Daily Archives: October 7, 2011

Best movies for Halloween #25 Flatliners

“Philosophy failed. Religion failed. Now it’s up to the physical sciences.”

Like most scientists in horror films the characters of Flatliners think that science can reveal everything, damn the consequences…
…and be it a sci fi or horror movie that always works really well.

The movie posters had the rather cheesy catch phrase “Some lines shouldn’t be crossed.” (Terrible pun). But this goes to the heart of an the issue of should science have boundaries. And as so many horror stories came out of the Romantic era it will always be tied to the Romantic’s distrust of the arrogance of science to find all answers. And they’re not entirely wrong. The history of science, while a great story of the progress and advancement of the human race, has these dark side notes of human experimentation and only considering the consequence of one’s actions only after the after(I am confused and don’t know what you are saying here) (Oppenheimer…”I am become death…”). We see it in Frankenstein. We saw it in The Island of Dr. Moreau. We saw it throughout the X-files, Fringe, Outer Limits, and the Twilight Zone and a dozen other stories, movies and TV shows. They’re cautionary tales to remind people that science has always been and always will be a double edged sword that when misused or misunderstood can do far more damage than good. And the idea of killing yourself to scientifically see what’s on the other side of death does seem to be one of those lines science shouldn’t be so eager to go past.

In this case how would you like all of your worst sins and things your regret come back not just as memories but as tangible, physical things to torment and torture. I assume for many of us this would be a nightmare…more so for the highly flawed characters of this movie.

Now, somewhere between being a cool vampire and being the most deadly force in the history of counter-terrorism, Kieffer Sutherland played the rather arrogant and guilt-ridden character of Nelson. This character was the driving force behind these experiments of Flatliners, Nelson, is also the one most tied to death. He claims he has no fear of what is on the other side and it is just pure curiosity on his part, but he is also suffering from the buried guilt of having killed someone in his youth. In fact you find that the only other character so interested in the experiments is Julia Robert’s character, who also lost someone to death, show that their desire to know about death isn’t curiosity, it is very much the fear of not knowing what death it.

The fear of death is often tied to the fear of being judged for your actions (it’s sad people have such a limited view of God they think he is so willing to damn you). And that is what ties each of the characters of Flatliners together. Whether what happened was their fault or not, whether it was major or minor, they felt guilty about it and in this film their guilt became a physical manifestation. Now I don’t know if the writers were intentionally going for this or it’s just an interesting parallel, but this does partially match up to the idea that when you die you review your life and you the parts that you review in most detail are the ones that you are most emotionally tied to…and there are few emotions stronger than guilt. It also seems to parallel the Buddhist idea that in the afterlife one of the things you will face is the karmic consequences of your actions and if you can’t move past these (move past the guilt) then you will be forced to live through the karmic consequences of those actions in your next life (but this may be reading too much into the screenwriter’s intent).

Whatever the actual purpose the writer and director were attempting to bring out about the nature of the afterlife, they do have a fairly clear point that the way out is not death but forgiveness.

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Filed under Death, Fear, Halloween, Movies

Economic inequality hurts people…or does it?


“The Other 99%” (or I’ve also seen 98%) they don’t seem to have a lot of specific goals and ideas. But by their title alone they seem to think that because the top 1% has the majority of the wealth in the world then that clearly means that they’re the ones ruining our lives and it has nothing whatsoever to do with our choices. I think it’s fair to say that whatever the cornucopia of beliefs this movement holds; they all seem to think that the wealth should be spread around a little more. But does that work?

Well let’s look at some facts and figures.… (yes I do math so you don’t have to, you should thank me for doing something so drearily dull as this for you).

They seem to think that if the wealth were spread out just a little more that their lives would be better.

So let’s look at some common statistics before we look at the heart of their argument.

What leads to a better life?

Well the UN has some statistics on standards of living (I’m not sure if this is the best judge for what is a good life, but we’ll play in the liberal’s ballpark and use the UN’s numbers).  Now if we chart that against the average GDP for each country (numbers from the CIA Handbook), (I’ll include a long boring chart with all these figures at the end if you want to check my math) we find that, low and behold the more money you have the better the average quality of life is in any given country. (In case you want to know the better quality of life the higher the score). Not terribly surprising when you consider that one of the UN’s criteria is average GDP, but you’ll notice that that the line goes up exponentially (it curves up) rather than linearly (a straight line) thus suggesting that at some point you need more money just to get the same jump you did last time.  Thus to get to the highest standards of living you need lots of money, at least as an average GDP.

Further it would not be unreasonable to argue that there are secondary benefits, (not having to worry about debt, freedom for leisure, the joys of philanthropy–which is really dependent on having lots of money, etc) that come from extra money not shown in the UN’s standard of living numbers thus making the exact curve even more pronounced in the favor of higher GDP having numerous benefits. So in reality, if we were able to measure all the benefits provided by higher income (see video below), for every extra $10,000 you earn your quality of life better than what it is suggested by the UN data graph below.  (Or to put it another way if we had accurate data and not just UN numbers you would not see as great a level of diminishing returns, but closer to a linear progression).

But is money alone what causes a good life? Not quite because we need to answer what creates lots of money.

And for that we turn to economic liberty…you know the very thing these whiners at The Other 99% are arguing against. For that we turn to the Heritage Foundation and its yearly ranking of economic Freedom. (Again, the higher the score the more economically free).  Seems pretty clear to me that if you have economic freedom you get more money and a better standard of living. Yes, yes, yes correlation does not equal causation…but you’d have to be a damn fool to not see that they’re not related. (By the way, the United States has dropped it’s economic freedom almost every year for the last decade…you know all the while that the economy kept getting worse and worse…I’m sure one had nothing to do with the other).

Okay, so it apear to me that you need more economic freedom if you’re going to have a better life. However, maybe that’s only one interpretaion. Maybe these Other 99% people have a point. So where do we get numbers for economic inequality? Luckily the UN collects those numbers as well. They use something call the Gini coefficient–I could bore you with the math, but let’s just say that the lower the number the more wealth is concentrated in the hands of the few, and the higher the number the more the money is spread around. I’m dealing with a slightly smaller pool of countries because the UN reports do not have a complete listing for all countries (countries where a GDP of nothing is spread around equally or countires where the dictator owns everything are pretty much what makes up the majority of the list where you find no data).


If you’re looking for a straight line, you’ll find Waldo in there before you find a straight line. At most you could argue you see the a bell curve here (especially since some of the worst countries where everyone shares in poverty are not on the list and proably have Gini coefficient near 10, and GDP near 0 weren’t calculated) but that would be a very weak correlation at best. Yes you don’t want massive inequality like you would see in Saudi Arabia, but you don’t complete socialist sharing either). What you seem to want is a Gini score between 30-45 (the U.S. is at 40) but this is no guraentee of success. You’ll notice that some of the lowest countries for GDP, standard of living, and economic freedom are all in that range. Conversly if you cross a 70 score on econoimc liberty it seems literally impossible to be in a bad spot.

The distribution of wealth on the whole seems to be a very irrelevant piece of information. It doesn’t appear to be a cause of good or bad economies nor does it appear to be an effect or sign of good or bad economies. It’s a useless talking point. It doesn’t matter what portion of the pie you’re getting…it only matter how big in an abosolute sense a piece you’re getting. If you’getting only a diproportionate 1% of the U.S. eocnomy you’re doing better than most of the world currently (would you rather have your exactly equal share by population of the Somalian economy?) and certainly better than 99.999999999% of the people throughout history.

Real math seems to show that economic inequality is nothing more than a useless talking point that drummed up for class warfare purposes.

If these idiots at “The Other 99%” really cared about improving the quality of life of the 99% who aren’t among the rich, then they would be protesting government, bureaucracy, red tape, taxes and regulation…but they don’t care about that…they don’t want it better for everyone, they just want if better for them so they can sit around all day and get paid for doing nothing…that or they are obscenely bad at math.

So the next time you get into an argument that the rich control too much or that they aren’t paying their fair share and that should change (i.e. redistribute wealth and lower our economic freedom) ask them what proof they have that such a move would improve our quality of life or even average GDP. What proof do they have? Because it certainly isn’t any proof from this little thing called reality.

Country GDP per person Economic Liberty Score Standard of living
 Albania

3,900

64

0.719

 Algeria

4,600

52.4

0.677

 Angola

5,000

46.2

0.403

 Argentina

9,000

51.7

0.775

 Armenia

3,200

69.7

0.695

 Australia

57,400

82.5

0.937

 Austria

45,900

71.9

0.851

 Azerbaijan

5,800

59.7

0.713

 Bahrain

19,200

77.7

0.801

 Bangladesh

700

53

0.469

 Barbados

13,900

68.5

0.788

 Belarus

5,700

47.9

0.732

 Belgium

44,700

70.2

0.867

 Belize

4,400

63.8

0.694

 Benin

700

56

0.435

 Bolivia

1,900

50

0.643

 Bosnia and Herzegovina

3,600

57.5

0.71

 Botswana

6,900

68.8

0.633

 Brazil

10,400

56.3

0.699

 Bulgaria

6,700

64.9

0.743

 Burkina Faso

500

60.6

0.305

 Burma

800

37.8

0.451

 Burundi

200

49.6

0.282

 Cambodia

800

57.9

0.494

 Cameroon

1,200

51.8

0.46

 Canada

46,600

80.8

0.888

 Cape Verde

3,200

64.6

0.534

 Central African Republic

400

49.3

0.315

 Chad

700

45.3

0.295

 Chile

12,100

77.4

0.783

 China, People’s Republic of

4,400

52

0.663

 Colombia

6,500

68

0.689

 Comoros

800

43.8

0.428

 Congo, Democratic Republic of the

200

40.7

0.239

 Costa Rica

7,900

67.3

0.725

 Croatia

13,500

61.1

0.767

 Cuba

5,200

27.7

0.76

 Cyprus

21,000

73.3

0.81

 Czech Republic

18,800

70.4

0.841

 Denmark

56,300

78.6

0.866

 Djibouti

1,500

54.5

0.402

 Dominican Republic

5,300

60

0.663

 Ecuador

4,000

47.1

0.695

 Egypt

2,700

59.1

0.62

 El Salvador

3,600

68.8

0.659

 Equatorial Guinea

22,300

47.5

0.538

 Estonia

15,300

75.2

0.812

 Ethiopia

300

50.5

0.328

 Fiji

3,600

60.4

0.669

 Finland

45,500

74

0.871

 France

39,900

64.6

0.872

 Gabon

8,500

56.7

0.648

 Georgia

2,500

70.4

0.698

 Germany

40,600

71.8

0.885

 Ghana

1,300

59.4

0.467

 Greece

28,400

60.3

0.855

 Guatemala

3,100

61.9

0.56

 Guinea

400

51.7

0.34

 Guinea-Bissau

500

46.5

0.289

 Guyana

3,000

49.4

0.611

 Haiti

700

52.1

0.404

 Honduras

1,900

58.6

0.604

 Hong Kong

31,700

89.7

0.862

 Hungary

12,900

66.6

0.805

 Iceland

40,800

68.2

0.869

 India

1,300

0.519

 Indonesia

2,900

56

0.6

 Iran

4,600

42.1

0.702

 Ireland

44,200

78.7

0.895

 Israel

29,000

68.5

0.872

 Italy

33,800

60.3

0.854

 Jamaica

4,800

65.7

0.688

 Japan

42,800

72.8

0.884

 Jordan

4,300

68.9

0.681

 Kazakhstan

8,100

62.1

0.714

 Kenya

800

57.4

0.47

 Korea, South

20,700

69.8

0.877

 Kuwait

51,600

64.9

0.771

 Kyrgyzstan

800

61.1

0.598

 Laos

1,000

51.3

0.497

 Latvia

10,800

65.8

0.769

 Lesotho

1,100

47.5

0.427

 Liberia

300

46.5

0.3

 Libya

11,500

38.6

0.755

 Lithuania

10,300

71.3

0.783

 Luxembourg

110,400

76.2

0.852

 Macedonia, Republic of

4,400

66

0.701

 Madagascar

400

61.2

0.435

 Malawi

300

55.8

0.385

 Malaysia

8,400

66.3

0.744

 Maldives

4,700

48.3

0.602

 Mali

700

56.3

0.309

 Malta

20,400

65.7

0.815

 Mauritania

1,200

52.1

0.433

 Mauritius

7,500

76.2

0.701

 Mexico

9,200

67.8

0.75

 Micronesia, Federated States of

2,200

50.3

0.614

 Moldova

1,600

55.7

0.623

 Mongolia

2,000

59.5

0.622

 Montenegro

6,000

62.5

0.769

 Morocco

3,300

59.6

0.567

 Mozambique

400

56.8

0.284

 Namibia

5,600

62.7

0.606

 Nepal

500

50.1

0.428

 New Zealand

33,000

82.3

0.907

 Nicaragua

1,200

58.8

0.565

 Niger

400

54.3

0.261

 Nigeria

1,300

56.7

0.423

 Norway

88,600

70.3

0.938

 Pakistan

900

55.1

0.49

 Panama

7,900

64.9

0.755

 Papua New Guinea

1,600

52.6

0.431

 Paraguay

2,900

62.3

0.64

 Peru

5,300

68.6

0.723

 Poland

12,200

64.1

0.795

 Portugal

21,400

64

0.795

 Qatar

75,300

70.5

0.803

 Romania

7,400

64.7

0.767

 Russia

10,500

50.5

0.719

 Rwanda

500

62.7

0.385

 Saudi Arabia

17,200

66.2

0.752

 Senegal

1,000

55.7

0.411

 Serbia

5,300

58

0.735

 Sierra Leone

400

49.6

0.317

 Singapore

43,300

87.2

0.846

 Slovakia

16,000

69.5

0.818

 Slovenia

23,900

64.6

0.828

 Solomon Islands

1,300

45.9

0.494

 South Africa

7,300

62.7

0.597

 Spain

30,300

70.2

0.863

 Sri Lanka

2,400

57.1

0.658

 Suriname

6,700

53.1

0.646

 Swaziland

2,600

59.1

0.498

 Sweden

50,200

71.9

0.885

 Switzerland

68,700

81.9

0.874

 Syria

2,700

51.3

0.589

 Taiwan (Republic of China)

18,700

70.8

0.868

 Tajikistan

800

53.5

0.58

 Tanzania

500

57

0.398

 Thailand

4,800

64.7

0.654

 Timor-Leste

500

42.8

0.502

 Togo

500

49.1

0.428

 Tonga

3,400

55.8

0.677

 Trinidad and Tobago

16,800

66.5

0.736

 Tunisia

4,200

58.5

0.683

 Turkey

9,500

64.2

0.679

 Turkmenistan

5,700

43.6

0.669

 Uganda

500

61.7

0.422

 Ukraine

3,000

45.8

0.71

 United Arab Emirates

60,700

67.8

0.815

 United Kingdom

36,000

74.5

0.849

 United States

47,600

77.8

0.902

 Uruguay

12,200

70

0.765

 Uzbekistan

1,400

45.8

0.617

 Venezuela

10,700

37.6

0.696

 Vietnam

1,200

51.6

0.572

 Yemen

1,300

54.2

0.439

 Zambia

1,200

59.7

0.395

 Zimbabwe

600

22.1

0.14

Country UN Gini Score GDP per person Economic Liberty Score Standard of living
 Albania

31.1

3,900

64

0.719

 Algeria

35.3

4,600

52.4

0.677

 Argentina

48.8

9,000

51.7

0.775

 Armenia

33.8

3,200

69.7

0.695

 Australia

35.2

57,400

82.5

0.937

 Austria

29.1

45,900

71.9

0.851

 Azerbaijan

36.5

5,800

59.7

0.713

 Bangladesh

33.4

700

53

0.469

 Belarus

29.7

5,700

47.9

0.732

 Belgium

33

44,700

70.2

0.867

 Benin

36.5

700

56

0.435

 Bolivia

57.2

1,900

50

0.643

 Bosnia and Herzegovina

26.2

3,600

57.5

0.71

 Botswana

60.5

6,900

68.8

0.633

 Brazil

49.3

10,400

56.3

0.699

 Bulgaria

29.2

6,700

64.9

0.743

 Burkina Faso

39.5

500

60.6

0.305

 Burundi

42.4

200

49.6

0.282

 Cambodia

41.7

800

57.9

0.494

 Cameroon

44.6

1,200

51.8

0.46

 Canada

32.6

46,600

80.8

0.888

 Central African Republic

61.3

400

49.3

0.315

 Chile

52

12,100

77.4

0.783

 China (PRC)

46.9

4,400

52

0.663

 Colombia

58.5

6,500

68

0.689

 Costa Rica

48.9

7,900

67.3

0.725

 Croatia

29

13,500

61.1

0.767

 Czech Republic

25.4

18,800

70.4

0.841

 Denmark

24.7

56,300

78.6

0.866

 Dominican Republic

50

5,300

60

0.663

 Ecuador

54.4

4,000

47.1

0.695

 Egypt

34.4

2,700

59.1

0.62

 El Salvador

46.9

3,600

68.8

0.659

 Estonia

35.8

15,300

75.2

0.812

 Ethiopia

30

300

50.5

0.328

 Finland

26.9

45,500

74

0.871

 France

32.7

39,900

64.6

0.872

 Georgia

40.4

2,500

70.4

0.698

 Germany

28.3

40,600

71.8

0.885

 Ghana

40.8

1,300

59.4

0.467

 Greece

34.3

28,400

60.3

0.855

 Guatemala

53.7

3,100

61.9

0.56

 Guinea

38.6

400

51.7

0.34

 Guinea-Bissau

47

500

46.5

0.289

 Haiti

59.5

700

52.1

0.404

 Honduras

55.3

1,900

58.6

0.604

 Hong Kong

43.4

31,700

89.7

0.862

 Hungary

26.9

12,900

66.6

0.805

 India

36.8

1,300

0.519

 Indonesia

34.3

2,900

56

0.6

 Iran

43

4,600

42.1

0.702

 Ireland

34.3

44,200

78.7

0.895

 Israel

39.2

29,000

68.5

0.872

 Italy

36

33,800

60.3

0.854

 Jamaica

45.5

4,800

65.7

0.688

 Japan

24.9

42,800

72.8

0.884

 Jordan

38.8

4,300

68.9

0.681

 Kazakhstan

33.9

8,100

62.1

0.714

 Kenya

42.5

800

57.4

0.47

 Kyrgyzstan

30.3

800

61.1

0.598

 Laos

34.6

1,000

51.3

0.497

 Latvia

37.7

10,800

65.8

0.769

 Lesotho

63.2

1,100

47.5

0.427

 Liberia

52.6

300

46.5

0.3

 Lithuania

36

10,300

71.3

0.783

 Macedonia

39

4,400

66

0.701

 Madagascar

47.5

400

61.2

0.435

 Malawi

39

300

55.8

0.385

 Malaysia

49.2

8,400

66.3

0.744

 Mali

40.1

700

56.3

0.309

 Mauritania

39

1,200

52.1

0.433

 Mexico

51.6

9,200

67.8

0.75

 Moldova

33.2

1,600

55.7

0.623

 Mongolia

32.8

2,000

59.5

0.622

 Morocco

39.5

3,300

59.6

0.567

 Mozambique

47.3

400

56.8

0.284

 Namibia

74.3

5,600

62.7

0.606

 Nepal

47.2

500

50.1

0.428

 New Zealand

36.2

33,000

82.3

0.907

 Nicaragua

52.3

1,200

58.8

0.565

 Niger

50.5

400

54.3

0.261

 Nigeria

43.7

1,300

56.7

0.423

 Norway

25.8

88,600

70.3

0.938

 Pakistan

30.6

900

55.1

0.49

 Panama

54.9

7,900

64.9

0.755

 Papua New Guinea

50.9

1,600

52.6

0.431

 Paraguay

53.2

2,900

62.3

0.64

 Peru

50.5

5,300

68.6

0.723

 Poland

34.5

12,200

64.1

0.795

 Portugal

38.5

21,400

64

0.795

 Romania

31

7,400

64.7

0.767

 Russia

39.9

10,500

50.5

0.719

 Rwanda

46.8

500

62.7

0.385

 Senegal

41.3

1,000

55.7

0.411

 Sierra Leone

62.9

400

49.6

0.317

 Singapore

42.5

43,300

87.2

0.846

 Slovakia

25.8

16,000

69.5

0.818

 Slovenia

28.4

23,900

64.6

0.828

 South Africa

57.8

7,300

62.7

0.597

 South Korea

31.6

20,700

69.8

0.877

 Spain

34.7

30,300

70.2

0.863

 Sri Lanka

40.2

2,400

57.1

0.658

 Swaziland

50.4

2,600

59.1

0.498

 Sweden

25

50,200

71.9

0.885

 Switzerland

33.7

68,700

81.9

0.874

 Tajikistan

32.6

800

53.5

0.58

 Tanzania

34.6

500

57

0.398

 Thailand

42

4,800

64.7

0.654

 Trinidad and Tobago

38.9

16,800

66.5

0.736

 Tunisia

39.8

4,200

58.5

0.683

 Turkey

41.2

9,500

64.2

0.679

 Turkmenistan

40.8

5,700

43.6

0.669

 Uganda

45.7

500

61.7

0.422

 Ukraine

28.1

3,000

45.8

0.71

 United Kingdom

36

36,000

74.5

0.849

 United States

40.8

47,600

77.8

0.902

 Uruguay

47.1

12,200

70

0.765

 Uzbekistan

36.8

1,400

45.8

0.617

 Venezuela

49.5

10,700

37.6

0.696

 Vietnam

34.4

1,200

51.6

0.572

 Yemen

33.4

1,300

54.2

0.439

 Zambia

50.8

1,200

59.7

0.395

 Zimbabwe

50.1

600

22.1

0.14

33

70.8

0.868

30 Comments

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