__Comparing levels of fairness among different elections in different countries and electoral systems____proportion__

__of seats__that your chosen party gets comes very close to matching the

__proportion__

__of votes__they got. When your party's quantity of

__in the "house of power" is__

**representation**__to the quantity of votes they got, that's called__

**proportional**

**"proportional representation."****those two match in past elections -- both in our country and others.**

__how closely____various levels of proportionality among various past elections from various electoral systems of various countries. As we look back over time, we can see consistent__

**compare**__patterns and tendencies__.

__past__elections, then people can better choose, design, and improve their electoral system to fit

__their__particular needs in

__future__elections.

**Regardless of which party we are connected to, the Gallagher index provides us with a**

__Non partisan:____common__way to assess things. It can’t be swayed by bias because it's purely mathematical and therefore purely

__objective__. That’s why it’s worth learning about how the math works.

__If you encounter an electoral system that you’re not familiar with, and you question the exact extent to which it matches seats in proportion to votes (and you don’t have time to learn all the detailed nuances of that electoral system) you can put it through the test of the Gallagher Index to gain more confidence of its level of proportionality or dis-proportionality.__

**Test an unfamiliar electoral system more quickly:**

__Understanding it in chewable chunks in a table form__For each party, we take the

__"% of votes"__and subtract the "

__% of seats__" to get the "

__difference__" in percentages for each party.

__About the last column: Finding a way to compare the disproportionality of entire elections____entire__election is in comparison with other

__entire__elections, we need to somehow create

__one single score__for this entire election. We need to gather all of the

__"parties__’ scores of disproportionality" into one score of

__"election__disproportionality."

**Before we can add up all of the parties’ scores, we need to convert them all into positive numbers**.

**We can do that by squaring them all**(multiplying the number by itself)

**.**

**Summary of the last column:****, all the parties’ scores are squared, and they all become positive numbers.**

__First____, you add up all of the squares from all of the parties into one score for the entire election. Then you can compare this "score" with other elections' scores. Whichever election has the “least squares” has the least disproportionate electoral outcome. (See below FAQ #1)__

**Second**

**Learning from history with the Gallagher Index**The Gallagher Index "scores" for individual elections can also be applied to many elections over longer spans of time in history. As we look back over time, we can see

__consistent patterns and tendencies.__To see Canada's average "score" between 1950 and 2016, compared to eleven other countries (with various electoral systems) see this example. Or look here. Or to see many past elections from many countries (with various electoral systems), click here and look for the subtitle "Values of indices."

###
__
FREQUENTLY ASKED QUESTIONS (FAQ)__

#### 1. Did Gallagher invent the idea of "least squares?"

**No. Gallagher himself said that the idea of “Least Squares” (LSq) has a long history**in the natural sciences and social sciences. His index ("LSq = ...") is simply another form of it applied to elections. The method of “least squares” is used to compare an observed value (“what actually happens”) to its data point (“the ideal” or “reference point”). ("Least Squares" is discussed in both a Simple English Wikipedia article, and a regular Wikipedia article.)

####

2. Why halve (cut in half) the sum of the squares?

####

The parties which "got more seats than their votes warranted" actually "took" those seats from other losing parties (in a sense). If we would count __both __those "seats taken" and those__ same __"seats received," then we would be counting that__ same__ disproportionality __two__ times. But we only want to count that disproportionality __once__, so we halve the sum of the squares (divide it by __two__).

__same__

__same__

__two__

__two__

####

3. Why is there a square root done at the very end?

####

Because it reverses the exponential effect of all the squaring that was done earlier in the Gallagher calculation. This is done to make the final answer number more similar to the
numbers it was derived from -- namely the percentage
differences in the "differences" column.

####

The "exponential effect" is shown here: 2x2=4, but 3x3=9. Comparing 4 to 9 is an exponentially larger difference than comparing 2 to 3. To undo that particular
"exponential" effect of all the squaring we did earlier in the calculation, we simply do a square root at the end of the calculation (after the initial squaring has finished serving its purpose of converting all numbers into positive numbers).

####

4. The rules for federal elections __in Canada__ require that certain provinces always get a certain quantity of seats - __on a province by province basis__. If so, then the Gallagher index for Canada ought to ALSO reflect that. In other words, the Gallagher data should be collected on a province by province basis; and the Gallagher score should be calculated on a province by province basis. Only after that is done, can we then add up all of those provincial scores and then average them out to get the true national "composite Gallagher index" score. Agree?

####

Yes. And if we do that, then the above table calculation of 12 __for Canada __is incorrect. It should instead show a "composite Gallagher index" of 17.1. Byron Weber Becker developed this index.

#### 5. What level of math do I need to understand the Gallagher Index?

#### Grade 8: Practice with squares and square roots together is here, and here in equations.

**L****E****ARN MO**__ RE__ at these links (listed from "easy" to "hard" ...sort of):

- What is the Gallagher Index?

- The Gallagher Index: A measure of Disproportionality (a Google Doc)

- Composite Gallagher Index in detail - and much more - at Byron Weber Becker's Elections Modelling website (for Canada)

- English Wikipedia entry for the Gallagher Index

- Michael Gallagher's work on Electoral Systems at Trinity College Dublin (see this subtitle: "**Calculate the indices for any election")**

- a more general link to Gallagher's work on "least squares index"

__ Other Useful links__ (

__not__listed from "easy" to "hard"):

- Fair Vote Canada

- Représentation équitable au Canada

- Wikipédia en français - Indice de Gallagher

- List of Recommendations from the Canadian Parliamentary Committee on Electoral Reform. Recommendation #1 mentions the Gallagher Index

More on Byron Weber Becker - Overview of Simulations

Another way to measure fairness in electoral systems is to measure the proportion of the voting power of __ individuals__, as opposed to the proportion of the power of

__. There are three ways to measure that voting power of individuals:__

**parties**1. Representation Metric: the percentage of voters represented by an MP for whom they voted

2. Legislative Power Share (LPS) Score: the share of legislative voting power held by individual voters relative to their ‘fair share’

3. Legislative Power Disparity Index: The distribution of legislative power among voters

To learn more visit this blog post called, "Exploring Strengths in The Charter Challenge for Fair Voting and the Affidavit of Antony Hodgson."

Another way to learn more detail is to visit the Evidence page of the Canadian Charter Challenge for Fair Voting at this link. Then download the PDF of the Fair Voting BC affadavit.