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Category: Statistics

The general theory, methods, and philosophy of the Science of Guessing What Is.

February 19, 2018 | 6 Comments

Did A Man Really Breastfeed A Baby?

Stream: Did A Man Really Breastfeed A Baby?

Something’s not right.

A paper in the journal Transgender Health reports that a man injected with a myriad of chemicals was able to temporarily breastfeed a baby.

The press is not surprisingly reporting the event uncritically. For instance, The Guardian calls the event a “breakthrough”.

There are reasons to doubt the study, however, as we shall see.

Reported Details

Here are the salient details. A thirty-year-old man desirous of breastfeeding presented at the Mount Sinai Center for Transgender Medicine and Surgery.

The man was at that time was in a “feminizing hormone regimen”, taking spironolactone, estradiol, and micronized progesterone. He was also taking occasional clonazepam for a “panic disorder”
and zolpidem for insomnia.

Presumably because of the long use of hormones, and without augmentation surgery, the man’s breasts appeared well developed.

To induce lactation, the researchers:

(1) increased estradiol and progesterone dosing to mimic high levels seen during pregnancy, (2) use of a galactogogue [a lactation-inducing drug] to increase prolactin levels, (3) use of a breast pump with the speculation that it would increase prolactin and oxytocin levels, and (4) subsequent reduction in estradiol and progesterone levels, with the intention of mimicking delivery.

Potentially Dangerous Drugs

The galactogogue was domperidone, which is now banned in the United States. The FDA said:

The serious risks associated with domperidone include cardiac arrhythmias, cardiac arrest, and sudden death. These risks are related to the blood level of domperidone, and higher levels in the blood are associated with higher risks of these events. Concurrent use of certain commonly used drugs, such as erythromycin, could raise blood levels of domperidone and further increase the risk of serious adverse cardiac outcomes.

Domperidone is used on-label as a digestive aid. A listed side effect is “swelling of the breasts or discharge from the nipple in men or women.”

The man was able to secure domperidone from Canada.

How Much Milk?

After one month of treatment, the man “was able to express droplets of milk”. His drug dosages were increased, and after three months of treatment “the patient was making 8 oz [one cup] of breast milk per day.”

The baby in question finally arrived weighing 6 pounds, 13 ounces.

Here are the reported results:

The patient breastfed exclusively for 6 weeks. During that time the child’s pediatrician reported that the child’s growth, feeding, and bowel habits were developmentally appropriate. At 6 weeks, the patient began supplementing breastfeedings with 4-8 oz of Similac brand formula daily due to concerns about insufficient milk volume. At the time of this article submission, the baby is approaching 6 months old.

Suspicions

This is were the suspicion we haven’t learned the whole story begins.

Newborn babies weighing 6-7 pounds require about 14-17 ounces of breast milk per day. This is double what the paper reports the man capable of producing.

Normally developing babies at six weeks need somewhere north of 24-30 ounces of milk daily. The paper reports the baby’s diet was only then supplemented by 4-8 ounces of formula. This means the man must have consistently been producing at least 20 ounces of milk per day!

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Pull up a bottle, and click here to read the rest.

February 16, 2018 | 9 Comments

Science Says It’s Better To Be Single

The headline reads “It’s better to be single, study finds.

The study is the peer-reviewed paper “Does singlehood isolate or integrate? Examining the link between marital status and ties to kin, friends, and neighbors” by Natalia Sarkisian and Naomi Gerstel.

The recent news report summarized the paper.

It turns out, if you’re single, you probably hold stronger social bonds that help people.

Marriage can constrain people socially, and is not always the happy ending we perceive it to be — and a study, published in 2015, has supported that notion.

Sarkisian and Gerstel discovered “Being single increases the social connections of both women and men.” We might translate this as: Married couples on average stay at home with their kids more often than single people.

The big conclusion—confirmed with wee p-values!—is this: “We find that single individuals are more likely to frequently stay in touch with, provide help to, and receive help from parents, siblings, neighbors, and friends than the married.”

Uh huh. And who is taking care of the kids, the single people or the married? Does it take any time at all to raise young’uns? Of course, single people, mainly women, do raise kids but not as often as the married.

Their “finding” apparently shocked some researchers. One “Putnam (2000)…expected to find that marriage would increase interactions with friends and neighbors, was surprised to discover the reverse and wrote, ‘Married people tend to be homebodies’.”

Golly.

We have to keep our eye on the clever Putnam. He (she?) theorized, “Getting a job outside the home has two opposing effects on community involvement—it increases opportunities for making new connections and getting involved, while at the same time it decreases time available for exploring those opportunities.'”

I hope you are taking notes.

We finally arrive at the what-about-the-children question with this stunner: “Children, needing time and affection, may cause parents to cut back on other relationships and activities.”

May.

Well, fine. So what. Why bother picking on this study? It is silly and unworthy of comment. Except that this kind of thing increases scientism of the first kind, which is the false belief that nothing can be known to be true until it has been “proved” true by science.

And because, once having indulged in this error, scientists fall into the second, which is supposing their opinions on matters of morals and culture carry more weight than civilians’. Scientism of the first kind leads to scientism of the second kind, which is theorizing.

This does not imply all theories are wrong. For instance:

Universal explanations suggest that the link between marriage and community ties is invariant, as it is based in the very nature of human coupling. Such explanations would, for example, suggest that the married quite naturally become soul mates, drawn to and focused on each other in such a way that excludes personal ties to others. It would suggest the married are naturally and necessarily homebodies. In contrast, single individuals would naturally feel lonely if they stayed at home, so they get out more, perhaps trying to find a marital partner along the way.

This is hilariously tentative, as if it is possible there are as-yet-to-be-discovered-by-science occult forces barring married folks from having more connections outside the home.

The razor-sharp Putnam “noted that there can be a ‘dark side of social capital,’ including gangs and criminal networks. The reduction of relationships outside marriage may mean a withdrawal of the married, especially men, from dangerous networks.”

Sarkisian and Gerstel build on their theory: “We do not want to overstate: A growing proportion of Americans think marriage is becoming obsolete, and almost half of those not married say they have no plans to marry (Pew Research Center, 2010). Nevertheless, there remains significant ideological support for marriage.”

Ideological.

Aha! We’re finally near our target—the Grand Theory. Ready?

They say “the overwhelming [cultural] emphasis on the benefits of marriage and the disadvantages of singlehood, we argue, is based on an inadequate understanding and analysis of negative implications of marriage and the positive contributions of singlehood.”

This understanding “was a key part of the second-wave feminist agenda.”

There we have it: the feminist agenda. And what, pray, is that?

That we not “overlook the ways that single individuals contribute to social welfare more than the married as well as the costs that marriage imposes.”

Costs. Like reproducing?

On that subject, our authors finally pronounce that “policy makers should craft a balance of marriage-focused and marriage-neutral programs to support children.”

There is the moral equivalence between kids born in wedlock, and those born outside, as insisted upon by the second-wave feminist agenda. And the pernicious belief that “policy makers” should interfere with culture.

February 13, 2018 | 44 Comments

The Limits Of Science

The title of this article could equally well be “The limits of philosophy” or of theology, or of any intellectual endeavor. The question is: can we continue to learn indefinitely?

John Horgan at the inaptly titled Scientific American asked a similar question with his Is Science Infinite?

He thinks, and I agree, that it is “already bumping into limits”, as he wrote in his book The End of Science? (which I haven’t read). Those are our limits, and not the limits of things to know. God is boundless, but our intellects are not.

Horgan spoke to Martin Rees (ellipsis original).

Rees, speaking via Skype from Cambridge, reiterated points he made last month in “Is There a Limit to Scientific Understanding?” In that essay Rees calls [physicist David Deutsch’s book] Beginning of Infinity “provocative and excellent” but disputes Deutsch’s central claim that science is boundless. Science “will hit the buffers at some point,” Rees warns. He continues:

There are two reasons why this might happen. The optimistic one is that we clean up and codify certain areas (such as atomic physics) to the point that there’s no more to say. A second, more worrying possibility is that we’ll reach the limits of what our brains can grasp. There might be concepts, crucial to a full understanding of physical reality, that we aren’t aware of, any more than a monkey comprehends Darwinism or meteorology…Efforts to understand very complex systems, such as our own brains, might well be the first to hit such limits. Perhaps complex aggregates of atoms, whether brains or electronic machines, can never know all there is to know about themselves.

There is the danger here of scientists assuming philosophical problems can be answered via scientific explanations, and thus (of course) failing to answer them and so incorrectly announcing answers do not exist. As an example of this hubris, Horgan “asserted that scientists are running into cognitive and physical limits and will never solve the deepest mysteries of nature, notably why there is something rather than nothing.”

But excepting mistaking philosophy for science, we will still hit a wall. Barbara Tversky,
Professor Emerita of Psychology, Stanford University, hinted as such in her “last” question to Edge. “How do the limits of the mind limit our understanding?”, she asked.

Anybody who has spent any time with students knows that such limits exist, and that the limits are not just on a per-person basis, but exist for our race as a whole.

Each person has, say, forty, fifty productive years at best to learn all they are to learn, with most of that learning concentrated into half that period. It is clear that that which can be known is infinite; thus, given our built-in time limitation, we’ll never know everything. That what can be known is infinite is known to be true based on even a small experience with mathematics.

You may say that we can continue to build on what was known before, and so increase knowledge. This is true to a certain extent. But as that pile of prior knowledge grows, it takes longer and longer to get through it before one can learn new things. And even if we only have to learn part of the pile to continue advancements, any individual cannot know it all, and we as a species cannot do so forever. And forever is what is required.

Of course, I have no idea if we are anywhere near our capacity. We do at least seem near an inflection point in many sciences. But that could equally be the result of being beholden to stale ideas or the increasing politicization of various fields as a result of our lack of intelligence.

It is more than obvious that scientists need a healthy dose of philosophical training. That lack holds them back and sends them into blind alleys. Horgan:

In Switzerland I suggested that the riddle of consciousness is a synecdoche for the riddle of humanity. What are we, really? For most of our history, religion has given us the answer. We are immortal souls, children of a loving god, striving to reach heaven or nirvana. Most modern scientists reject these religious explanations, but they cannot agree on an alternative…We are clusters of neurons awash in chemicals, genes shaped by natural selection, egos keeping a lid on ids, software programs, nodes of information in a cosmic web, quantum wave functions…

It is precisely because we can never achieve total self-knowledge that we will keep seeking [the riddle of consciousness] forever.

Nope. The riddle about the what is well solved. The question of how is wide open. Not that we’ll necessarily figure it out.

February 12, 2018 | 2 Comments

What People Think Probability Words Mean

The graph above came from Github and was the result of a poll of folks on Reddit. “The raw data came from /r/samplesize responses to the following question: What [probability/number] would you assign to the phrase ‘[phrase]’?”

There are various ways of plotting the results; shown at the top is just one, a smoothed “density” estimate of the responses. Another plot (at the site) uses horizontal box plots.

Let’s think about what exactly this graph shows, and what it does not. What it does not show is what probability is. Probability is not subjective, even though it subjective answers vary to the question. That requires a clarification.

We are always interested in the probability of some proposition, and since all probability is conditional, the probability of each proposition varies depending on the premises assumed. The premises are not only those that are explicit, but those that are implicit, too. If the premises include words, which I believe is always, then the implicit premises are those that carry the definition of those words, and of grammar. These grammatical and definitional premises are always there, even if they are not formally written.

So we might ask somebody to say “What are the chances your team wins?” and he’ll say “Highly unlikely.”

Now, how he came to that judgement depends on many, many premises, most of which your friend will not be able to articulate. Depending on the situation, he’ll consider some things in depth or in brief. If it were possible to lay out all the premises upon which he relies, including all those implicit ones, then we would see we could deduce from them the “highly unlikely” answer.

The premises on which your friend relies are likely to shift in time, perhaps even rapidly. Ask him the same question a minute later, he may come to a different answer, because his premises have changed. But if we were to do the impossible and extract all of them, then we could deduce whatever his answer was.

This is not in practice possible. There are just two many premises for most questions of interest, many of which are only vaguely contemplated. Thus it will appear that probability is subjective.

The same is true when we ask people what number they would assign to words like “highly unlikely”. What [probability/number] would you assign to the phrase [phrase]?

Any number of premises, evidence, thoughts will flit through a person’s mind, perhaps including certain concrete scenarios in which the person last used the term like “highly unlikely”. Most will scarcely be able to articulate these, and thus the number that pops out will represent some kind of approximation.

What’s interesting is that we can interpret the picture of the range of answers for each phrase as a rough indicator of how people internally think of the definition and grammar of phrases. It isn’t completely that, because we cannot be certain no other premises were involved in each person’s answer. There had to be a lot of folks who said of phrases, “I don’t know. Ten percent.” Ask them again, or in the context of a concrete situation, and the number will likely change.

You can see, quelle surprise, that not all took the poll seriously, because it is difficult to defend the idea that the English phrase “highly likely” would lead to numbers around 15%. Of course, it could be that one or more persons think exactly that. Similar seeming discrepancies exist for other phrases.

Interpretations of “unlikely” are far more variable than “about even.” You may think this makes sense—it does to me—because the words “about even” almost directly map to numbers hovering around 50%. Whereas “unlikely” maps grammatically to only under 50% but not impossible.

How can you use a graph like this? One situation is if you have to make a bet, or counter bet, on the truth of some proposition. When you hear your opponent use one of these words to describe his assessment, you can use the chart as a guess to what number he might assign, and thus you might be able to gauge his commitment. But many of the phrases produces vague answers, so there will not be much profit in that strategy.

Beside that, as said, it is useful to investigating empirical grammar.