William M. Briggs

Statistician to the Stars!

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Be A Man


Because of this Special Report, we interrupt our regularly scheduled tour of Summa Contra Gentiles. It returns next week.

The Archdiocese of New York held its first ever men’s conference on Saturday. Your Roving Reporter was there.

It was packed. Five hundred souls stuffed into the upper reaches of Fordham University. There was less room than on a Delta Airlines flight. More than a hundred were relegated to a waiting list. Besides the comforts of the liturgies of the hours, a eucharistic procession, and a mass, there were three speakers.

Joe Klecko, ex-defensive linesman of the New York Jets, loomed over the crowd and dared anyone to disagree with him. Damon Owens, director of the Theology of the Body Institute, told us that he had “Eight children; all of them boys…except for the first seven.”

And also Timothy Cardinal Dolan, who punched up the day’s theme, Men, Be Who You Are, starting with remembering St John Paul II’s lamentation on our culture’s emphasis on “having and doing” rather than on “being.” The loss of essence. This leads to the failed philosophies of utilitarianism and pragmatism, systems where people are “judged worthy by their utility”, which might sound all right, until you consider that when people can no longer fulfill their assigned function they become “a burden, an inconvenience, and without a second thought, are disposed of.” For instance, abortion.

Dolan said a man came to him and said, “I’m gay.” “No, you’re not,” Dolan replied. “You’re a man.” We are not, and cannot be, defined by our urges, especially our sexual urges. If we are so defined, what do we make of woofies, those individuals who desire relations with (non-human) animals? Are they a breed apart? No longer men but animals themselves? And what of those with even more curious sexual desires, such as men who pretend to be women? Do these people become something other than men? Yes, says society. The loss of essence.

Now a man claims to be a woman “trapped” inside a man, or, anyway, that he is not a man in fact but instead a woman. How does this man know he is a woman? To answer that, we must first understand the terms in the proposition. To know is to assert a truth, which is easy enough. So what is woman?

Any attempt at answering that inevitably leads to inescapable scientific truths such as “A woman is a human being without a Y chromosome”, and “A woman has naturally developing breasts and certain reproductive organs: ovaries, fallopian tubes, Bartholin’s glands, and the like,” and other such propositions.

Suppose a woman develops breast cancer and subsequently has mastectomies. Nobody would say that this unfortunate lady is not a woman because of lack of breasts, because we know that in the absence of the cancer and surgery it is in the nature of a woman to have breasts. Similarly, a man having surgery to implant bags of silicone under his chest has not turned into a woman because silicone bags are not breasts.

Neither are the swellings caused by estrogen injections in males breasts. Gynecomastia does not produce “working”, which is to say, real breasts; for instance, a baby could not be fed with them. No surgery can swap two X chromosomes with an X and a Y in any, let alone every, cell in a human’s body. Some rare males have two Y chromosomes, and others are born with other abnormalities, a term which recognizes that human nature exists and its qualities are known.

Finally, for instance, a person who has an artificial heart is still a person even though it is in the nature of persons to have real hearts. The artificial heart has not “turned”—magically transformed—the person into something which is not a person, e.g. a robot.

So everybody knows what a woman is. And so everybody knows that a man pretending to be one is not one. Just as everybody knows, or should know, that there is no such thing as a “sex change” operation or treatment. You cannot change what you are. Not by desire and certainly not by artificial means.

The loss of essence, of the knowledge of nature, insists there are no differences between men and women, a preposterous proposition that contains its own refutation. We would not be able to state it without knowing—truly knowing—that it is false. We cannot be what we desire. We must be who we are. We must be men.


New Paper: Climate Consensus and ‘Misinformation’

An earlier Consensus of Doom.

An earlier Consensus of Doom.

Well, not that new after all, seeing that the peer-reviewed “Climate Consensus and ‘Misinformation': A Rejoinder to Agnotology, Scientific Consensus, and the Teaching and Learning of Climate Change” by David Legates, Willie Soon, William Briggs, and Christopher Monckton of Brenchley—the same team that brought you the peer-reviewedWhy models run hot“—has been e-vailable in Science and Education for a year and a half (pdf).

But now we have the official announcement, complete with page numbers and whatnot. Sci & Educ (2015) 24:299–318, DOI 10.1007/s11191-013-9647-9, for citation collectors.

Abstract (paragraph breaks by me):

Agnotology is the study of how ignorance arises via circulation of misinformation calculated to mislead. Legates et al. (Sci Educ 22:2007–2017, 2013) had questioned the applicability of agnotology to politically-charged debates. In their reply, Bedford and Cook (Sci Educ 22:2019–2030, 2013), seeking to apply agnotology to climate science, asserted that fossil-fuel interests had promoted doubt about a climate consensus.

Their definition of climate ‘misinformation’ was contingent upon the post-modernist assumptions that scientific truth is discernible by measuring a consensus among experts, and that a near unanimous consensus exists. However, inspection of a claim by Cook et al. (Environ Res Lett 8:024024, 2013) of 97.1 % consensus, heavily relied upon by Bedford and Cook, shows just 0.3 % endorsement of the standard definition of consensus: that most warming since 1950 is anthropogenic.

Agnotology, then, is a two-edged sword since either side in a debate may claim that general ignorance arises from misinformation allegedly circulated by the other. Significant questions about anthropogenic influences on climate remain. Therefore, Legates et al. appropriately asserted that partisan presentations of controversies stifle debate and have no place in education.

You’ve heard of the dreaded 97% Consensus. Poppycock. An exaggeration of nearly two orders of magnitude. But not a surprising error. Those who see Dissent in Science are ever positing nefarious conspiracies, secret cabals of cigar-chomping Dark Masters who can control the press, government, and their neighbors.

These hidden-forces theories are always popular with the mob, which is expected, but also in the intellectual slums of the academy, which is…also expected.

Funniest thing about this climate nonsense is the sense of supreme importance many (like our opponents in the paper) feel. Politicians feed egos of scientists and their hangers on because, for now, these folks are useful in advancing the agenda-of-the-moment. But, as always happens, manias morph and something new will capture attentions. How sad some will be when the phone stops ringing! Perhaps the mere thought of this misery is what accounts the vehemence of the debate.

Anyway, about that silly 97%: from the conclusion (first paragraphs put there by me):

It has been demonstrated that the so-called consensus view is a fabrication, contrived by asking ill-defined questions, deploying multiple definitions of the consensus hypothesis interchangeably, or perusing abstracts identified by selective search terms and not necessarily interpreted with a clear and impartial eye.

It is no less legitimate to argue that the environmental lobby and its many friends in academe have circulated misinformation, including misinformation about the existence and extent of a supposed scientific “consensus”, as it is to argue—as Bedford and Cook argue—that the fossil fuel lobby has circulated misinformation calculated to minimize the anthropogenic influence on the evolution of the climate object. It is very likely that governments, the environmental lobby, academe and the news media have spent far more on information (and perhaps on mis-information) than the fossil fuel lobby.

Those who are financially dependent upon acquiescence in whatever governments may require have found it expedient, in the absence of definitive or even of adequate scientific data and results, to manufacture a scientific consensus, at all costs, so that the “misinformation that is the focus of agnotological studies can be improperly defined as that which deviates from this consensus…

Whilst agnotology can be useful in many situations where ‘old wives tales,’ myths, and other incorrect ideas exist, the value of using agnotology in politically-charged discussions such as climate change is questionable. Since the definition of misinformation lies in the eye of the advocate of a particular viewpoint, there is a danger that agnotology may serve not to enhance discussion or learning but rather to stifle debate and silence critics…

See also the peer-reviewed Legates, D. R., Soon, W., & Briggs, W. M. (2013). Learning and teaching climate science: The perils of consensus knowledge using agnotology. Science & Education, 22, 2007–2017 (pdf).


Build Your Own Embryo DNA Kits, Because Justice


A curious statement in Guy Ringler’s “Get Ready for Embryos From Two Men or Two Women“:

…There likely will be a time when reproductive science could create an embryo from the cells of two men or two women.

Anti-gay forces will not want to hear this news, but science will continue to explore it in an attempt to explain biology. This is the role of science in our society: to improve the quality of life of all of us and to advance human equality. Scientific breakthroughs that can help two people who are committed to having children together—regardless of their sex—are inspiring developments.

Ignore the simulated, conspiratorial pathos about “Anti-gay forces” (which he used four times), and we’ll come back to the bit about explaining biology. What does Ringler say is the role of science? To improve the quality of life and to advance human equality.

That might sound wrong or incongruous, but he’s right. Increasing knowledge for the sake of knowledge was always an afterthought, an amiable side effect, of the Enlightenment. From the beginning, the stated purpose of men like Baron d’Holbach, Enlightenment leader, author of La Contagion sacrée (pdf), and Encyclopédist, was to better life. D’Holbach, and many like him, thought that goal could only be met about by removing religion, advancing some form of socialism, and lightening man’s burden. Science was to contribute to all.

Latterly, science for the sake of science has been heard from university pulpits, in part for the sake of pure knowledge, but also because ministers of scientism believe falsely that “Science” is the ultimate answer to every question. This accounts for the mania (from all sides) over evolution. Scidolators are certain sure that once all accept evolution, religion becomes a useless adaptation.

Ridiculous, of course. But it explains why Ringler thinks that tinkering with DNA will “explain” biology. It won’t, and can’t. Experimenting with creating designer babies will tell us what makes viable people and, tragically, what won’t. Insert gene X here before this time, or the life will die or be born malformed, etc. Here, as in many areas, over-confidence and the refusal to see the negative abounds.

Anyway, science will never explain biology, simply because explaining any science isn’t itself a scientific matter.

Philosophy can.

Scientism is, of course, a philosophy: though it’s an inconsistent and fundamentally broken philosophy which pretends it isn’t one. It’s a sort of evangelical Whiggish empiricism. Anything that can be tried ought to be tried. There are nothing but brute facts, brute facts which must be acknowledged and which lead to the salvation of non-existence.

Nowhere is the failure of scientism more keenly felt than when it is asked What is Man? What is the Good? What is the Best Way To Live? Answering “Science!” fails, hence the marriage with progressivism and its constant appeals to “fairness” and “equality”.

“Just like straight couples, many gay men and lesbians are eager to have a genetic relationship with their children.” Dust off those test tubes, because it would unfair to deny couples “genetic relationships”. How do you even begin to argue with such immaturity? Does Ringler not see that once we allow designer babies (which won’t stop at “couples”), it’s a short ride to government guidelines and the brave new world of Bokanovsky’s process? Does Ringler not care what the creation of a caste system (scientifically produced babies will be thought superior) will do to our culture and humanity?

Of course he cares. Whatever Ringler desires is, by progressive definition, good. His opponents who dispute his desire are not just scientifically wrong, but immoral. And that follows because denying a good is iniquitous.

But no one’s identity—be it race, gender, or sexual orientation—should ever play into the advancement of medicine. What’s important here is that we bring children into this world from a desire to love and provide a happy and healthy environment for their growth. These ingredients can be as powerfully provided by a same-sex couple as they can by heterosexuals. Studies have shown this, and I have seen it first hand in the hundreds of gay families from around the world who I’ve helped to conceive.

Medical science has transformed our society for the better in so many ways. It has helped the deaf to hear. It has cured many diseases and is pioneering the genetic targeting of agents to cure cancer. It has lengthened our lives and made them more fulfilling. And it has helped people—gay and straight, black and white, Christian, Jews, and Buddhists—to become parents.

When the time comes for two men or two women to have a biological child together, we should embrace it as another positive advancement to a happier world of fulfilled lives.

Pathos, special pleading, assumption as fact, scientism, shocking over-certainty, improper comparisons, rank zealotry, fallacy upon fallacy. Even though there are a few voices urging caution, it’s a good bet Ringler’s arguments will carry the day.



Calculating Markov Chain Stationary Distributions Is Immoral?

From the Census Bureau's  "Content Reinterview Survey: Accuracy of Data for Selected Population and Housing Characteristics as Measured by Reinterview"

From the Census Bureau’s “Content Reinterview Survey: Accuracy of Data for Selected Population and Housing Characteristics as Measured by Reinterview”

No, I don’t think so, but the Census Bureau thought (thinks?) as much.

What follows is one of the more curious emails I’ve received, describing the experiences of Juan (not his real name), who used to work at the Census. Perhaps his story proves what readers have suspected: the more time spent with statistics, the looser your grasp of reality.

I’d really like your help with this one. I’m not sure how to answer.

…I was working at the U.S. Census Bureau doing quality control on the Current Population Survey. The primary way that we checked data quality was by performing re-interviews. We would ask the same set of questions, for the same time period, from a sub-sample of the households in our monthly survey.

One day I got the bright idea that the re-interview data I had looked a lot like a Markov chain. There was possibility that a different answer was given in the re-interview than there was in the interview. Questions that had a high frequency of answers changing were considered unreliable. I had a matrix for each question showing the frequency/probability of moving from one state (answer) to another. This looked just like the transition probability matrix that I had been taught about in my first stochastics class. I remember a problem where we had to predict tomorrow’s weather based on today’s. This was exactly the same and I went about taking a limit and calculating the stationary distributions for several of the re-interview questions.

My branch chief had me run the idea by the chief statistician at the Census Bureau and his reaction was not what I was expecting. He said that calculating the stationary distribution was simulating an immoral experiment! His thought process, as best I can remember it, was that taking the limit of that matrix was simulating re-interviewing our sample households an infinite number of times which was immoral.

A couple of years later I asked a friend, who holds a PhD in Biostatistics from Harvard, about this and she agreed with the chief statistician. This seems to me like they are taking the abstract and trying to make it real which is a huge stretch for me. Is the Bayesian interpretation of this approach different? Would Bayesians have moral qualms about calculations the stationary distribution in such a situation?

I followed up with Juan and he gave me more details confirming the story. An example of how a question on race (which was mutable) heads this post. Terrific evidence that most survey data should not be taken at face value.

Markov chains are the fancy names given to certain probabilities. Juan used weather as an example. Suppose the chance of a wet day following a dry day, given some evidence, is p01, and the chance of a wet day following a wet day, given some evidence, is p11, and say, p11 > p01. Since these are probabilities, they don’t for instance tell us why wet days are more likely to follow wet than dry days; they only characterize the uncertainty.

This is a “two-state” (wet or dry) Markov chain. Of course, you can have as many states as you like (there are 6 above), and the matrix of the probability of going from one state to another, given some evidence, describes the chain. The “stationary distribution” of any chain are the calculated probabilities of how likely the system will be in any state “in the long run”. These probabilities are no longer conditional on the previous state, but they still are (obviously) on whatever evidence was used.

There is no such thing as “the long run” as in Keynes’s quip and in the directors odd idea of infinite simulations, but these stationary distributions are useful as approximations. Say we wanted to know the chance of wet day conditional only on the evidence and not on whether yesterday was wet or dry. We get that from the stationary distribution. If, for example, p11 = 0.5 and p01 = 0.1, then the stationary distribution is π(0) = 0.17 and π(1) = 0.83 (if the back of my envelope isn’t misleading me).

What Juan did was to use the evidence of questions changing answers in the sample to guess the probability of each of the answers would be given by the population as a whole, e.g. the probability of being white, etc. Understand that this final guess was based on the guess of the transition probabilities. No matter what, guessing, i.e. models, were involved.

Is modeling immoral? Those stationary distributions are deduced, i.e. they follow no matter what, from the transition probabilities. They’re there whether they’re used or not.

One possibility is that the Census is supposed to be an enumeration—no models. And thank the Lord for that. Perhaps the director thought any introduction of models breached their mandate? Doubtful, since the document which gave the table above is filled with statistical models.

There’s even a model for the table above, which attempts to do exactly what Juan did, but using another classical test (“Index of consistency”). So I’m lost. Is this yet another frequentist panic, another instance of the Deadly Sin of Reification?

What do you think?

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