Fun with Voting in Cambridge, MA

My city of Cambridge, MA is one of a few municipalities which employs ranked choice voting for City Council elections. Unlike most cities, the Mayor is chosen by the City Council and is largely a ceremonial position. Most real power resides with the City Manager, who is appointed for an indefinite term by the City Council. This means that City Councils which get to appoint a new City Manager exert an inordinate influence over the future course of the city. One such point is fast approaching. Unfortunately, given the present and probable near-term composition of the City Council, the decision likely will be based on considerations other than aptitude. However, putting aside my city’s somber prognosis, the upcoming City Council election is a good opportunity to discuss an unusual method of voting and some of its shortcomings.

Ordinary winner-takes-all elections dominate the popular consciousness. National elections are of this nature. It would not be inaccurate to observe that such an approach reflects the general weltanschauung of our culture. However, there are many other voting methods. In fact, voting theory is a vibrant field of research. Together with its sibling, auction theory, it forms part of the subject commonly known as “social choice theory”.

As an aside, I recently published a paper, Social Choice using Moral Metrics in that field. It focuses on measuring distances between behaviors, rather than on voting systems per se. Back in 2008, I also wrote a voting theory piece about swing votes and block voting. What I termed “influence” in it is more commonly referred to as “voting power”. Neither are related to what I discuss in this post, but I encourage the interested reader to peruse them.

It may be argued that certain voting methods are fairer than others, by one or another definition of fairness. Particular flavors sometimes are advocated by those disenchanted with an existing method or an agenda to see some particular group gain influence.  Calls for change sometimes arise in response to highly-visible anomalies, election outcomes which appear egregiously unfair even to disinterested eyes.

In elections with a large field of candidates or those in which a number of positions are simultaneously filled (such as the Cambridge City Council election), winner-takes-all voting may not be suitable or may give rise to such anomalies.

California’s recall system is an example. The ballot in that case has 2 questions: (1) whether to recall the governor and (2) who should replace him. The first question is winner-takes-all for the governor alone. If he loses, the 2nd question is winner-takes-all for the other candidates. It is quite possible for a candidate to be chosen who easily would have lost to the recalled governor one-on-one. In 2003, 44.6% of voters voted not to recall Governor Davis. He thus was recalled, and Schwarzenegger then won with 48.58% of the votes for replacement. It is highly unlikely that in a head-to-head gubernatorial election, Republican Schwarzenegger would have beaten Democrat Davis in the heavily blue state. However, Gray was excluded from this 2nd contest and Schwarzenegger was deemed preferable to the alternatives by most voters.

Arrow’s Theorem

It is natural to ask whether any voting system is unimpeachably fair, indicting the use of other systems as anachronistic or disingenuous. Arrow famously proved that, under even a small set of fairness constraints and for a broad class of voting systems, it is impossible to find one. Loosely speaking, when more than 2 candidates are present, no method of aggregating the rankings of candidates by voters into a single outcome ranking can simultaneously satisfy three conditions: (1) if every voter prefers candidate x to candidate y, then x outranks y in the outcome, (2) no single voter’s preference determines the outcome (i.e. no dictator), and (3) if each voter ranks x relative to y (i.e. above or below it) the same way in elections A and B (though the order can differ between voters, of course), then the outcomes of A and B do too. I.e., if voters change their overall ranking of x and y or the relative placement of other candidates, but don’t change whether x is preferred to y or vice versa, then whether x outranks y or vice versa in the outcome is unchanged.

It is quite plausible to add more fairness conditions, but most plausible definitions of fairness would require at least these three conditions to hold. Arrow showed that there is no ranked voting system (including “preponderance of the votes”) in which unfair anomalies cannot arise.

As an aside, if one were to relax a condition, the most palatable clearly would be (3). It is conceivable that a “fair” aggregation method may allow the overall ranking of candidates to affect a pairwise order in the outcome. However, this generally is deemed undesirable.

As with complexity results in computer science (CS) or Godel’s impossibility theorem in logic, the theoretical existence of hard or problematic cases does not necessarily pose a practical obstacle. In CS, an algorithm with worst-case exponential complexity may be far more useful than one with linear complexity in real-world applications. For example, the latter could have a huge constant cost (often referred to as a “galactic algorithm”) and the former could be exponential only in an infinitesimal fraction of cases or under circumstances which never arise in practice. Godel’s theorem does have real-world examples (i.e. non-meta-theorems), but (at this point) they remain rare.

Though nowhere near as profound,  Arrow’s theorem invites similar skepticism.  The impossibility of a preference system which excludes all anomalies does not mean such anomalies arise in practice, or that a system which excludes all realistic anomalies cannot be found.   Unfortunately (or fortunately, depending on one’s perspective), such anomalies do arise in practice.  Worse,  the systems in question often are of significant social import and subject to intense scrutiny.  The anomalies which do arise can be quite visible and politically troublesome.

Social choice theory exhibits another critical difference from CS and logic, one which merits additional caution.  The goal of logic, mathematics, and theoretical computer science generally is to understand which problems are solvable and how best to solve them.  Anomalies are viewed as pathological and undesirable.  They sometimes serve as useful counterexamples, guiding researchers to better understanding and helping them improve their tools.   However, they are to be avoided in real-world applications.   If a pathological case arises in such a context, alternate machinery must be employed or the framework modified to exclude it.

This need not be the case in social choice theory.   Not everyone’s goal is aligned, or social choice would be unnecessary.    With elections, there could be adverse incentives. It may be possible to game an election by identifying and exploiting anomalies endemic to the specific system involved.  There also may be groups who strongly prefer that anomalies arise, either for purposes of fomenting discord or if those anomalies serve them well.  For this reason, dismissing anomalies as almost impossible under some assumed prior may be naive. The prior must incorporate human behavior, and this very well could concentrate probability around the anomalies.  Put another way, if we naively model the probability of anomalies arising using an assumption of ideal behavior we risk ignoring the very real possibility that participants will engineer or utilize anomalies.

This issue is related to Gibbard’s theorem, which loosely states that under even weaker conditions than Arrow’s theorem (at least 3 candidates and no dictator), there is no ideal ballot which reflects a voter’s preferences. Put another way, the voting system can be gamed. In fact, a voter may need to game it (perhaps in response to polls or other information) in order to best reflect their individual preferences. The optimal ballot ranking to enact a voter’s preferences may not be their actual preference ranking of candidates.

The Rules in Cambridge

What does all this have to do with the Cambridge elections? Cambridge employs a particular system of ranked choice voting, which they refer to as “Proportional Representation”. This often is portrayed as fairer, more democratic, and so on. I am going to offer an example of an egregious anomaly which can result. I do this not in the expectation that it will arise or be exploited.  Nor do I hope to change a voting method that is, all things considered, quite reasonable.  Rather, the anomaly serves an illustrative example of the inherent problem with claiming that one voting system is “fairer” than another.

First, I’ll describe the precise rules of the Cambridge election, as best I understand them. See MA Election Laws, section 9 for details.  State law governs the general rules for proportional representation voting in any Massachusetts municipalities which choose to employ it.  Only certain parameters and details of execution are left to local discretion.

The City Council consists of 9 individuals, and the entire body is elected once every 2 years. Voters are presented with a list of candidates and may select a 1st choice, a 2nd choice, and so on.  I do not recall the maximum number of choices which can be made, but let us suppose it is not limited. The anomaly arises whether or not this is the case. Note that a given voter is not required to rank all the candidates. They could select only their top 3 choices, for example. Whether or not a full ranking by each voter is required does not affect the anomaly.

First some definitions. N will denote the total number of ballots (i.e. the number of voters who participate in the election).  At the time of writing, the minimum number of signatures to get on the ballot is 50.  We’ll call this ‘M’, because State law gives it a role in the algorithm. Q=(N/10)+1 will be the “quota”, the minimum number of ballots a candidate needs to win.

Why not choose Q=N/9?  The type of voting system we’re describing is sometimes referred to as “single-transferable-vote” (STV) because of the use of spillovers (described below). There are two common quota methods for determining STV winners:  (1) “Hare” corresponds to Q=N/9, and (2) “Droop” corresponds to Q=(N/10)+1.   In each case, we round up if needed. The two methods generally result in the same outcome or differ only in how the last winner is chosen. Each has benefits and drawbacks vis-a-vis what is deemed fair in terms of proportional representation. Among other things, the Droop quota tends to favor small parties over large. It also is the smallest quota which guarantees no more than 9 winners. As we will see, neither method guarantees a full complement of 9 winners.  Regardless, the Droop quota is that used by Cambridge.

Once the ballots have been collected, a sequence of steps is performed by computer. An order of polling places is determined randomly by the city beforehand. Within each polling place, ballots are sorted by the choice of 1st place candidate (and then presumably randomly within each such cohort).  The ballots then go through a series of stages.  The first stage is special.

Stage 1: Any candidate who reaches Q votes is declared a winner. Subsequent 1st place votes for them are passed to the next ranked candidate on the ballot who has not already been declared a winner. Ex. if a ballot is reached with x, y, and z as the 1st, 2nd, and 3rd candidates, and both x and y already have been declared winners, it would go to z. If no non-winner choice remains on the ballot, it is swapped with a ballot that already was consumed by the winner and has non-winner choices on it. This minimizes the number of discarded ballots. Note that it always pays for a voter to rank a lot of choices, because otherwise some other voter may have their preference registered instead. It’s not clear from the law what order the 1st place candidates’ ballots should be sorted, but we’ll assume randomly. It does not matter for the anomaly we will discuss. As the sorting proceeds, any candidate with Q votes (by spillover from other candidates or by being 1st on their own) is declared a winner, and any remaining votes for them spill over as described.

Once this process has been completed, almost every ballot has been assigned to some candidate (i.e. either consumed by a winner or spilled over to a remaining candidate). Because of the ballot-swapping mechanism described, it unlikely (but still possible) for ballots to have been discarded due to lack of non-winner alternatives. Each winner has consumed precisely Q ballots, and each remaining candidate has less than Q ballots. In what follows we use “higher-ranked” to refer to the preferred candidates on a ballot. In practice, this means they have been assigned a lower number. I.e., the 1st place candidate on a ballot is “higher-ranked” than the 2nd place candidate.

At this point, any candidate with fewer than M ballots (in our case 50) is declared to have lost. Their ballots are transferred in the same manner as before to the remaining candidates. Note that this form of elimination only takes place in this first round, since the number of ballots assigned to a candidate cannot decrease in subsequent rounds.

Stages 2+: If 9 candidates have been declared winners, the process ends. Otherwise, the trailing candidate is declared to have lost, and their votes are transferred (one by one) to the remaining candidates in the same  manner as before, but with one important change. Unlike in the first round, if no remaining non-winner candidates are listed on a ballot, it is discarded rather than swapped with another. As before, any candidate who reaches Q votes is declared a winner and can accrue no more votes. There are some tie-breaker rules associated with determining who is the trailing candidate at the end of a given round, but we won’t go into those. If at any time, the number of winners plus remaining candidates is 9, all remaining candidates are declared winners. The round ends when every ballot in play either has been spilled over (once) or discarded. Those ballots not discarded or consumed by winners and those candidates not eliminated then proceed to the next round.

Note that a spillover never can result in a ballot being assigned to a higher-ranked candidate. For example, suppose a ballot already has been assigned to the 3rd listed candidate on it. This only could happen if there was a reason to skip the top 2. This means they either already were declared winners or already were eliminated. Nor do any swaps (possible only in the 1st round) affect this. Any subsequent spillovers must go to lower-ranked candidates, or the ballot would have been handed to a higher-ranked candidate already.

Note that unless every voter ranks every candidate, it is possible for some ballots to be discarded. This is highly unlikely in the first round, because swapping is allowed. However, in subsequent rounds ballots may be discarded if they list no candidates which remain in play (i.e. that have not already been declared winners or eliminated). Though there is a theoretical bound on the number of possible discarded ballots, it can be high.

It is quite possible for an insufficient number of winners to be declared. This is no surprise. If every voter lists the same three candidates, but no others, then only three candidates will win. Insufficient ranking by voters can lead to inadequate outcomes.

Unless the field of candidates is reduced below 9 in the first round (i.e. too few candidates meet the 50 vote threshold), there ultimately will be 9 winners. However, some may not get many votes. If every voter ranks every candidate, then all winners will meet quota. If not, some candidates may win without meeting quota by dint of being the last ones uneliminated.

A number of obvious anomalies come to mind. For example, if everyone votes for x,y, and z as the top 3 candidates but there is a huge field of candidates for 4th place — so that each gets 51 spillover votes — then the remaining candidates won’t be eliminated in the first round. The remaining 6 winners then will be selected by the tie-breaker procedure (which we didn’t elaborate on).  Fair yes, desirable no. However, such anomalies can be accounted voter-failures. If each voter ranks the whole field of candidates, they won’t arise.

One important thing to note is that the election method described does not obey the conditions of Arrow’s theorem. The procedure is not even deterministic, and certainly does not satisfy the 3rd fairness condition. It is quite possible for a change in the ranking of candidate z on individual ballots to affect the order of x relative to y in the outcome even if the order of x relative to y is unchanged on those individual ballots. As an extreme example, suppose x is 1st and y is 2nd on 50 ballots and y is 1st and x is 2nd on 50 ballots, and suppose z is 3rd on all of these.   If one of the 1st 50 ballots moves z to the top, x will be eliminated in the 1st round.  If one of the 2nd 50 ballots moves z to the top y will be eliminated in the 1st round.  In neither case did the ranking of x relative to y change on any ballots.  Some anomalies arise for similar reasons to those involved in Arrow’s theorem, but others arise for different reasons.

The Anomaly

Let us now consider the specific anomaly we set out to discuss. Suppose there are 10000 ballots and 9 positions to be filled. We require 1001 votes for a candidate to win, but we’ll call it 1000 to simplify calculation. Suppose that candidate x is ranked 1st on all 10000 ballots, candidate y is ranked 3rd on all 10000 ballots, and 100 other candidates (which we’ll call z1-z100) are ranked 2nd on 100 ballots each.

Everyone agrees that candidates x and y should be on the City Council. They both rank in the top 3 choices for everyone. However, candidate y is eliminated in the first round. All the spillover votes from candidate x go to candidates z1-z100. The number could vary for each, depending on the order in which ballots are processed.  For example, it is possible that each of z1-z100 is assigned 90 spillover votes from candidate x.  It also is possible that z1-z90 would accrue 100 spillover votes each, and the rest would get 0 and be eliminated.

At the end of round 1, x is declared a winner and consumes 1000 votes, y has 0 votes, and z1-z100 each have between 0 and 100 votes.  At least 90 of them have enough to survive the 50 vote test.  However, y is eliminated.  The remaining z’s then proceed through a series of elimination and spillover rounds (with possible tie-breakers for the trailing candidate if needed) until only 8 of the z’s remain. These then are declared winners.

The result is 1 winner everyone wants, 8 winners few people agree on, and the conspicuous loss of the 2nd candidate everyone wants.

This is just one fun example of how well-intentioned voting systems can result in highly-undesirable outcomes.

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