Faster Evolution Means More Ethnic Differences

Russian scientists showed in the 1990s that a strong selection pressure (picking out and breeding only the tamest fox pups in each generation) created what was — in behavior as well as body — essentially a new species in just 30 generations. That would correspond to about 750 years for humans. Humans may never have experienced such a strong selection pressure for such a long period, but they surely experienced many weaker selection pressures that lasted far longer, and for which some heritable personality traits were more adaptive than others. It stands to reason that local populations (not continent-wide “races”) adapted to local circumstances by a process known as “co-evolution” in which genes and cultural elements change over time and mutually influence each other.


How To Think Real Good

Via All of the following are quotes from the article that, in general, appeal to my priors. All emphasis in original, which you should read in its entirety.

The implicit assumption is that the problem Bayesianism solves is most of rationality, and if I’m unimpressed with Bayesianism, I must advocate some other solution to that problem. I do have technical doubts about Bayesianism, but that’s not my point. Rather, I think that the problem Bayesianism addresses is a small and easy one.

– Bayesianism is a theory of probability.

– Probability is only a small part of epistemology.

– Probability is only a small part of rationality.

– Probability is a solved problem. It’s easy. The remaining controversies in the field are arcane and rarely have any practical consequence.

My answer to “If not Bayesianism, then what?” is: all of human intellectual effort.

* * *

Understanding informal reasoning is probably more important than understanding technical methods.

* * *

Many of the heuristics I collected for “How to think real good” were about how to take an unstructured, vague problem domain and get it to the point where formal methods become applicable. … Finding a good formulation for a problem is often most of the work of solving it.

* * *

Suppose you want to understand the cause of manic depression. For every grain of sand in the universe, there is the hypothesis that this particular grain of sand is the sole cause of manic depression. Finding evidence to rule out each one individually is impractical. … [T]here is an infinite list of logically possible causes. … We can’t even imagine them all, much less evaluate the evidence for them. So:

Before applying any technical method, you have to already have a pretty good idea of what the form of the answer will be.

* * *

Choosing a good vocabulary, at the right level of description, is usually key to understanding.

* * *

1. A successful problem formulation has to make the distinctions that are used in the problem solution.

2. A successful problem formulation has to make the problem small enough that it’s easy to solve.

* * *

It’s important to understand that problem formulations are never right or wrong.

Truth does not apply to problem formulations; what matters is usefulness.

In fact,

All problem formulations are “false,” because they abstract away details of reality.

* * *

[I]f you don’t know the solution to a problem, how do you know whether your vocabulary makes the distinctions it needs? The answer is: you can’t be sure; but there are many heuristics that make finding a good formulation more likely. Here are two very general ones:

Work through several specific examples before trying to solve the general case. Looking at specific real-world details often gives an intuitive sense for what the relevant distinctions are.

Problem formulation and problem solution are mutually-recursive processes.

You need to go back and forth between trying to formulate the problem and trying to solve it.

* * *

If a problem seems too hard, the formulation is probably wrong. Drop your formal problem statement, go back to reality, and observe what is going on.

* * *

Learn from fields very different from your own. They each have ways of thinking that can be useful at surprising times. Just learning to think like an anthropologist, a psychologist, and a philosopher will beneficially stretch your mind.

If you only know one formal method of reasoning, you’ll try to apply it in places it doesn’t work.

* * *

– Figuring stuff out is way hard.

– There is no general method.

– Selecting and formulating problems is as important as solving them; these each require different cognitive skills.

– Problem formulation (vocabulary selection) requires careful, non-formal observation of the real world.

– A good problem formulation includes the relevant distinctions, and abstracts away irrelevant ones. This makes problem solution easy.

– Little formal tricks (like Bayesian statistics) may be useful, but any one of them is only a tiny part of what you need.

– Progress usually requires applying several methods. Learn as many different ones as possible.

– Meta-level knowledge of how a field works—which methods to apply to which sorts of problems, and how and why—is critical (and harder to get).

Cholesterol Is Not Bad For You; or, The 8 Stages Of Science Scams

1) it is propagated by scientists on a non-scientific mission

2) it is believed because it plausibly explains an observation (increasing global temperature [for a time], increasing heart attacks from smoking in the 1950s and 60s). It taps into large anxieties about too much wealth, too much happiness, in western societies. There must be sin somewhere, and the public is ready to flog itself in the cause of a secularized idea of God, uh, I mean Good.

3) the causal relationship is weaker than first supposed; the research is found to be sloppy, the facts have been fudged, subsequent studies do not fully support the original claims, nevertheless the orthodoxy is promulgated all the more harshly for being doubted.

4) by now, powerful economic and ideological interests have taken hold. They supply an ongoing source of funds and opinion to ensure the perpetuation of the alarm: in the case of cholesterol, the margarine industry, the pharmaceutical industry, and the medical establishment, and in the case of AGW, the tribe of bureaucrats and leftists who seek to control markets, whose god of Marxism had failed, and who needed a new god (Gaia) to justify their rule.

5) The skeptics who have patiently argued on the basis of facts that the science of each phenomenon was weak, are ostracized by the opinion establishments of medicine and global warming. Cranks, but the cranks are right and the orthodox priests and Levites are wrong.

6) Eventually, after fifty or sixty years, the subject of discussion just changes. In the case of cholesterol, the evidence gets weaker and weaker, and the problems caused by too much sugar consumption (obesity, diabetes), caused in part by people not eating enough fats and meats, reaches a stage where it can no longer be ignored.

7) the retreat of the orthodoxy is covered by a smokescreen of fresh concerns for some other catastrophe. No admissions of error or apologies for wrecked careers and following bad science are ever issued. Time flows on, bringing neither knowledge nor greater understanding of the role of folly in human affairs.

8) stages 6 and 7 have been reached in the cholesterol cycle; they are beginning in the anthropogenic global warming scam. Fifty years from now, there will still be clanking windmills in the North Sea, but whether they will be still linked to a power grid is less likely, and whether anyone will pay attention is doubtful. The lobbies that keep them there, however, will still exist.

Source: RIP: The great cholesterol scam (1955 – 2015) – Barrel Strength

The Varieties of Scientific Experience

I liked this mostly because it exposes a lot of “fans or science” as mostly tribal, not as actual adherents to a methodology or approach. The varieties are:

– Science as Method

– Science as Production and Stewardship

– Science as Authority

– Science as Belonging

– Science as “Progress”

– Science as Aesthetic

– Science as Dispassionate Sensibility

– Science as Nihilism

– Non-Experience of Science

Via The Varieties of Scientific Experience.

The “Hollaback” Video: Facts Are Meaningless Without A Theory

The Hollaback video also shows why “data” without theory can be so misleading—and how the same data can fit multiple theories. Since all data collection involves some form of data selection (even the biggest dataset has selection going into what gets included, from what source), and since data selection is always a research method, there is always a need for understanding methods.

The important methodological point is that the video, without further reflection, can support all three wildly incompatible propositions. In other words, if you just look at the video, you can believe any three, and you will likely choose whichever fits your existing conclusions and prejudices.

This is a point that Drucker made decades ago: Events by themselves are not facts. … Opinions come first. “Facts” mean nothing without a lens through which to view them. All the data in the world is meaningless without a world-view to interpret them. You have to recognize that your opinion, your hypothesis, your world-view, comes first, and *then* you can do something with data.

Via That Catcalling Video and Why “Research Methods” is such an Exciting Topic (Really!) — The Message — Medium.

You Think Atheists Are More Intelligent? Think Again.

A summary of Vox Popoli: Mailvox: the distribution of atheist intelligence:

– On average, atheist IQ is a little higher than theist IQ. Of course, averages are misleading, because …

– There are more high-IQ theists than high-IQ atheists.

– The majority of atheists have sub-100 IQs.

– “The two most common types of atheists are the High Church atheists with 128+ IQs and Low Church atheists with 65-72 IQs. The Low Church atheists actually outnumber the High Church atheists, 22.9 to 17.2 percent.”

– “There are 11.4x more 128+ IQ theists who either ‘know God exists’ or ‘believe God exists despite having the occasional doubt’ than there are 128+ IQ atheists who ‘don’t believe God exists.'”

See the article for an interesting set of graphs.

Part of me wonders if this accounts for the “I Love Science!” crowd, despite not actually know what science *is*, as well.

FWIW, I was raised a Methodist Christian, so I have a warm place in my heart for religion. In adulthood I became an agnostic, not an atheist, so I have no particular dog in that fight. I have not taken a formal IQ test so I do not know where I fall on that scale. I like science as a methodology, which is why I am perturbed by messages purporting to be “scientific” when they are not.

You Don’t Love Science. You Don’t Even Know What It Means.

So let me explain what science actually is. Science is the process through which we derive reliable predictive rules through controlled experimentation. That’s the science that gives us airplanes and flu vaccines and the Internet. But what almost everyone means when he or she says "science" is something different.

To most people, capital-S Science is the pursuit of capital-T Truth. It is a thing engaged in by people wearing lab coats and/or doing fancy math that nobody else understands. The reason capital-S Science gives us airplanes and flu vaccines is not because it is an incremental engineering process but because scientists are really smart people.

In other words — and this is the key thing — when people say "science", what they really mean is magic or truth.

What we now know as the “scientific revolution” was a repudiation of Aristotle: science, not as knowledge of the ultimate causes of things but as the production of reliable predictive rules through controlled experimentation.

If you ask most people what science is, they will give you an answer that looks a lot like Aristotelian “science” — i.e., the exact opposite of what modern science actually is. Capital-S Science is the pursuit of capital-T Truth. And science is something that cannot possibly be understood by mere mortals. It delivers wonders. It has high priests. It has an ideology that must be obeyed.

This leads us astray.

This is how you get the phenomenon of philistines like Richard Dawkins and Jerry Coyne thinking science has made God irrelevant, even though, by definition, religion concerns the ultimate causes of things and, again, by definition, science cannot tell you about them.

You might think of science advocate, cultural illiterate, mendacious anti-Catholic propagandist, and possible serial fabulist Neil DeGrasse Tyson and anti-vaccine looney-toon Jenny McCarthy as polar opposites on a pro-science/anti-science spectrum, but in reality they are the two sides of the same coin. Both of them think science is like magic, except one of them is part of the religion and the other isn’t.

What you probably mean when you say “I love science” is “I love my tribe.” Via How our botched understanding of 'science' ruins everything – The Week.

Fluid Experiments Support Deterministic “Pilot-Wave” Quantum Theory

This idea that nature is inherently probabilistic — that particles have no hard properties, only likelihoods, until they are observed — is directly implied by the standard equations of quantum mechanics. But now a set of surprising experiments with fluids has revived old skepticism about that worldview. The bizarre results are fueling interest in an almost forgotten version of quantum mechanics, one that never gave up the idea of a single, concrete reality.

The experiments involve an oil droplet that bounces along the surface of a liquid. The droplet gently sloshes the liquid with every bounce. At the same time, ripples from past bounces affect its course. The droplet’s interaction with its own ripples, which form what’s known as a pilot wave, causes it to exhibit behaviors previously thought to be peculiar to elementary particles — including behaviors seen as evidence that these particles are spread through space like waves, without any specific location, until they are measured.

Particles at the quantum scale seem to do things that human-scale objects do not do. They can tunnel through barriers, spontaneously arise or annihilate, and occupy discrete energy levels. This new body of research reveals that oil droplets, when guided by pilot waves, also exhibit these quantum-like features.

To some researchers, the experiments suggest that quantum objects are as definite as droplets, and that they too are guided by pilot waves — in this case, fluid-like undulations in space and time. These arguments have injected new life into a deterministic (as opposed to probabilistic) theory of the microscopic world first proposed, and rejected, at the birth of quantum mechanics.

via Fluid Experiments Support Deterministic “Pilot-Wave” Quantum Theory | Simons Foundation.

No Observable Global Warming For 17 Years 9 Months

According to the RSS satellite data, whose value for May 2014 has just been published, the global warming trend in the 17 years 9 [months] since September 1996 is zero (Fig. 1). The 213 months without global warming represent more than half the 425-month satellite data record since January 1979. No one now in high school has lived through global warming.

The hiatus period of 17 years 9 months is the farthest back one can go in the RSS satellite temperature record and still show a zero trend. But the length of the pause in global warming, significant though it now is, is of less importance than the ever-growing discrepancy between the temperature trends predicted by models and the less exciting real-world temperature change that has been observed.

Meanwhile, my understanding is that atmospheric carbon has continued to increase. The models based on carbon don’t look very predictive at this point. Via The pause continues – Still no global warming for 17 years 9 months | Watts Up With That?.

We Are All Scientists

Science is not a degree, or a paying job, or even (as many mistakenly believe, and sadly how it’s too often taught in school) a compendium of accumulated knowledge, but a way of thinking and learning about how the physical world works.

Science is a process: observe a phenomenon, form a theory about why it occurred, test the theory with an experiment or other observation, see it fail (in which case a new theory is required) or continue to believe it until a test of it fails. Anyone who survives in life does it every day.

via PJ Media » We Are All Scientists.