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Droop quota

Droop quota is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Droop quota rather than just read about it. In short: In the study of electoral systems, the Droop quota (sometimes called the Hagenbach-Bischoff, Britton, or Newland-Britton quota) is the minimum number of votes a party or candidate needs to receive in a district to guarantee they will win at least one seat. The Droop quota is used to extend the concept of a majority to multiwinner elections, taking the place of the 50% bar in single-winner elections.

Droop quota — main illustration
Droop quota — illustration

Key takeaways

  • Droop quota belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Droop quota to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Droop quota from memory before moving on to harder problems.

Reference excerpt

In the study of electoral systems, the Droop quota (sometimes called the Hagenbach-Bischoff, Britton, or Newland-Britton quota) is the minimum number of votes a party or candidate needs to receive in a district to guarantee they will win at least one seat. The Droop quota is used to extend the concept of a majority to multiwinner elections, taking the place of the 50% bar in single-winner elections. Just as any candidate with more than half of all votes is guaranteed to be declared the winner in single-seat election, any candidate with more than a Droop quota's worth of votes is guaranteed to win a seat in a multiwinner election. Besides establishing winners, the Droop quota is used to define the number of excess votes, i.e. votes not needed by a candidate who has been declared elected. In proportional quota–based systems such as STV or expanding approvals, these excess votes can be transferred to other candidates to prevent them from being wasted. (As well, the equivalent of one quota is the number of votes not used to elect someone in many STV contests.) The Droop quota was first suggested by the English lawyer and mathematician Henry Richmond Droop (1831–1884) as an alternative to the Hare quota and later by Swiss physicist Eduard Hagenbach-Bischof in the context of STV and not for the largest remainder method. The Droop quota is used in almost all STV elections, including those in Australia, the Republic of Ireland, Northern Ireland, and Malta. It is also used in South Africa to allocate seats by the largest remainder method. Switzerland uses the Droop quota, calling it the Hagenbach-Bischof quota. Although common, the quota's use in proportional representation has been criticized both for its bias toward large parties and for its ability to create no-show paradoxes, situations where a candidate or party loses a seat as a result of having won too many votes. However, this situation can occur regardless of whether the quota is used with largest remainders or STV. Charges of no-show paradoxes are based on having knowledge of how a vote would be transferred if a candidate were eliminated when that candidate may not have been in real life. It is clear that any system that uses ranked votes produces different results if candidates are in different order, which is partly determined by how votes are split and therefore that charge can apply to any ranked voting system no matter what quota is used. Some analysis states that no-show paradoxes are extremely rare in real-world elections. For one thing, transfers have little effect in general on who is elected, the winners usually being among the front runners in the first round of counting anyway.

Definition The value of the exact Droop quota for a k {\displaystyle k} -winner election is given by the expression:

total votes k + 1 {\displaystyle {\frac {\text{total votes}}{k+1}}}

In the case of a single-winner election, this reduces to the familiar simple majority rule. Under such a rule, a candidate can be declared elected as soon as they have more than 50% of the vote, i.e. their vote total exceeds total votes 2 {\textstyle {\frac {\text{total votes}}{2}}} . A candidate who, at any point, holds strictly more than one Droop quota's worth of votes is therefore guaranteed to win a seat. Sometimes, the Droop quota is written as a share of all votes, in which case it has value 1⁄k+1.

Original Droop quota The original Droop as devised by Henry Droop was one more than the exact Droop:

total votes k + 1 + 1 {\displaystyle {\frac {\text{total votes}}{k+1}}+1}

Modern variants of STV use fractional transfers of ballots to eliminate uncertainty and therefore do not need to use the original whole-vote Droop quota. The original Droop quota is not necessary in elections that allow fractional transfers of ballots. However, some older implementations of STV with whole vote reassignment did not use fractional votes and so instead either rounded up or added one and truncated:

⌈ total votes k + 1 ⌉ ≈ ⌊ total votes k + 1 + 1 ⌋ {\displaystyle \left\lceil {\frac {\text{total votes}}{k+1}}\right\rceil \approx \left\lfloor {\frac {\text{total votes}}{k+1}}+1\right\rfloor }

This whole-vote variant of the quota is not necessary in the context of modern elections with fractional votes, and it can cause problems in small elections (see § Variety of Droop quotas). However, it is the most commonly used definition in legislative codes worldwide.

Derivation of the original Droop quota The Droop quota was derived by considering what would happen if k candidates (here called "Droop winners") have achieved the Droop quota: could too many achieve quota? The goal was to identify whether an additional candidate could defeat any of the candidates who have quota. If each quota winner's share of the vote equals 1⁄k+1, all unelected candidates' share of the vote, taken together, is at most 1⁄k+1 votes. Thus, even if there were only one unelected candidate who held all the remaining votes, their vote tally would not exceed any of those with Droop quota.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Droop quota

Start with the simplest possible case. Write down what Droop quota claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Droop quota before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Droop quota ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Droop quota

In research
Droop quota appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Droop quota in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Droop quota is common in secondary-school and first-year university syllabi. It links to neighbouring topics Apportionment methods, Electoral system quotas, Single transferable vote, so understanding it makes those chapters shorter.
In everyday life
Look for Droop quota outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Droop quota in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Droop quota means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Droop quota out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Droop quota in simple terms?

In the study of electoral systems, the Droop quota (sometimes called the Hagenbach-Bischoff, Britton, or Newland-Britton quota) is the minimum number of votes a party or candidate needs to receive in a district to guarantee they will win at least one seat. The Droop quota is used to extend the conc…

Why does Droop quota matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Droop quota?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Droop quota.

Tags

  • Apportionment methods
  • Electoral system quotas
  • Single transferable vote

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