Article: The Unrealized Horrors of Population Explosion

The original New York Times article ripping Paul Ehrlich to shreds (with video!)

Hat tip: Paul Ehrlich: Even Worse than the New York Times Says He Is

Yet another moral panic [overpopulation is going to kill us all!].

The Great Campus Rape Hoax [Updated]

Article: The great campus rape hoax

Americans have been living through an enormously sensationalized college rape hoax, but as the evidence accumulates it's becoming clear that the entire thing was just a bunch of media hype and political opportunism.

Claimed: A female college student runs a 1 in 5 chance, or 20% of being raped during her 4 years at college. (And even the researchers who came up with that number say it should not be used as it has been.)

Reality #1: the rate of rape and sexual assault for college students is 6.1 per 1,000, or 0.6%.

Reality #2: the rate of rape and sexual assault for non-students is 7.6 per 1,000.

Reality #3: the rate of rape and sexual assault has been dropping, both on campus and off, for decades.

While the Left, with its SJW allies, are using this bogus statistic, it needs to be mentioned that America is subject to periodic moral panics: demon rum, cocaine (in the early 1900's and again in the 1970's), dope fiends (1930's and 1960's), satanism at day care centers, the Catholic Church pedophile scandals (overlooking the public school pedophile scandals), and now "rape culture."

This does not even include such panics as DDT, alar, the uninsured, GMOs (and other organic food related panics), the anti-vaxxers, and the Christian Proctor and Gamble hysteria of the 1980's.

Update: More College Rape Hype — This Time from the Washington Post

Article: Why Most Published Science Studies Are Wrong

A simple idea underpins science: “trust, but verify”. Results should always be subject to challenge from experiment. That simple but powerful idea has generated a vast body of knowledge. Since its birth in the 17th century, modern science has changed the world beyond recognition, and overwhelmingly for the better.

[snip]

Little wonder that one in three researchers knows of a colleague who has pepped up a paper by, say, excluding inconvenient data from results “based on a gut feeling”. 

[snip]

And as more research teams around the world work on a problem, the odds shorten that at least one will fall prey to an honest confusion between the sweet signal of a genuine discovery and a freak of the statistical noise. Such spurious correlations are often recorded in journals eager for startling papers. 

[snip]

Some government funding agencies, including America’s National Institutes of Health, which dish out $30 billion on research each year, are working out how best to encourage replication.

I started this blog back in June. I have deliberately sought out research that 1) contradicted the "received" and politically correct narrative and/or 2) "research" that is obviously bogus.

The paper reports between 75-90% of research findings could not be "replicated" (the gold-standard of research). That is, 75-90% of published research is bunk.

One of my favorite targets have been research focusing on global warming. It is obvious why this has been such an easy target for someone who actually thinks about the research, rather than repeat talking points.

Anything people, government and money touches, they corrupt. And $30 billion pays for a lot of corruption. I do not mean corruption in the sense of bribes. I mean paying for biases. Research that produces the correct answers get rewarded.

Michael Mann of Penn State is considered a major player in the field of climate change, yet the "hockey stick" research was full of cherry-picked data ("...One in three researchers knows of a colleague who has pepped up a paper by, say, excluding inconvenient data"). He has been called a fraud, though not in the technical and legal sense such as the convicted swindler, Bernie Madoff.

US badly informed by media. Media is appalled.

Article: Get your facts right: Italy, U.S. come bottom in modern life survey

Americans think that 32% of the people in the country are immigrants (no, it is 13%).

Americans think that 24% of girls aged 15-19 give birth each year (no, it is 3%).

Americans think that 15% of the people in the country are Muslims (no, it is 1%).

Elsewhere, it has been shown that Americans think that the proportion of people in the US who are homosexual is 10-15% or higher. The real number is about 3%.

Wow! Americans sure are dumb!

Actually, not.

Americans are mis-informed. Badly misinformed. Badly misinformed by the media.

Badly misinformed by a media whose coverage of many topics is often hysterical. And by "media" here, I mean broadcast and cable entertainment shows, too.

And by hysterical, I mean relentless coverage of some topics, like immigration and teen pregnancies. The shear overwhelming number of stories on these subjects makes people think the issue is bigger than it is.

Worse, article after article attacks (usually) whatever is viewed as the "conservative" or
"Republican" position. So there is a tendency to over-emphasize certain aspects: "Immigrants are wonderful! Look at all the happy children!" "Global warming is going to kill us all! Evil deniers are in the pay of the oil companies!"

The result is an intelligent populace bombarded by stupid.

Article: History Of Autism And Vaccines: How One Man Unraveled The World’s Faith In Vaccinations

Nice info-graphic covering most of the FAQ.

Take one, now-discredited and "struck off" quack in the UK. Add an ambulance chasing lawyer (who financed the "research" and then harvested the lawsuits), some crackpot starlets and a minor scion of a once prominent political family. Stir in fear-mongering headlines. And the anti-vax, anti-science movement has the blood of thousands of children on their hands.

GET YOUR CHILDREN VACCINATED.

Hiring in STEM and gender bias

Article: New research proves gender bias extraordinarily prevalent in science, technology, engineering and math fields
     Written by Ernesto Reuben, assistant professor of management at Columbia Business School.

Obligatory acknowledgment: Yes, men vastly outnumber women in the STEM fields.

Real title #1: Researcher cannot tell the difference between fantasy and reality. Claims "bias extraordinarily prevalent."

Summary:

With everyone from the federal government to corporate America working to encourage more women to pursue careers in science, technology, engineering and math fields, you would think the doors would be wide open to women of all backgrounds. A new study shows that this could not be further from the truth and that gender bias among hiring managers in STEM fields is extraordinarily prevalent.

This is the experiment:

To test the biases of hiring managers, Reuben and his research partners designed an experiment in which about 150 participants, in the role of job candidates, would be hired to perform a math assignment: correctly summing as many sets of four two-digit numbers as possible over a period of four minutes. Previous studies have shown that this type of arithmetic task is performed equally well by men and women. All of the candidates completed the task and were given their scores. In some versions of the experiment, the candidates were allowed to tell the managers how well they had performed, while in others their test results were not revealed.

Close to 200 other subjects, in the role of hiring managers, decided whether to hire a particular candidate to perform the task. The hiring managers also completed computer-based behavioral testing that indicated the degree to which they held stereotypes about the performance of men and women in science and math.

Do you see the flaw?

The author claims that bias exists in hiring in the real world. But they do not use real world hiring managers. They used "subjects," probably college students. And since the research was done at a business school, the subjects may not have even been STEM students. Potentially, the "hiring managers" might not even know many STEM women.

Real title #2: Researcher finds bias against women STEM workers in college students at elite university.

Actually, they did find bias at all. What they found was that the "hiring managers" had stereotypes that they acted on. "Bias" implies that the "hiring managers" were acting out of dislike or deliberate unfairness. So...

Real title #3: Researcher finds that college students at elite university have stereotypes about female STEM workers.

But real world "hiring managers" are trained NOT to be biased. They are legally forced to be unbiased. A real "hiring manager" behaving this way would lose his/her job. And the human resource director he/she might report to would not/could not tolerate it.

What is poverty in the US?

Article: Air Conditioning, Cable TV, and an Xbox: What is Poverty in the United States Today?

One of the key points in the article is that Americans confuse "poverty" (which has a political definition) with destitution. Very few people in the US are actually destitute. And most of those in poverty are as well off as the middle classes in Europe.

Abstract: For decades, the U.S. Census Bureau has reported that over 30 million Americans were living in “poverty,” but the bureau’s definition of poverty differs widely from that held by most Americans. In fact, other government surveys show that most of the persons whom the government defines as “in poverty” are not poor in any ordinary sense of the term. The overwhelming majority of the poor have air conditioning, cable TV, and a host of other modern amenities. They are well housed, have an adequate and reasonably steady supply of food, and have met their other basic needs, including medical care. Some poor Americans do experience significant hardships, including temporary food shortages or inadequate housing, but these individuals are a minority within the overall poverty population. Poverty remains an issue of serious social concern, but accurate information about that problem is essential in crafting wise public policy. Exaggeration and misinformation about poverty obscure the nature, extent, and causes of real material deprivation, thereby hampering the development of well-targeted, effective programs to reduce the problem.

The article:  What is poverty in the US today?
The authors of the article make a distinction between poverty and destitution. Poverty is, essentially, an arbitrary line, a political construct. Destitution is what most people think the word poverty means, but is not what our political definitions of poverty mean.

Although the public equates poverty with physical deprivation, the overwhelming majority of poor households do not experience any form of physical deprivation. Some 70 percent of poor households report that during the course of the past year, they were able to meet “all essential expenses,” including mortgage, rent, utility bills, and important medical care. 

It is widely supposed that the poor are unable to obtain medical care, but in reality, only 13 percent of poor households report that a family member needed to go to a doctor or hospital at some point in the prior year but was unable because the family could not afford the cost.

There is a trope on the right: in 1964 we declared war on poverty. Poverty won.

In reality, true poverty, Dickensian poverty, destitution, has been mostly defeated. And a significant amount of what is left is due to appallingly bad choices (drug and alcohol addiction) or due to psychopathology (or both). 


The Vision of the Anointed
I am currently reading The Vision of the Anointed by Thomas Sowell.

One of the oft repeated points he makes in Chapter 3 ("By the Numbers") is how the intelligentsia (the "Anointed") in the US grab "aha" statistics to make a case.

He differentiates between data/facts on one hand, and evidence on the other. While data can be evidence, evidence is usually a broader look at all the data, and involves a testable hypothesis. That is, if a government policy is put into effect, then an hypothesis about what the policy will accomplish can be used to predict which evidence will show the success or failure of a policy.

One can always find an "aha" to support a policy: facts, statistics, data, and/or anecdotes.

He also makes a point about those who are in the lowest income bracket. On page 44 he notes (and footnotes) that 80% of those in poverty in 1979 where not there in 1988. About the same number were in poverty, by only 20% of these were in poverty in both 1979 and in 1988.

People in the US move into and out of various income brackets during their life times. A recent college graduate who is doing an AmeriCorps internship may be receiving food stamps and be in poverty. It is unlikely that he or she will there in 10 years. A professional in the last 5 years of his/her working life maybe in the top 5% bracket, but no longer be in the top 20% upon retiring. A family may be doing well when both parents are working, but in the lowest 20% if one is laid off and cannot find work for a year or two. Some members of a family in the middle 20% bracket may end up in the lowest 20% after a divorce.

Anecdote
For the last 20 years of her life, my mother lived in "poverty."  She had a small income from CD's originally set up by my father before his death. She had a small social security check (small for a variety of reasons).

She also owned her own home (with A/C), a car, 2 fridges, a microwave, a dishwasher, and two TV's (both with cable). She did not want a music system; she would listen to TV-embargoed baseball games on a boombox. She lived in a retirement community, and therefore paid a homeowner's fee to take care of the house's exterior including the roof, the lawn, and the trash disposal.

Yet, because her income was so small, she was living in poverty.

(She refused to get food stamps; those were for 'poor people.')

This is the #waronwomen?

Table A-1. Time spent in detailed primary activities and percent of the civilian population engaging in each detailed primary activity category, averages per day by sex, 2013 annual averages

The table at the link is used as evidence of the #waronwomen in an article in The Atlantic.

"Household activities" (including cooking, cleaning, maintainance, yard work, etc). Men do (on average) 1.34 hours per day and women do 2.19 hours. Or women do, on average, 51 minutes more "household activities" than men do.

There are two ways "work and related activities" are reported:

1) Work and related activities, average hours per day, "for the whole population." Men do (on average) 4.2 hours per day, women do 2.77 hours. Or men do 1.43 hours per day more than women do. Put another way, men spend about 50% more time working per day, on average, in the whole population, working and non-working, than women do.

2) Work and related activities, "average hours per day for persons who engaged in the activity." Men do 8.45 hours per day and women do 7.46 hours.  Or men do a full hour of work per day more than women do, when both are working.

On other words, women spend an extra hour a day on household activities and men spend an extra hour per day working.

The author of the article above then complains that women do twice as much "caring for others" than men do; the difference being about 20 minutes a day.

This is the #waronwomen?

Yet another pernicious paradigm.

Additionally:

Generally, on average, women spend more time volunteering that men do. Except that men who do volunteer spend about 30 minutes per day more time volunteering than women do.

Men watch more TV than women do, but also engage in "sports, exercise, and recreation" more than women do.

Article: Divorce Shocker: Most Marriages Do Make It

Article: Divorce Shocker: Most Marriages Do Make It

 This is based on a book. I saw a post of this somewhere a few weeks back, so the book has been out for a while now.

The commonly used statistic for divorce in the US is 50%; that is, 50% of all US marriages end in divorce. Turns out there was never any basis for this number. Nobody ever researched the actual rate of the divorce. The 50% statistic was derived from the increase in the divorce rate in the 1970's to 1980's and extrapolated.

Various quotes:

"First-time marriages: probably 20 to 25 percent have ended in divorce on average," Feldhahn revealed. "Now, okay, that's still too high, but it's a whole lot better than what people think it is."

[I]t's even lower among churchgoers, where a couple's chance of divorcing is more likely in the single digits or teens.

Feldhahn has more shocking research: four out of five marriages are happy. That number flies in the face of the popular belief that only about 30 percent of marriages are happy.

Some observations:
1) Herbert Stein's law paraphrased, no trend that can't continue, won't.
2) No trend lasts forever. (I could not find an attribution)
3) People like to believe bad news.
4) Some people love to spread bad news.
5) "There are three types of lies: Lies, d**n lies, and statistics." This has been attributed to various wits, wags, and writers.