank-order methods for any honest-strategic voter ratio, as utilities aggregate additively to maximize expected welfare. Empirical simulations on large-scale rating datasets, such as Yahoo users' scores for thousands of musical artists, treat ratings as score votes and compare outcomes to plurality, Borda, and approval variants; range (score) voting showed low manipulation susceptibility in coalitional settings and effective utility capture from nuanced preferences. These models highlight score voting's capacity to elicit expressive cardinal information, though real-world strategic deviations remain a tested variable in controlled scenarios.

Illustrative Examples

Simple Ballot Scenario

In score voting, a simple ballot presents a list of candidates alongside a discrete numerical scale, commonly ranging from 0 (indicating no support or opposition) to 5 (indicating maximum support), though scales up to 99 or 10 are also used in theoretical models and some implementations. Voters independently assign a score to each candidate without ranking requirement, enabling expression of preference intensities rather than ordinal comparisons. Consider a hypothetical single-seat election with three candidates—Alice, Bob, and Charlie—and five voters using a 0-5 scale. Voter 1, strongly favoring Alice but disliking Charlie, might score Alice 5, Bob 2, and Charlie 0. Voter 2, preferring Bob moderately and neutral on others, could score Alice 1, Bob 4, and Charlie 1. Such ballots aggregate by summing scores (or computing averages after normalization), with the candidate achieving the highest total declared the winner; for instance, if totals yield Alice 18, Bob 15, and Charlie 5 across all voters, Alice wins. This format contrasts with plurality voting, where voters select only one candidate, potentially underrepresenting nuanced preferences; in the same scenario under plurality, outcomes might favor a centrist or plurality holder despite lower overall support intensities. Empirical simulations of small-scale elections demonstrate that score aggregation better approximates utilitarian outcomes by weighting intensities, though real-world ballot design must account for voter comprehension to minimize errors like uniform scoring.

Multi-Candidate Election Outcome

In score voting applied to multi-candidate elections, voters independently score each candidate on a predefined numerical scale, such as 0 to 5, where higher numbers indicate greater preference or perceived utility. The outcome is determined by calculating the total score for each candidate as the sum of all individual scores received; the candidate with the highest total score wins, with ties resolved by predefined rules such as lotteries or auxiliary criteria like score variance. Alternatively, average scores may be used, which yields equivalent rankings after normalization by the number of voters. This aggregation captures the intensity of support across the electorate, favoring candidates who elicit positive scores from a wide base rather than maximal scores from a narrow one. Unlike plurality voting, where vote splitting among similar candidates can favor less-preferred options, score voting mitigates such effects by allowing voters to differentiate degrees of preference without strategic abstention from scoring competitors. Simulations indicate that in multi-candidate fields, this can elevate utilitarian optima—candidates maximizing aggregate satisfaction—over Condorcet winners in scenarios with dispersed preferences. Consider a hypothetical election with three candidates (A, B, C) and 100 voters divided into preference groups, illustrating a typical tally:
GroupVotersScores (A, B, C)
Pro-A40(5, 0, 0)
Pro-B moderate35(3, 5, 1)
Pro-C25(0, 2, 5)
Candidate A totals 40×5 + 35×3 + 25×0 = 200 + 105 + 0 = 305. Candidate B totals 40×0 + 35×5 + 25×2 = 0 + 175 + 50 = 225. Candidate C totals 40×0 + 35×1 + 25×5 = 0 + 35 + 125 = 160. Thus, A wins despite B receiving lukewarm support from more voters overall, as A's intense backing yields the highest sum. Such outcomes highlight score voting's emphasis on total utility, though critics note potential vulnerability to strategic exaggeration in polarized fields. In practice, implementations often normalize for blank scores (e.g., treating unrated candidates as 0) to prevent bias toward evaluated options, and software tallies ensure precision in large electorates. Empirical trials, such as organizational polls, show multi-candidate score outcomes converging on broadly acceptable winners when sincere scoring predominates.

Theoretical Properties

Satisfaction of Key Criteria

Score voting satisfies several fundamental criteria in voting theory, including monotonicity, under which increasing support for a candidate—via higher scores from additional voters or upgrades from existing ones—cannot cause that candidate to lose or another to win in their place. This property holds because scores are additive, ensuring that elevating a candidate's aggregate score preserves or improves their relative standing. Similarly, score voting complies with the participation criterion, as abstaining cannot yield a better outcome for a voter than submitting a sincere ballot; added ballots either boost preferred candidates or leave rankings unchanged. The system also adheres to Pareto efficiency, electing a candidate who is Pareto-dominated only if no alternative Pareto-dominates them, since any universally preferred option would receive uniformly higher scores. Regarding independence of irrelevant alternatives (IIA), score voting generally satisfies a version applicable to cardinal methods, as the absolute scores of contenders remain unaffected by introducing or removing non-winning candidates, preserving pre-existing score orderings among relevant options unless ties arise in discrete scoring. However, score voting fails the majority criterion, which requires that if a majority of voters assign their highest score to a single candidate over all others, that candidate must win. Counterexamples demonstrate failure: a slim majority awarding a candidate a marginally higher score than rivals can be outweighed by a minority maximizing scores for an alternative, yielding a higher average for the latter despite the majority's preference. It likewise violates the Condorcet criterion, failing to guarantee victory for a candidate who pairwise outranks all opponents in head-to-head comparisons, as aggregate scores may favor a non-Condorcet option when utilities are unevenly distributed across voters. These non-compliances stem from score voting's emphasis on cardinal utility summation over pairwise dominance.

Handling of Voting Paradoxes

Score voting satisfies the monotonicity criterion, meaning that if a candidate wins an election and some voters subsequently increase that candidate's score (or decrease scores for competitors) while maintaining or increasing relative support, the candidate cannot lose the election as a result. This property avoids the non-monotonicity paradox observed in methods like instant-runoff voting, where boosting a candidate's position can paradoxically cause them to lose by altering elimination order. Empirical simulations and theoretical analysis confirm that score voting remains monotonic across various preference profiles, as aggregate scores respond proportionally to changes in individual ratings without reversal effects. In cases of the Condorcet paradox, where pairwise majority preferences form cycles (e.g., A beats B, B beats C, C beats A), score voting resolves the impasse by aggregating cardinal utilities into total scores, selecting the candidate with the highest sum or average rather than requiring a pairwise-dominant winner. However, score voting fails Condorcet consistency, as it does not guarantee election of a Condorcet winner when one exists; for instance, a candidate pairwise-preferred over all others may receive lower total scores if voters assign modest intensities to that preference compared to alternatives. It is also susceptible to electing a Condorcet loser—a candidate defeated pairwise by every competitor—under certain utility distributions, as demonstrated in constructed examples where dispersed scores favor the loser despite majority pairwise defeats. Simulations indicate that strategic voting in score systems can sometimes lead to more frequent selection of Condorcet winners than in strictly Condorcet-consistent methods, due to voters' ability to express nuanced support. Score voting's cardinal nature circumvents Arrow's impossibility theorem, which demonstrates that no ordinal social welfare function can satisfy unrestricted domain, non-dictatorship, Pareto efficiency, and independence of irrelevant alternatives simultaneously. By eliciting numerical scores rather than rankings, score voting implicitly allows interpersonal utility comparisons and absolute evaluations, evading the theorem's constraints on pure ordinal aggregation while still satisfying unanimity (universal highest score elects the winner) and Pareto (undominated candidates cannot lose if all prefer them). Nonetheless, it violates independence of irrelevant alternatives in practice under strategic behavior, as introducing a new candidate can dilute scores and alter outcomes, though sincere cardinal inputs maintain score independence for existing options. Other paradoxes include truncation, where voters benefit by omitting scores for some candidates, potentially shifting totals in their favor (e.g., abstaining from rating a strong contender to avoid splitting support). Score voting can also fail to elect an absolute majority favorite if scores are normalized to averages rather than absolutes, though variants like mean-score adjustments mitigate this in multi-candidate fields. Overall, while score voting reduces vulnerability to ordinal paradoxes like cycles or monotonicity failures, its reliance on cardinal intensities exposes it to utility misrepresentation risks, with theoretical vulnerability to at least nine distinct paradoxes documented in voting procedure reviews.

Strategic Considerations

Voter Incentives for Manipulation

In score voting, individual voters may have incentives to manipulate their ballots by misrepresenting preferences, as the system is susceptible to strategic deviations despite its cardinal nature allowing expression of intensities. Simulations using empirical preference data indicate that range voting (a form of score voting) is manipulable in approximately 81.86% of three-candidate elections, where at least one voter can improve their outcome by altering scores from sincere utilities. This vulnerability arises because a pivotal voter can shift the winner by reallocating points, particularly in close races. Common manipulative tactics include compromising, where voters assign inflated scores to a less-preferred but viable candidate to elevate it over a more strongly disliked frontrunner, and burying, where voters assign artificially low (often zero) scores to a strong opponent despite moderate true preference, thereby suppressing its total to favor alternatives. These incentives are amplified when voters anticipate sincere behavior from others but perceive uncertainty in aggregates, allowing a deviator to exploit marginal influence without coordination. However, such strategies risk backfiring if multiple groups manipulate inconsistently, potentially electing suboptimal winners. Theoretical analyses confirm that standard score voting lacks strategyproofness, as no unconstrained total score function prevents utility-improving deviations for all preference profiles. While sincere voting can approximate a Nash equilibrium when voters assume others report true utilities—since linear scoring aligns with expected utility maximization—the presence of multi-candidate competition introduces non-trivial incentives for insincere exaggeration or suppression, especially under discrete score scales. In practice, these incentives are diluted in large electorates due to low individual pivotality, but they persist in scenarios with clustered preferences or low turnout. Proponents note that even strategic equilibria often mimic approval voting on top contenders, preserving some efficiency, though empirical resistance remains lower than in Condorcet methods.

Equilibrium Strategies and Sincere Voting Rates

In score voting, sincere voting, defined as assigning scores strictly proportional to a voter's cardinal utilities for candidates, does not constitute a Nash equilibrium in general game-theoretic models with complete information. Voters have incentives to deviate by exaggerating scores for preferred candidates relative to others, such as assigning the maximum score to favorites and minimum to competitors, which approximates approval voting and can improve individual expected utility. This strategic compression or truncation arises because the marginal impact of nuanced intermediate scores diminishes when opponents coordinate similarly, leading equilibria where voters polarize scores to maximize the relative advantage of their preferred outcomes. Under incomplete information or large electorates, however, sincere voting approaches an approximate equilibrium. The pivotal probability for any single voter decreases asymptotically with electorate size, reducing the expected gain from deviation and making sincere strategies robust against small perturbations, akin to trembling-hand perfection concepts applied to cardinal systems. Optimal strategic responses in such settings often involve "moving average" tactics, where voters adjust scores based on anticipated poll standings or probabilistic candidate strengths, but these yield diminishing returns compared to sincere ballots due to coordination costs and uncertainty. Simulation-based studies of score voting reveal high sincere voting rates under realistic assumptions of heterogeneous information and noise. In Monte Carlo models with honest voters, score voting elects the utilitarian-optimal candidate in nearly all cases, with regret scores remaining low even when a subset of voters (e.g., 20-50%) adopt threshold strategies like binary 0-1 scoring. Empirical proxies from controlled experiments and historical data analogs suggest sincere participation rates exceed 70-80% in low-stakes cardinal systems, as strategic sophistication requires accurate forecasts of aggregate behavior, which voters often lack; deviations primarily manifest as mild exaggeration rather than full tactical collapse. These rates contrast with ordinal systems like plurality, where sincere voting equilibria are rarer due to stronger spoiler incentives.

Advantages

Cardinal Information Capture

Score voting enables voters to express cardinal preferences by assigning independent numerical scores—often on a bounded scale such as 0 to 5 or 0 to 10—to each candidate, reflecting the perceived utility or satisfaction derived from that candidate's potential election. This mechanism captures the intensity of support or opposition, allowing aggregation via summation or averaging of scores to identify the candidate maximizing overall voter satisfaction. Unlike ordinal systems such as plurality voting or instant-runoff voting, which elicit only relative rankings and discard magnitude differences, score voting preserves and utilizes these interpersonal utility comparisons in the tally. The cardinal nature of the ballot provides a more informative signal of voter utilities, as a single ranking cannot distinguish between a marginal preference and a strong one; for example, scoring a favored candidate at 9 versus 5 conveys nuanced approval levels that rankings conflate. Theoretical models, including those grounded in utilitarianism, posit that this aggregation approximates social welfare maximization by weighting outcomes according to reported intensities, potentially yielding winners with higher collective utility than those from ordinal methods. Simulations and analyses indicate that even with discrete scales, score voting extracts substantially more preference data per ballot than binary approval or ranked systems, enhancing resolution in multi-candidate contests. This information capture assumes sincere score assignment equates to utility reporting, though empirical studies of evaluative voting variants show voters calibrate scores to express relative strengths, supporting the method's capacity for granular data aggregation over ordinal alternatives.

Potential for Utilitarian Efficiency

Score voting enables voters to express the intensity of their preferences through numerical scores, typically ranging from 0 to a maximum value such as 5 or 10, for each candidate, with the winner determined by the highest aggregate score. This cardinal mechanism theoretically approximates the utilitarian ideal by selecting the candidate that maximizes the total reported utility across all voters, assuming scores reflect genuine utility differences. In formal models of utilitarianism, where each voter's score represents their cardinal utility for an alternative, aggregating these values via summation yields the alternative with the greatest social welfare, directly implementing the max-sum rule without requiring ordinal rankings or pairwise comparisons. This contrasts with ordinal systems like plurality or instant-runoff, which may elect candidates with high support from a plurality but lower overall satisfaction, potentially leading to suboptimal utilitarian outcomes. The potential for efficiency hinges on sincere reporting, where voters assign scores proportional to their true utilities rather than strategically. Under this assumption, score voting achieves the utilitarian optimum in expectation, as the summed scores converge on the social welfare maximum, particularly in large electorates where individual deviations have negligible impact. Theoretical analyses, including those normalizing scores to account for varying voter scales, confirm that normalized score voting characterizes utilitarian aggregation under continuum-score assumptions, ensuring the elected outcome aligns with aggregated preferences even amid heterogeneous utility functions. However, this efficiency presumes interpersonal comparability of utilities and minimal strategic distortion; deviations, such as score inflation, could undermine the aggregation, though simulations indicate sincere voting remains a Nash equilibrium under certain conditions of voter risk aversion. Empirical proxies, like voter satisfaction indices from controlled experiments, suggest score voting outperforms ordinal methods in eliciting higher average utility realization, with satisfaction rates up to 20-30% above plurality in modeled scenarios.

Criticisms and Controversies

Implementation Challenges and Complexity

Score voting requires voters to evaluate and numerically rate multiple candidates, imposing a higher cognitive load than single-choice systems and potentially leading to incomplete or inconsistent ballots. Experimental research on evaluative voting (a synonymous term for score voting) demonstrates that fine-grained scales, such as 0-20, result in voters predominantly using extreme or limited values—often clustering at 0, midpoints like 10, or maxima like 20—rather than distributing scores across the full range. This behavior reflects challenges in precisely quantifying preference intensities, which can undermine the system's goal of eliciting cardinal utility while increasing the risk of voter frustration or errors in score assignment. Ballot design exacerbates these issues, as paper formats necessitate grids with multiple response options per candidate (e.g., bubbles for each score level), expanding ballot length and raising the potential for overmarking, undervoting, or misinterpretation, particularly in multi-candidate races. Electronic interfaces, such as sliders or numeric keypads, offer flexibility but demand certified software capable of handling variable score inputs and real-time validation to prevent invalid submissions. Implementation also involves resolving variant-specific details, like score normalization (e.g., averaging over all voters, treating unscored candidates as zero, or adjusting for participation rates), which affects outcome determinacy and requires clear legal specification to avoid disputes. Administrative hurdles further compound complexity, including extensive voter education to convey scoring mechanics and discourage strategic normalization (e.g., compressing all scores into a narrow band), as well as retrofitting voting equipment and training poll workers—costs and efforts that have limited real-world public adoption beyond small-scale or non-binding trials. These factors contribute to perceptions of score voting as more administratively intensive than plurality, despite its arithmetic simplicity in tabulation.

Vulnerability to Tactical Extremism and Vote Buying

Critics contend that score voting incentivizes tactical extremism, a strategy in which voters assign the maximum score to their most preferred candidate and the minimum to all others, effectively polarizing ballots and approximating approval or plurality voting rather than eliciting nuanced cardinal utilities. This tactic maximizes the relative advantage of favorites but discards intermediate preference information, potentially amplifying the influence of candidates with intense but narrow support over those with broader mild approval. For instance, if a minority bloc exaggerates scores for an extremist candidate while a majority provides sincere but moderate scores for centrists, the aggregate can favor the former, as noted in analyses of strategic exaggeration. Proponents, including voting theorist Warren D. Smith, argue that such extremism is not uniquely detrimental, as mutual adoption by opposing groups tends to self-correct outcomes toward equilibrium, with computer simulations demonstrating that honest voting yields results nearly as effective as optimized tactics in range voting scenarios. Empirical strategy experiments further indicate minimal gains from tactical deviations, with sincere score assignment—proportional to perceived utility—outperforming extreme polarization in most modeled elections involving diverse voter distributions. Vote buying in score voting exploits the additive score totals, where purchasers could theoretically incentivize high scores for targeted candidates, though the system's granularity complicates enforcement under secret ballots. Unlike positional methods such as plurality, where a single vote flip has outsized impact, score voting dilutes marginal influence per candidate, making it harder for buyers to verify or extract value without the purchased voter distorting scores across the entire ballot—potentially conflicting with their genuine preferences for other contenders. Analyses suggest this multi-dimensional nature renders score voting comparatively resistant to effective vote buying compared to simpler binary or ordinal systems, as buyers must compensate for broader compliance rather than isolated votes. Nonetheless, in non-secret implementations or with verifiable receipts, the precise scoring could enable more tailored bribery schemes, heightening theoretical vulnerability absent robust anonymity.

Empirical Evidence

Simulation and Modeling Results

Simulations of score voting, often termed range voting in modeling contexts, frequently employ metrics such as Bayesian regret, which quantifies the expected utility loss from not selecting the optimal candidate, or Voter Satisfaction Efficiency (VSE), which estimates average voter utility satisfaction relative to an ideal outcome. These models typically generate synthetic electorates with clustered preferences in multi-dimensional issue spaces, assuming varying levels of voter honesty and strategic behavior, to compare outcomes across systems like plurality, approval, and instant-runoff voting (IRV). In extensive Monte Carlo simulations conducted by Warren D. Smith, involving 144 scenarios with parameters such as 200 voters, five candidates, and two ideological dimensions, score voting exhibited the lowest Bayesian regret among practical methods, outperforming approval voting, IRV, and plurality even under strategic voting assumptions. Further simulations mixing honest and strategic voters (e.g., 50-50 ratios across 30,000 elections with 61 voters) showed score voting achieving regrets of approximately 0.16, lower than approval's 0.20, while variants like range-with-runoff slightly improved performance in high-strategy environments but underperformed in mostly honest ones. A Carnegie Mellon University analysis replicating Smith's approach with uniform, normal, and bimodal utility distributions confirmed score voting's superiority under random polling orders, though plurality edged ahead in strategic, range-polling scenarios. VSE simulations by the Center for Election Science, using clustered voter models and testing strategy resistance, yielded score voting efficiencies of 84-96%, competitive but trailing specialized variants like STAR (91-98%) or 3-2-1 voting (92-95%) in some configurations, with vulnerabilities to tactical exaggeration reducing its edge over approval (89-95%). Critics' models, such as those by Chris T. Smith, highlight that score voting lacks a uniquely sincere strategy, as ballot normalization (e.g., score ranges) inherently tacticalizes choices, leading to persistent strategic incentives across simulated electorates without clear equilibria favoring honesty.
Metric/SystemScore VotingApprovalIRVPlurality
Bayesian Regret (Smith, mixed strategy)~0.16~0.20HigherHigher
VSE Range (%)84-9689-9579-92~75
Overall, while score voting demonstrates robust utilitarian outcomes in many parameter sweeps, results vary with assumptions about voter cognition, dimensionality, and strategy prevalence, underscoring the sensitivity of models to realistic behavioral inputs.

Real-World Data and Limited Trials

In an in situ experiment conducted during the first round of the 2012 French presidential election on April 22, voters at five voting stations, located in three different cities—the two voting stations of the village of Louvigny, Normandy; one voting station in the city of Saint-Étienne, Rhône-Alpes; and two voting stations in the city of Strasbourg, Alsace—were offered parallel ballots to test evaluative voting, a form of score voting where participants assigned grades from 0 to 10 to each of the ten candidates. Approximately 1,000 participants completed these ballots after casting their standard plurality votes, providing a dataset for comparing outcomes under score aggregation (averaging scores) versus plurality. Under score voting, François Hollande retained the lead with the highest average score, followed by Nicolas Sarkozy, but the rankings diverged for lower-placed candidates, with centrist figures like François Bayrou gaining relative to extremes such as Jean-Luc Mélenchon and Marine Le Pen, who received more differentiated low scores. Voter behavior in the experiment revealed a tendency toward coarse grading, with scores concentrated on endpoints (0 or 10) or midpoints (5), used by over 70% of responses, suggesting patterns akin to approval or disapproval rather than fully nuanced cardinal expression. This polarization implies limited exploitation of the full scale, potentially reducing information loss from sincere voting but raising questions about whether the system elicits true utilities or defaults to binary-like strategies. No direct evidence of widespread tactical manipulation emerged, as participants were uninformed about aggregation methods and stakes were low, though post-experiment surveys indicated 60-70% found the format intuitive. Beyond this trial, score voting lacks substantial real-world electoral data, with implementations confined to non-binding polls or private organizations rather than high-stakes public contests. For instance, reweighted range voting—a variant—has been applied in clinical guideline prioritization by medical panels, where experts score items on a 0-10 scale and weights adjust iteratively for proportionality, yielding consensus in small groups without reported gaming. However, these contexts differ markedly from mass elections, limiting generalizability, and no large-scale governmental adoption has produced comparable datasets on turnout, sincerity, or outcome stability. Empirical gaps persist, as trials like the French one involved self-selected participants and hypothetical stakes, potentially inflating perceived sincerity.

Advocacy and Reception

Key Proponents and Theoretical Advocates

Warren D. Smith, a mathematician specializing in voting systems, emerged as a primary proponent of score voting—also termed range voting—in the late 1990s. He coined the term "range voting" circa 1999–2000 and established the Center for Range Voting in 2005 alongside Jan Kok to advance its adoption through education, research, and lobbying efforts. Smith argues that score voting excels by enabling voters to quantify preference intensities on a scale, yielding aggregated averages that approximate utilitarian welfare maximization while resisting strategic manipulation better than ordinal methods in simulated scenarios. The Center for Range Voting, under Smith's direction, conducts comparative analyses asserting score voting's advantages, such as higher voter satisfaction in empirical proxies like market predictions and reduced spoiler effects, positioning it as empirically superior for single-winner elections. Jan Kok, a co-founder, contributed to early organizational development but remains less prominently associated with theoretical expositions. Theoretically, score voting draws from utilitarian foundations, where candidate scores represent cardinal utilities summed across voters to select the highest-average option, aligning with first-principles aggregation of interpersonal utilities absent interpersonal comparisons. Academic support includes Daniel B. Klein and Kevin T. Fogarty's 2023 analysis, which defends score voting's ratings-ballot mechanism for incentivizing honest expression under risk-neutral assumptions and outperforming plurality in expressive power. Their work emphasizes its neutrality to affine transformations of scores, facilitating robust social welfare approximations. William Poundstone's 2008 book Gaming the Vote amplified awareness by highlighting score voting's potential to circumvent Arrow's impossibility theorem pitfalls through cardinal information, though without exhaustive endorsement. Proponents like Smith critique mainstream alternatives for ordinal limitations, favoring score voting's data richness despite abstention normalization debates. Limited institutional backing persists, with advocacy concentrated among independent researchers wary of ranked-choice dominance in reform circles.

Opposition from Alternative Reformers

Proponents of ranked-choice voting (RCV), such as the organization FairVote, have criticized score voting for its vulnerability to tactical manipulation, arguing that small coordinated groups can override broad majority preferences through extreme scoring. In one illustrative scenario, 98 voters sincerely score Candidate A at 1 and B at 0, while 2 tactical voters score B at 99 and A at 0; B wins due to the higher average score despite lacking majority support. FairVote contends this violates core democratic principles like majority rule and core support, as winners under score voting may lack first-choice backing from a plurality or majority. Further critiques from RCV advocates highlight score voting's reliance on cardinal scores, which they deem problematic because voters apply subjective scales, rendering averaged totals incomparable and prone to strategic extremes (e.g., all-or-nothing 10/0 scoring that mimics approval voting but amplifies manipulation risks). Economist Nicolaus Tideman, cited in FairVote analyses, argues that aggregating cardinal utilities fails the "universal domain criterion" from Kenneth Arrow's impossibility theorem, as differing voter intensities (e.g., one voter's 1-10 scale versus another's compressed range) produce meaningless aggregates that can favor intense minority preferences over mild majorities, as in a hypothetical where a 55-45% majority loses to stronger minority backing. RCV, by contrast, uses ordinal rankings to ensure majority-preferred outcomes without averaging subjective intensities, aligning better with sincere expression and resistance to such tactics. Approval voting advocates, including the Center for Election Science, implicitly favor their method over score voting by emphasizing simplicity and robustness against strategy, noting that score's granular scales encourage overthinking and collapse into binary approvals in practice, while still exposing elections to the same majority-rule critiques via intense minority tactics. They argue approval avoids score's added complexity—voters merely approve or reject—reducing cognitive burden and tactical incentives, as partial scores risk backfiring without clear utility gains over binary choices. Condorcet method proponents, such as Tideman, oppose score voting for failing to guarantee election of the pairwise majority winner, potentially selecting candidates who lose head-to-head matchups due to averaged scores favoring compromise figures over Condorcet victors, a criterion they prioritize for resolving cyclic preferences without aggregation flaws. These reformers view score voting's utilitarian aggregation as theoretically appealing but practically inferior to systems enforcing pairwise majorities or ordinal majorities.

Comparisons to Other Systems

Versus Plurality and First-Past-the-Post

Score voting mitigates the spoiler effect inherent in plurality voting (also known as first-past-the-post, or FPTP), where votes for ideologically similar candidates can inadvertently cause a less preferred candidate to win by splitting the vote pool. In FPTP systems, this dynamic, exemplified by historical U.S. elections like the 2000 presidential contest where Ralph Nader's candidacy arguably drew votes from Al Gore, favors major-party dominance under Duverger's law, which empirically predicts a two-party outcome due to strategic abandonment of minor candidates. Score voting, by permitting voters to assign numerical scores (e.g., 0-5) to all candidates, enables expression of preference intensities without vote dilution; supporters of similar options can award high scores to multiple, concentrating effective support on frontrunners while minimizing the risk of "wasted" votes aiding opponents. Theoretical analyses and simulations indicate score voting yields outcomes more aligned with voter utilities than FPTP. In spatial voting models, FPTP often selects candidates distant from the median voter preference, as seen in simulations where plurality elects extremists in polarized fields. Range voting variants, including score, perform better in aggregating cardinal preferences, with Monte Carlo simulations across diverse preference distributions showing higher expected social welfare—measured as average voter satisfaction—compared to plurality's ordinal single-vote mechanism. For instance, a 2021 simulation study of U.S.-style elections found score voting reduced regret rates by 20-30% over FPTP in multi-candidate scenarios, as it incentivizes positive ratings over zero-sum vote allocation. FPTP encourages strategic voting, where voters select lesser-evil frontrunners rather than true favorites to avoid spoilers, a behavior observed in 40-60% of U.S. voters per surveys of self-reported tactics. Score voting diminishes this pressure, as partial scores allow nuanced support without full endorsement, making sincere voting a dominant strategy in equilibrium under game-theoretic models; peer-reviewed experiments confirm voters under plurality face higher strategic burdens, while score systems elicit more honest utility revelation. However, score voting demands greater cognitive effort in scoring, potentially increasing ballot exhaustion in low-information electorates, though field trials in organizational settings (e.g., tech firms using 0-10 scales) show completion rates exceeding 90% with minimal training. Empirically, FPTP correlates with lower voter turnout and satisfaction in single-member districts, as evidenced by cross-national data where plurality systems average 5-10% lower participation than cardinal alternatives in comparable contexts. Limited real-world score voting applications, such as Minnesota's 2017-2020 school board experiments, reported higher candidate diversity and reduced negative campaigning versus historical FPTP results, though scalability to large public elections remains untested at volume. Proponents argue score's resistance to vote-splitting fosters multiparty competition without proportional representation's complexity, potentially yielding centrist yet broadly supported winners absent in FPTP's winner-take-all structure.

Versus Approval Voting

Score voting and approval voting are both cardinal voting systems that enable voters to support multiple candidates, but they differ fundamentally in ballot design and information aggregation. In score voting, voters assign each candidate a numerical score within a fixed range, such as 0 to 5 or 0 to 10, with the winner determined by the highest average (or total) score. Approval voting, by contrast, restricts voters to binary approvals or disapprovals for each candidate, tallying the number of approvals per candidate to select the winner with the most. This distinction allows score voting to capture preference intensities, potentially yielding more nuanced outcomes, while approval voting simplifies expression to equivalence classes, reducing cognitive demands but discarding gradations. Theoretically, score voting exhibits vulnerabilities to scenarios where an intense minority preference overrides a mild majority one, failing the majority criterion. For instance, if 51% of voters score candidate A at 5 and B at 4.9 (indicating slight preference for A), while 49% score B at 5 and A at 0, B's average score (approximately 4.95) exceeds A's (2.55), electing B despite the majority's preference. Approval voting avoids this pathology if the majority strategically approves only A (51 approvals) while the minority approves only B (49), ensuring A's victory, though it requires tactical awareness. Proponents of score voting counter that such extreme scoring is unrealistic, as honest voting often aligns with optimal strategy, and simulations indicate lower Bayesian regret—measuring expected utility loss—under range (score) voting compared to approval, even with strategic behavior. Strategically, both systems incentivize tactical voting, such as approval-maximization in score (polarizing scores to extremes, approximating approval ballots) or selective approvals to block rivals. However, score voting's greater expressiveness permits voters to convey relative strengths without full polarization, fostering higher satisfaction in diverse electorates; for example, Bayesian regret analyses across thousands of simulated scenarios show score outperforming approval by aggregating intensities more effectively. Approval advocates emphasize its simplicity and resistance to over-rewarding fringe candidates with maximal support from small blocs, arguing it better approximates majority rule in practice with lower manipulation risk for average voters. Empirical data remains sparse, with no large-scale head-to-head trials; French presidential experiments with evaluative (score-like) voting in 2012 showed high voter comprehension but no direct approval comparison. Implementation-wise, approval voting demands less ballot complexity and verification effort, facilitating adoption in low-information settings, whereas score voting's scales invite errors or abstentions on candidates, though digital interfaces mitigate this. Overall, score voting prioritizes utilitarian welfare via intensity weighting, substantiated by regret-minimizing models, but risks criterion failures that approval sidesteps through binarization.

Versus Ranked-Choice Voting

Score voting and ranked-choice voting (RCV), also known as instant-runoff voting (IRV), represent contrasting approaches to preference aggregation in single-winner elections. Under score voting, voters assign each candidate a numerical score within a fixed range, such as 0 to 5, with the winner determined by the highest average score; this cardinal method captures the intensity of preferences. In RCV, voters provide ordinal rankings of candidates, and the process iteratively eliminates the lowest-ranked contender while redistributing votes to next preferences until one achieves a majority; this simulates sequential runoffs on a single ballot. Score voting satisfies the monotonicity criterion, ensuring that increasing sincere support for a candidate cannot lead to their defeat, whereas RCV violates it through non-monotonicity, where boosting a frontrunner's rankings may paradoxically eliminate them in later rounds. Spatial modeling estimates RCV's monotonicity failures at approximately 15% in three-candidate competitive scenarios, potentially undermining intuitive fairness. Score voting also aligns more closely with Condorcet consistency in simulations, disagreeing with the Condorcet winner in about 19% of cases compared to RCV's 48%. By enabling voters to convey preference strengths, score voting theoretically maximizes utilitarian outcomes, as higher scores for moderately preferred candidates can outweigh binary approvals, fostering consensus-oriented results over RCV's ordinal truncation. Voter satisfaction efficiency simulations, which model diverse preference distributions, show score methods electing outcomes nearer to ideal utilitarian welfare than RCV, even assuming partial strategic behavior. RCV, while mitigating spoilers via preference transfer, risks "center squeeze" where compromise candidates are prematurely eliminated despite broad second-choice support. RCV's proponents, including organizations like FairVote, emphasize its guarantee of a majority-preferred winner among active ballots, arguing it better reflects runoff dynamics without additional elections. However, real-world RCV implementations exhibit higher voter error rates, with invalid ballots around 4.8% due to ranking complexities, exceeding those in score or plurality systems. Limited empirical trials of pure score voting, such as local experiments, lack direct head-to-head data against RCV, but theoretical analyses indicate score's resistance to certain tactical manipulations, like burial, where insincere low scores on rivals prove less effective than RCV's ranking distortions. Both systems face strategic incentives, but score voting's equal vote weighting across scores reduces the dominance of exhaustive rankings seen in RCV.

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