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Excursions in Modern Mathematics Sixth Edition

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### Excursions in Modern MathematicsSixth Edition

### Chapter 4The Mathematics of Apportionment

### The Mathematics of Apportionment

### The Mathematics of Apportionment

### The Mathematics of Apportionment

### The Mathematics of Apportionment

### The Mathematics of Apportionment

### The Mathematics of Apportionment

Peter Tannenbaum

Making the Rounds

The Mathematics of ApportionmentOutline/learning Objectives

- To state the basic apportionment problem.
- To implement the methods of Hamilton, Jefferson, Adams and Webster to solve apportionment problems.
- To state the quota rule and determine when it is satisfied.
- To identify paradoxes when they occur.
- To understand the significance of Balanski and Young’s impossibility theorem.

4.1 Apportionment Problems

The Mathematics of Apportionment

Apportion- two critical elements

in the definition of the word

- We are dividing and assigning things.
- We are doing this on a proportional basis and in a planned, organized fashion.

A

B

C

D

E

F

Total

Population

1,646,000

6,936,000

154,000

2,091,000

685,000

988,000

12,500,000

The Mathematics of ApportionmentTable 4-3 Republic of Parador (Population by State)

The first step is to find a good unit of measurement. The most

natural unit of measurement is the ratio of population to seats.

We call this ratio the standard divisor SD = P/M

SD = 12,500,000/250 = 50,000

A

B

C

D

E

F

Total

Population

1,646,000

6,936,000

154,000

2,091,000

685,000

988,000

12,500,000

Standard quota

32.92

138.72

3.08

41.82

13.70

19.76

250

The Mathematics of ApportionmentTable 4-4 Republic of Parador: Standard Quotas for Each State (SD = 50,000)

For example, take state A. To find a state’s standard quota,

we divide the state’s population by the standard divisor:

Quota = population/SD = 1,646,000/50,000 = 32.92

The Mathematics of Apportionment

- The “states.” This is the term we will use to describe the players involved in the apportionment.
- The “seats.” This term describes the set of Midentical, indivisible objects that are being divided among the N states.
- The “populations.” This is a set of N positive numbers which are used as the basis for the apportionment of the seats to the states.

The Mathematics of Apportionment

- Upper quotas. The quota rounded down and is denoted by L.
- Lower quotas. The quota rounded up and denoted by U.
In the unlikely event that the quota is a whole number, the lower and upper quotas are the same.

4.2 Hamilton’s Method and the Quota Rule

Population

Step1

Quota

A

1,646,000

32.92

B

6,936,000

138.72

C

154,000

3.08

D

2,091,000

41.82

E

685,000

13.70

F

988,000

19.76

Total

12,500,000

250.00

The Mathematics of ApportionmentHamilton’s Method

- Step 1. Calculate each state’s standard quota.

Population

Step1

Quota

Step 2

Lower Quota

A

1,646,000

32.92

32

B

6,936,000

138.72

138

C

154,000

3.08

3

D

2,091,000

41.82

41

E

685,000

13.70

13

F

988,000

19.76

19

Total

12,500,000

250.00

246

The Mathematics of ApportionmentHamilton’s Method

- Step 2. Give to each state its lower quota.

Population

Step1

Quota

Step 2

Lower Quota

Fractional

parts

Step 3

Surplus

Hamilton

apportionment

A

1,646,000

32.92

32

0.92

First

33

B

6,936,000

138.72

138

0.72

Last

139

C

154,000

3.08

3

0.08

3

D

2,091,000

41.82

41

0.82

Second

42

E

685,000

13.70

13

0.70

13

F

988,000

19.76

19

0.76

Third

20

Total

12,500,000

250.00

246

4.00

4

250

The Mathematics of Apportionment- Step 3. Give the surplus seats to the state with the largest fractional parts until there are no more surplus seats.

The Mathematics of Apportionment

The Quota Rule

No state should be apportioned a number of seats smaller than its lower quota or larger than its upper quota. (When a state is apportioned a number smaller than its lower quota, we call it a lower-quota violation; when a state is apportioned a number larger than its upper quota, we call it an upper-quota violation.)

4.3 The Alabama and Other Paradoxes

The Mathematics of Apportionment

The most serious (in fact, the fatal) flaw of Hamilton's method is commonly know as the Alabama paradox. In essence, the paradox occurs when an increase in the total number of seats being apportioned, in and of itself, forces a state to lose one of its seats.

Population

Step 1

Step 2

Step 3

Apportionment

Bama

940

9.4

9

1

10

Tecos

9,030

90.3

90

0

90

Ilnos

10,030

100.3

100

0

100

Total

20,000

200.0

199

1

200

The Mathematics of ApportionmentWith M = 200 seats and SD = 100, the apportionment under Hamilton’s method

Population

Step 1

Step 2

Step 3

Apportionment

Bama

940

9.45

9

0

9

Tecos

9,030

90.75

90

1

91

Ilnos

10,030

100.80

100

1

101

Total

20,000

201.00

199

2

201

The Mathematics of ApportionmentWith M = 201 seats and SD = 99.5, the apportionment under Hamilton’s method

The Mathematics of Apportionment

The Hamilton’s method can fall victim to two other paradoxes called

- thepopulation paradox- when state A loses a seat to state B even though the population of A grew at a higher rate than the population of B.
- thenew-states paradox- that the addition of a new state with its fair share of seats can, in and of itself, affect the apportionments of other states.

4.4 Jefferson’s Method

The Mathematics of Apportionment

Jefferson’s Method

- Step 1. Find a “suitable” divisor D. [ A suitable or modified divisor is a divisor that produces and apportionment of exactly M seats when the quotas (populations divided by D) are rounded down.

Population

Standard Quota

(SD = 50,000)

Lower Quota

Modified Quota

(D = 49,500)

Hamilton

apportionment

A

1,646,000

32.92

32

33.25

33

B

6,936,000

138.72

138

140.12

140

C

154,000

3.08

3

3.11

3

D

2,091,000

41.82

41

42.24

42

E

685,000

13.70

13

13.84

13

F

988,000

19.76

19

19.96

19

Total

12,500,000

250.00

246

250

The Mathematics of ApportionmentJefferson’s Method

- Step 2. Each state is apportioned its lower quota.

The Mathematics of Apportionment

Bad News- Jefferson’s method can produce upper-quota violations!

To make matters worse, the upper-quota violations tend to consistently favor the larger states.

4.5 Adam’s Method

Population

Quota

(D = 50,500)

A

1,646,000

32.59

B

6,936,000

137.35

C

154,000

3.05

D

2,091,000

41.41

E

685,000

13.56

F

988,000

19.56

Total

12,500,000

The Mathematics of ApportionmentAdam’s Method

- Step 1. Find a “suitable” divisor D. [ A suitable or modified divisor is a divisor that produces and apportionment of exactly M seats when the quotas (populations divided by D) are rounded up.

Population

Quota

(D = 50,500)

Upper Quota

(D = 50,500)

Quota

(D = 50,700)

Adam’s

apportionment

A

1,646,000

32.59

33

32.47

33

B

6,936,000

137.35

138

136.80

137

C

154,000

3.05

4

3.04

4

D

2,091,000

41.41

42

41.24

42

E

685,000

13.56

14

13.51

14

F

988,000

19.56

20

19.49

20

Total

12,500,000

251

250

The Mathematics of ApportionmentAdam’s Method

- Step 2. Each state is apportioned its upper quota.

The Mathematics of Apportionment

Bad News- Adam’s method can produce lower-quota violations!

We can reasonably conclude that Adam’s method is no better (or worse) than Jefferson’s method– just different.

4.6 Webster’s Method

The Mathematics of Apportionment

Webster’s Method

- Step 1. Find a “suitable” divisor D. [ Here a suitable divisor means a divisor that produces an apportionment of exactly M seats when the quotas (populations divided by D) are rounded the conventional way.

Population

Standard Quota

(D = 50,000)

Nearest

Integer

Quota

(D = 50,100)

Webster’s

apportionment

A

1,646,000

32.92

33

32.85

33

B

6,936,000

138.72

139

138.44

138

C

154,000

3.08

3

3.07

3

D

2,091,000

41.82

42

41.74

42

E

685,000

13.70

14

13.67

14

F

988,000

19.76

20

19.72

20

Total

12,500,000

250.00

251

250

The Mathematics of ApportionmentStep 2. Find the apportionment of each state by rounding its quota the conventional way.

The Mathematics of Apportionment Conclusion

- Covered different methods to solve apportionment problems
named after Alexander Hamilton, Thomas Jefferson, John Quincy Adams, and Daniel Webster.

- Examples of divisor methods
based on the notion divisors and quotas can be modified to work under different rounding methods

The Mathematics of Apportionment Conclusion (continued)

- Balinski and Young’s impossibility theorem
An apportionment method that does not violate the quota rule and does not produce any paradoxes is a mathematical impossibility.

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