Posts tagged with belief

This is a question about argument, counterargument, convincing people of something, and why people believe the things they do.

  • Let’s say you make a claim. For example the claim that rich people are rich because they do the most good in society.
  • I want to argue that you’re wrong. There are a couple ways I could proceed.
  • Now, to me, personally, the most logical tack to take should be to ask you for evidence.
    Wikipedian Protester

    You’ve made a sweeping claim about a large number of people, using ill-defined abstractions like "good", and so on.
  • In my mind, the way I personally think, I should ask you to back that up, you won’t be able to (or will make recourse to doctors, neglecting the real issues like LBO investors or the bottom billion) and then you end as wrong or neutral.
  • But. This is not what really works in a real debate or argument. It’s mysterious to me as to why, but I think a correct answer as to why would be pure gold.
  • What’s going to work better is if I argue a separate theory.  Like "No, the rich don’t benefit society the most, they just screw people over the most. They put the terms of trade in their favour, they set up deals that screw over powerless or uninformed parties, and the game is set up in a way that benefits them.” If I’m really impassioned and present some stories backing up my viewpoint this will work even better.
  • Now to me this seems illogical. You’re saying "X" and rather than responding "Not X" I’m supposed to respond "Y". Y relates somewhat to X and kind-of negates X, but mostly Y is just a different theory of the world.
  • Another example could be that you argue for supply-side economics. Instead of me arguing against supply-side economics, pointing out the flaws or weak points in it, it’s more convincing if I argue Keynesianism, or MMT, or some other full theory, instead.

My examples are economics debates because I’m stupid. But this principle of arguing in a different direction than directly contrary to what you say works elsewhere too.

  • Look up "Gish Gallop" for example. The phrase relates to evolutionists complaining about the way a creationist, Duane Gish, argues. Gish allegedly adds more and more propositions to his argument, forcing his opponent to look up and refute stuff much slower than Gish can add new propositions.
  • Gish is not arguing this way, and his evolutionist opponents are not frustrated by the rhetorical style, because it doesn’t work. Irrespective of how much he does it, the fact that evolutionists were bothered enough to name a “fallacy" after Duane Gish indicates that audiences were swayed by the technique of adding more and more propositions.
  • Logically—to me at least—it’s harder to prove a claim made up of many propositions than to prove just one of the propositions making up the claim. So “Not only does G-d exist, but the Christian G-d exists, and was made manifest as Jesus Christ, and died on the cross to atone for the sins of mankind, and ten other points of doctrine" —- should be harder to prove than just "Any G-d exists”. But yet I’ve seen more than one “Atheism debate” where the anti-atheist person debates this very long proposition.
  • Or let’s say you’re arguing that a thesis you read in the Times is “probably right" because it’s vetted by experts. I should argue back that vetting doesn’t imply it’s right. But to be more convincing, I probably should counter the Times writer’s theory with one of my own. If I don’t have one, but just like to carry around a bucket of scepticism to pour on fires of passion? I’m SOL rhetorically.
  • Why wouldn’t you just defend the easiest argument—the one that Pareto-dominates the long argument?
  • The fact that people don’t agree with what I’m calling simple logic means I’m missing something. In fact I don’t think anyone has a theory of why people are convinced by things, which captures the appeal of these run-on arguments. Of course I would be happy to be told I’m wrong about that; please tell me if I am.
  • Do people prefer more information-dense statements? Does making a more specific claim imply, in some wider "ecological" sense, that the speaker is “more likely to be” well-informed? Do people prefer whole frameworks to piecemeal facts? If so, why?
  • I could go on with more questions and half-baked theories of what might be happening, but I’ll spare you.

So, why do people think this way? Is it a lack of sfumato? And what does the fact that people think this way tell us about other important stuff, like rationality, love relationships, parenting, reasoning, good decisionmaking, "facts", habits, authority, marketing, judgement, court convictions, investing/retirement planning, political voting, how people come to their beliefs, and what it takes to change someone’s beliefs?

Winthrop also subscribed to the belief that the native peoples who lived in the hinterlands around the colony had been struck down by G-d, who sent disease among them because of their non-Christian beliefs:

“But for the natives in these parts, God hath so pursued them, as for 300 miles space the greatest part of them are swept away by smallpox which still continues among them. So as G-d hath thereby cleared our title to this place…”

New World Encyclopedia, via MRU

(search pictures of smallpox only if you have a strong stomach)

Einstein opined that the great philosophical breakthrough leading to the mental possibility of science was the hypothetico-deductive method.

Which is a jargony way of saying: forget whether A is true or not (measurement of the world)—let’s talk about the separate, purely logical issue, of whetherif A were true, would B necessarily be true as well, as a result of A being true? ⧝

People aren’t great with hypotheticals, though—at least not everyone or not without education.

  • I can get people to agree with my reasoning  by first telling them that  leads to a conclusion they already agree with B.
  • (This is really dastardly because once I’ve judoed someone this far I can get them to agree to even more things, in order to maintain local consistency.)
  • We judge each other on credentials (A).
  • We judge arguments on what other experts think of them.
  • Mathematics is all about the  and most people are either scared to tears by mathematics, bored to tears by mathematics, or think mathematics irrelevant, or all three.
  • People think that if I argue that their reasoning  is wrong, I’m saying their conclusion B is wrong.
  • (Symbolically it’s obvious that A↛B = A⊬B = ¬(A→B) isn’t the same as ¬B. But people regularly interpret “That does not follow” as “That’s wrong”.)

File:Catechism-Madras Presidency Village.jpg

Whatever it is people do in arriving at their beliefs, it’s not propositional calculus; it’s not Bayesian probability; it’s not “believe whatever mama says”. But it is a little like all of those.


I was riding on a train in Italy. Watching lemon trees out the window. Fantasising of tasting a lemon-based liqueur.

Lemon trees. Amalfi Coast, Campania, Italy (color)



My travel partner and I shared a vestibule with an American monk-cum-priest who introduced himself as Father John. Father John was making a pilgrimage from the Carolinas to Vatican City. I don’t know if he always evangelised but, although my partner and I tried to steer the conversation away from religion, Father John wanted to talk about his Catholic faith—specifically in a way that might score some converts.


I don’t know whether the part of me that makes me debate with strangers online was acting out in its pre-internet form, or whether Fr J’s insistence on having a conversation we clearly did not want to have put me in a pugilistic mood.

File:Jules-Alexis Muenier - La Leçon de catéchisme.jpg

For whatever reason, I started querying him on some of the more outlandish assertions of Catholic doctrine. One thing I challenged him on in particular was transubstantiation.

File:Pietro Longhi 021.jpg

Try though the alchemists might they could never transmute lead to gold—but every Sunday around the world, holy men of Christianity transmute sacramental bread and wine into literally the body and blood of Christ.


The biochemistry involved in going from wheat flour to bone marrow or from pectin to haemoglobin is not discussed in catechism, but the transition is obviously impossible by natural processes. Nonetheless, “the real presence of Christ in the Eucharist is a mystery—something so packed with meaning that we can never fully understand it.”


I really don’t have a bone to pick with “transubstantiationalists”. I find the deeper reasons he and I think as we do more interesting than what we profess. I don’t go out of my way to attack people or hurt anyone’s feelings—but I do consider it rude to evangelise someone without consent.

So I needled the man. "Come on, you really believe that? Really? It’s not just a symbol? You can’t just have your religion without this physically impossible claim? Why would you insist on invoking the supernatural when that clearly undermines the credibility of everything else you say? Not only is it impossible according to science, even to your own sensory experience it just looks like a normal wafer—not like a hand or a butt or whatever. You literally, actually believe that this wafer literally, actually turns into actual human flesh of a dead man from two millennia ago—using up more body mass than he ever had all over the world every Sunday—really? Really?”

I still remember Father John’s response (which is how I’m able to tell you this story). He said: “OK, I understand your objections. But consider this. What if it were all true? What if the Resurrection, the Virgin Birth, G-d walking among men, the sacred mysteries, all of it were true? Wouldn’t that be wonderful? Wouldn’t that change everything about the way you see the world?”

What-if indeed, Father. What if.

Lucas’ “rational expectations” revolution in macroeconomics has been tied to the ending of stagflation in the world’s largest economy, and to the reintroduction of “psychology” into finance and economics. However, I never felt like the models of “expectation” I’ve seen in economic theories seem like my own personal experience of living in ignorance. I’d like to share the sketch of an idea that feels more lifelike to me.

First, let me disambiguate: the unfortunate term-overlap with “statistical expectation” (= mean = average = total over count = ∑ᵢᴺ•/N = a map from N dimensions to 1 dimension) indicates nothing psychological whatever. It doesn’t even correspond to “What you should expect”.

If I find out someone is a white non-Hispanic Estadounidense (somehow not getting any hints of which state, which race, which accent, which social class, which career track…so it’s an artificial scenario), I shouldn’t “expect” the family to be worth $630,000. I “expect” (if indeed my expectation is not a distribution but rather just one number) them to be worth $155,000. (scroll down to green)

Nor, if I go to a casino with 99% chance of losing €10,000 and 1% chance of winning €1,000,000 (remember the break-even point is €990,000). “On average” this is a great bet. But that ignores convergence to the average, which would be slow. I’d need to play this game a lot to get the statistics working in my favour, and I mightn’t stay solvent (I’d need to get tens of millions of AUM—with lockdown conditions—to even consider this game). No, the “statistical expectation” refers to a long-run or wide-space convergence number. Not “what’s typical”.

Not only is the statistical expectation quite reductive, it doesn’t resemble what I’ve introspected about uncertainty, information, disinformation, beliefs, and expectations in my life.

File:Coloured Voronoi 3D slice.svg

A better idea, I think, comes from the definition of Riemann integration over 2+ dimensions. Imagine covering a surface with a coarse mesh. The mesh partitions the surface. A scalar is assigned to each of the interior regions inscribed by the mesh. The mesh is then refined (no lines taken away, only some more added—so some regions get smaller/more precise and no regions get larger/less precise), new scalars are computed with more precise information about the scalar field on the surface.
a scalar field

NB: The usual Expectation operator 𝔼 is little more than an integral over “possibilities” (whatever that means!).

(In the definitions of Riemann integral I’ve seen the mesh is square, but Voronoi pictures look awesomer & more suggestive of topological generality. Plus I’m not going to be talking about infinitary convergence—no one ever becomes fully knowledgeable of everything—so why do I need the convenience of squares?)

I want to make two changes to the Riemannian-integral mesh.



First I’d like to replace the scalars with some more general kind of fibre. Let’s say a bundle of words and associations.

(You can tell a lot about someone’s perspective fro the words they use. I’ll have to link up “Obverse Words”, which has been in my drafts folder for over a year, once I finish it—but you can imagine examples of people using words with opposite connotation to denote the same thing, indicating their attitude toward the thing.)

Second, I’d like to use the topology or covering maps to encode the ignorance somehow. In my example below: at a certain point I knew “Rails goes with Ruby” and “Django goes with Python” and “Git goes with Github” but didn’t really understand the lay of the land. I didn’t know about git’s competitors, that you can host your own github, that Github has competitors, the more complex relationship between ruby and python (it’s not just two disjoint sets), and so on.

When I didn’t know about Economics or Business or Accounting or Finance, I classed them all together. But now they’re so clearly very very different. I don’t even see Historical Economists or Bayesian Econometricians or Instrumental Econometricians or Dynamical Macroeconomists or Monetary Economists or Development Economists as being very alike. (Which must imply that my perspective has narrowed relative to everyone else! Like tattoo artists and yogi masters and poppy farmers must all be quite different to the entire class of Economists—and look even from my words how much coarse generalisation I use to describe the non-econ’s versus refinement among the econ’s.
These meshes can have a negative curvature (with, perhaps a memory) if you like. You know when you think that property actuaries are nothing at all like health actuaries that your frame-of-reference has become very refined among actuary-distinguishment. Which might mean a coarse partitioning of all the other people! Like Bobby Fischer’s use of the term “weakies” for any non-chess player—they must all be the same! Or at least they’re the same to me.)


Besides the natural embedding of negatively-curved judgment grids, here are some more pluses to the “refinement regions” view of ignorance:

  1. You could derive a natural “conservation law” using some combination of e.g. ability, difficulty, how good your teachers are, and time input to learning, how many “refinements” you get to make. No one can know everything.

    (Yet somehow we all are supposed to function in a global economy together—how do we figure out how to fit ourselves together efficiently?

    And what if people use your lack of perspective to suggest you should pay them to teach you something which “evaluates to valuable” from your coarse refinement, but upon closer inspection, doesn’t integrate to valuable?)
  2. Maybe this can relate to the story of Tony—how we’re always in a state of ignorance even as we choose what to become less ignorant about. It would be nice to be able to model the fact that one can’t escape one’s biases or context or history.
  3. And we could get a fairly nice representation of “incompatible perspectives”. If the topology of your covering maps is “very hard” to match up to mine because you speak dialectics and power structures but I speak equilibria and optima, that sounds like an accurate depiction. Or when you talk to someone who’s just so noobish in something you’re so expert in, it can feel like a very blanket statement over so many refinements that you don’t want to generalise over (and from “looking up to” an expert it can also feel like they “see” much more detail of the interesting landscape.)
  4. Ignorance of one’s own ignorance is already baked into the pie! As is the beginner’s luck. If I “integrate over the regions” to get my expected value of a certain coarse region, my uninformed answer may have a lot of correctness to it. At the same time, the topological restrictions mean that my information and my perspective on it aren’t “over there” in some L2-distance sense, rather they’re far away in a more appropriately incompatible-with-others sense.

In conclusion, I’m sure everyone on Earth can agree that this is a Really Nifty and Cool Idea.



I’ll try to give a colourful example using computers and internet stuff since that’s an area I’ve learned a lot more about over the past couple years.

A tiny portion of Doug Hofstadter’s “semantic network”.  via jewcrew728, structure of entropy

First, what does ignorance sound like?

  • (someone who has never seen or interacted with a computer—let’s say from a non-technological society or a non-computery elderly rich person. I’ve never personally seen this)
  • "Sure, programming, I know a little about that. A little HMTL, sure!”
  • "Well, of course any programming you’re going to be doing, whether it’s for mobile or desktop, is going to use HTML. The question is how.

OK, but I wasn’t that bad. In workplaces I’ve been the person to ask about computers. I even briefly worked in I.T. But the distance from “normal people” (no computer knowledge) to me seems very small now compared to the distance between me and people who really know what’s up.

A few years ago, when I started seriously thinking about trying to make some kind of internet company (sorry, I refuse to use the word “startup” because it’s perverted), I considered myself a “power user” of computers. I used keyboard shortcuts, I downloaded and played with lots of programs, I had taken a C++ course in the 90’s, I knew about C:\progra~1 and how to get to the hidden files in the App packages on a Mac.

My knowledge of internet business was a scatty array of:

  • Mark Zuckerberg
  • "venture capital"
  • programer kid internet millionaires
  • — very nice interface!
  • perl.
    Regular Expressions
    11th Grade
  • mIRC
  • TechCrunch
  • There seem to be way more programming going on to impress other programmers than to make the stuff I wanted!
  • I had used Windows, Mac, and Linux (!! Linux! Dang I must be good)
  • I knew that “Java and Javascript are alike the way car and carpet are alike”—but didn’t know a bit of either language.
  • I used Alpine to check my gmail. That’s a lot of confusing settings to configure! And plus I’m checking email in text mode, which is not only faster but also way more cooly nerdy sexy screeny.
  • Object-Oriented, that’s some kind of important thing. Some languages are Object-Oriented and some aren’t.
  • "Python is for science; Ruby is for web"
  • sudo apt-get install
  • I had run at least a few programs from the command line.
  • I had done a PHP tutorial at W3CSchools … that counts as “knowing a little PHP”, right?

So I knew I didn’t know everything, but it was very hard to quantify how much I did know, how far I had to go.


A mediocre picture of some things I knew about at various levels. It’s supposed to get across a more refined knowledge of, for example, econometrics, than of programming. Programming is lumped in with Linux and rich programmer kids and “that kind of stuff” (a coarse mesh). But statistical things have a much richer set of vocabulary and, if I could draw the topology better, refined “personal categories” those words belong to.

Which is why it’s easier to “quantify” my lack of knowledge by simply listing words from the neighbourhood of my state of knowledge.

Unfortunately, knowing how long a project should take and its chances of success or potential pitfalls, is crucial to making an organised plan to complete it. “If you have no port of destination, there is no favourable wind”. (Then again, no adverse wind either. But in an entropic environment—with more ways to screw up than to succeed—turning the Rubik’s cube randomly won’t help you at all. Your “ship” might run out of supplies, or the backers murder you, etc.)


Here are some of the words I learned early on (and many more refinements since then):

  • Rails
  • Django
  • IronPython
  • Jython
  • JSLint
  • MVC
  • Agile
  • STL
  • pointers
  • data structures
  • frameworks
  • SDK’s
  • Apache
  • /etc/.httpd
  • Hadoop
  • regex
  • nginx
  • memcached
  • JVM
  • RVM
  • vi, emacs
  • sed, awk
  • gdb
  • screen
  • tcl/tk, cocoa, gtk, ncurses
  • GPG keys
  • ppa’s
  • lspci
  • decorators
  • virtual functions
  • ~/.bashrc, ~/.bash_profile, ~/.profile
  • echo $SHELL, echo $PATH
  • "scripting languages"
  • "automagically"
  • sprintf
  • xargs
  • strptime, strftime
  • dynamic allocation
  • parser, linker, lexer
  • /env, /usr, /dev,/sbin
  • virtual consoles
  • Xorg
  • cron
  • ssh, X forwarding
  • UDP
  • CNAME, A record
  • LLVM
  • the difference between jQuery and JSON (they’re not even the same kind of thing, despite the “J” actually referring to Javascript in both cases)
  • OAuth2
  • XSALT, XPath, XML

This is only—as they say—“the tip of the iceberg”. I didn’t know a ton of server admin stuff. I didn’t understand that libraries and frameworks are super crucial to real-world programming. (Imagine if you “knew English” but had a vocabulary of 1,000 words. Except libraries and frameworks are even better than a large vocabulary because they actually do work for you. You don’t need to “learn all the vocabulary” to use it—just enough words to call the library’s much larger program that, say, writes to the screen, or scrapes from the web, or does machine learning, for you.)

The path should go something like: at first knowing programming languages ⊃ ruby. Then knowing programming languages ⊃ ruby ⊃ rubinius, groovy, JRuby. At some point uncovering topological connections (neighbourhood relationships) to other things (a comparison to node.js; a comparison to perl; a lack of comparability to machine learning; etc.)

I could make some analogies to maths as well. I think there are some identifiable points across some broad range of individuals’ progress in mathematics, such as:

  • when you learn about distributions and realise this is so much better than single numbers!

    a rug plot or carpet plot is like a barcode on the bottom of your plot to show the marginal (one-dimension only) distribution of data

    who is faster, men or women?
  • when you learn about Gaussians and see them everywhere
    Central Limit Theorem  A nice illustration of the Central Limit Theorem by R:  Heaviside <- function(x) {      ifelse(x>0,1,0) }HH <- convolve( Heaviside(x), rev(Heaviside(x)),        type = "open"   )HHHH <- convolve(HH, rev(HH),   type = "open"   )HHHHHHHH <- convolve(HHHH, rev(HHHH),   type = "open"   )etc.  What I really like about this dimostrazione is that it’s not a proof, rather an experiment carried out on a computer.  This empiricism is especially cool since the Bell Curve, 80/20 Rule, etc, have become such a religion.NERD NOTE:  Which weapon is better, a 1d10 longsword, or a 2d4 oaken staff? Sometimes the damage is written as 1-10 longsword and 2-8 quarterstaff. However, these ranges disregard the greater likelihood of the quarterstaff scoring 4,5,6 damage than 1,2,7,8. The longsword’s distribution 1d10 ~Uniform[1,10], while 2d4 looks like a Λ.  (To see this another way, think of the combinatorics.)
  • when you learn that Gaussians are not actually everywhere
    kernel density plot of Oxford boys' heights.

    histogram of Oxford boys' heights, drawn with ggplot.A (bimodal) probability distribution with distinct mean, median, and mode.
  • in talking about probability and randomness, you get stuck on discussions of “what is true randomness?” “Does randomness come from quantum mechanics?” and such whilst ignorant of stochastic processes and probability distributions in general.
  • (not saying the more refined understanding is the better place to be!)
  • A brilliant fellow (who now works for Google) was describing his past ignorance to us one time. He remembered the moment he realised “Space could be discrete! Wait, what if spacetime is discrete?!?!?! I am a genius and the first person who has ever thought of this!!!!” Humility often comes with the refinement.
  • when you start understanding symbols like ∫ , ‖•‖, {x | p} — there might be a point at which chalkboards full of multiple integrals look like the pinnacle of mathematical smartness—
  • but then, notice how real mathematicians’ chalkboards in their offices never contain a restatement of Physics 103!
    Kirby topology 2012
    A parsimonious statement like “a local ring is regular iff its  global dimension is finite” is so, so much higher on the maths ladder than a tortuous sequence of u-substitutions.
  • and so on … I’m sure I’ve tipped my hand well enough all over that those who have a more refined knowledge can place me on the path. (eg it’s clear that I don’t understand sheaves or topoi but I expect they hold some awesome perspectives.) And it’s no judgment because everyone has to go through some “lower” levels to get to “higher” levels. It’s not a race and no one’s born with the infinite knowledge.

I think you’ll agree with me here: the more one learns, the more one finds out how little one knows. One can’t leave one’s context or have knowledge one doesn’t have. And all choices are embedded in this framework.

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  • wú wéi 無爲 — doing by not doing
  • the water is more powerful than the rock
  • "One of Daoism’s core ideas is that we can prolong life by following The Way" (contrast to Xtianity, Buddhism)
  • In the second century AD, Laodze was seen as “the alternative philosopher” to Confucius. Confucius represented the order of the State.
  • Buddhism may be an Indian form of Daoism come back to China
  • Later in the programme this appears to be a theme: Daoists as the under-religion, the shamanic folk religion. Well that almost fits the philosophy of “a ruler who doesn’t appear to be ruling” too nicely.
  • (Exceptions at times: the Yellow Turban revolt, 30 years of Daoist-led kingdom (which they peaceably annexed to a neighbouring ruler), widespread Daoist temples and 5 Bushels of Rice/year to pay for your Daoist shamanic exorcist/priestly councillor.)
  • "Shamanism preceded Confucianism" — "We are controlled by the unseen world"
  • In Chapter 42 [of the Dao De Jing 道德經] … the Dao gives birth to the Origin: the beginning of everything, the One. The One then gives birth to the Two, which is the Yin and the Yang. (These are cosmic forces. They’re not moral forces; they’re not divine forces. They’re just forces of the Universe.) And the Two give birth to the Three, which in traditional Daoist thought, is: Heaven, Earth, and Humanity. … And all this gives birth to the myriad things.
  • Cheng Dao Ling (2nd century) teaches he has the power to forgive sins.
  • Oh, so they have sins then? “But it’s harder to sin by inaction than by action.”← Lecturer’s supposition, I found the opposite to be one of the most interesting takeaways from the economic theory of opportunity cost. Why do we privilege the refrainment of wrongdoing over the failure to rightdoing?
  • Dao 道 = power (although our word for it has political connotations that 道 does not. I also notice our words for “logic" and "bureaucracy" don’t seem to fit in this discussion, denotatively or connotatively. Our language and theirs embed assumptions; ∄ neutral.) A universal process of change that applies to almost everything. (So, the Lagrangian-mechanics and post-Lagrangian-mechanics pursuit of minimisation of difference between potential and actual energy?)
  • De 德 = our individual instantiation with the Dao . Cycles of life. Which not everyone goes through with the same vigour.
  • Rulers needed to show that the celestial bureaucracy fitted harmoniously with their own worldly order. Li family 7th cent AD claims descent from (by then) Demigod Laodze.
  • "There’s no consistency to the Dao De Jing 道德經. It’s as if someone had chalked up parts of the Bible and mixed the pieces around and we had to derive a coherent philosophy from it." Actually this sounds exactly like the Bible. 73 books all by different authors and redacted by a series of future editors…yeah, not exactly one unified message.
  • "Gunpowder was developed by Daoists searching for the elixir of life…subdue KNO₃"
  • "Communists saw Daoism as mere superstition" — "By the Cultural Revolution ∃ ≤ 500 Daoist priests"
  • Joangdze: “Logic, rhetoric, argumentation don’t help us so much to understand The Universe” #logocentrism — Performance, experience, feelings are preferable to the (inserting my own pet peeves on economic theorists here) elaborate structures built upon fragile axioms [which then the fragile axioms defended at knifepoint since their collapse would bring down a roccocco golden palace on the theorist’s head].

(Source: BBC)

One of the important discoveries of the late 1700s and 1800s was that family life in Northwest Europe during this period varied substantially from family life in other parts of the world, such as Russia, The Middle East, China and India.

Compared to family life in many other parts of the world—with extensive family solidarity, little individualism, overwhelming control of parents over adolescent children, a young age at marriage, universal marriage, marriages arranged by parents, and large and extended households—family life in Northwest Europe could be characterized as having relatively little family solidarity, great individualism, little control of parents over adolescent children, an older age at marriage, many people never marrying, marriages arranged by the couple through courtship, and small and nuclear (or stem) households.

—arvind thornton

Hat tip to @mileskimball.


the Good People and the misguided

HT @jaredwoodard (supervenes)

the Good People and the misguided


HT @jaredwoodard (supervenes)


My friend and I were talking about hard bodies, which are normative in US culture.

Hardbodies Poster
Do you think it's feminine when a guy works out a lot to get a hot body?

She told me her theory that they are normative because US culture is pro-masculine in such a way that everyone has to perform masculinity in some way.

A feminine man, I was looking for a photo of a wimpy vegetarian in Birkenstocks shopping at an organic grocery store and being otherwise overly sensitive. But I was basically picturing Todd Louiso's character from High Fidelity. In this shot it looks like he's trying to appear more maculine. // The original conversation that led to this train-of-thought was about the Whitney Houston movie The Bodyguard, which I haven't seen but it came to mind as an example of perhaps a beautiful man being chased by a successful woman. But, still not having seen it, I speculate that there will be some point in the story where the man takes charge of the romantic pursuit, in order to maintain his attractiveness by recovering his masculinity.

I don’t know if I agree with that thesis or not, but it got me thinking about how a pro-masculine culture might be reflected in the economy, in the utility functions, and what an alternative on that dimension might look like.


So obviously, Estadounidenses work out; "Fitness is a $19 billion industry"; those who don’t are shamed.


But hard-ness might be reflected in utility functions in other ways as well.

  • preference of work (“I worked my #rse off to get where I am today”), busy-ness, regimens, organised workspaces, getting things done, goal-setting, achievement
    Larry Wall is disarrayed, chaotic, relaxed, embraces stillness, but I think he comes off as perhaps a bit of a feminine hippie.
  • a preference for doing over not-doing (or maybe doing over being-done-to)
  • a preference for hard-force over soft-relaxedness soft causing
  • shaming of laziness, softness, sloth, people who are too relaxed or don’t work enough, people who aren’t busy, have no career, have no ambition
  • a preference for my-own-space over shared-space
  • a preference for working hard, even if it’s to the point of overworking (overworking is actually kind of a compliment)
    "Work, work, and more work, and I expect it shall continue to be so." OK, obviously it's not _only_ US culture that preferes busy-ness to not-busy-ness.
  • a preference for individualism over communalism
  • a greater need for personal space (people stand relatively far apart from each other)
  • "I wish I could spend more time with my spouse and kids, but I’m too busy running this business empire!”
  • "I wish I could take a real vacation, or for longer”
  • Confidence, competence, winners, power over gentleness, flabbiness, passiveness, meekness, passivity, sensitivity.
  • creative destruction, building things, knocking them down, refurbishing, rebranding, striving for better, striving for more.

What about the alternative—what would a “soft” economy look like? Well, besides performing services and producing goods for each other, people can give utils to each other directly with

  • sex —the most obvious example of pure hedonic pleasure, uncounted in GDP, and “being good at it” (for men) may have less to do with a Big Man with a Big Dick, and more to do with openness, acceptance, creativity, curiosity, playfulness, sensitivity—characteristics which can be somewhat opposite to the Hard Body No Sleep Driven Successful macho man model
  • hugs
  • touching
  • softness toward each other
  • compliments
  • massages
  • Tumblr Likes
  • conversation
  • listening to each other
  • playing games together (think “childrens’ games” — why are they for children?)
  • sitting next to each other
  • holding hands
  • communicating that “I accept you as you are” or “I care what you think” or “I think you’re awesome”

(and equally they can harm each other with innuendo, bickering, hurrying or harrying each other, glares, invocation of rank/status, backhanded compliments, body language, and other perhaps “feminine” moves).

Somehow I got to think about Odo from Star Trek.
In at least one episode, the others of his shape-shifting race want him to return to live with them so they can all shape-shift into a goo and flow around in each other’s beings and experience each other. Which is one idea of Heaven. But Odo (a hero on a US TV show) wants to keep exploring, penetrating the cosmos to greater lengths. Maybe a “more feminine” economy, though, would look more like that. People touching each other, lazily hanging out,

I think there’s a reason that “California Buddhism”
looks like finding peace on a marathon instead of this:

Look at that fat guy! He’s just sitting there! So, but what do you do? I mean, what do you do, do?

If you’ve read Stats 101 at your local institution of schooling and refinement, you know the difference between false positives and false negatives.

  • False positive. Oncologist, to patient: Oh my God. This is terrible. Just terrible. Patient: What? Is it bad, Doc? Oncologist: Oh, not you. My son’s handwriting. It’s terrible! Practically illegible.”
  • False negative: Pregnancy test:  Eight months later: Waaaah!

False positive is when the canary has spent several years building up an immunity to iocaine mine gas; you stroll in and die. False negative is when the canary dies of canary-pneumonia in a gas-free mine; you scurry away and miss out on $500bn worth of shale coal.

twitter bird


For algorithmic traders, a “signal” is the switch that tells your software “Buy! Buy!” or “Sell! Sell!”

  • Computer: Just give me the signal, boss, and I’ll buy 10,000 shares of the company that makes IcyHot.
  • Trader: Let’s see … gold is up 50% on the year … the underlying is retracing between the third and fourth Fibonacci levels  … the volatility of the DOW is below 30 … it’s raining in Moscow … and my Alabama state government newsfeed just flashed the word “indubitably” … throw down the iron condor! Hard!!!

If I think about looking for a signal, I think about: when should I do this trade?


The idea behind this exercise is to have a computer search through data streams for you and tell you what’s a good time to trade.

If you take the perspective that the only thing you can control is your bet size (and not what the market will do), then it becomes clear that the choice is not only about {yes, no} but also about [£0, £100bn].

Accordingly, something that tells you when not to trade can be just as valuable as something that tells you when to trade.

The most obvious non-trading scenario is the Federal Open Market Committee. Say you normally trade forex intraday, close out all your positions when you leave the screen, and that’s your game. Right after the FOMC announcement, market movements may be drastic and will have little to do with what you normally bet on — unless you trade FOMC announcements specifically. But the point is it’s a separate modelling problem.

In theory at least, any strategy should be improvable if you can accurately identify conditions when the strategy fails. Removing losers will add to your PnL just as surely as adding winners.

I’ll make up a fake example with fake data (aka, lies). Say your strategy is to trade in the direction of momentum of S&P 500 E-mini’s iff the directionality has been sustained for at least 70% of the last five minutes, and to pull out the trade iff the fraction of price movements in your direction falls below 70%.

Looking at each hour of the past year, the least profitable hour for this trade, statistically, has been 12:00-1:00 New York time. So if you had followed the exact same instructions but closed out all positions and never traded during lunchtime, your PnL during 2011 would have been higher than the strategy as originally stated. (Of course, this example works only because one hour had to be the least profitable. But the same difficulty—distinguishing real patterns from numerical mirages—inheres in signal identification as well as anti-signal identification. If you identify a real cause & effect then the anti-signal should work.)

Any Statistical Model

Say you are trying to calculate when, where, and wieviel an advertiser should bid in a DMP for internet ad space. You take as inputs known or presumed data about site visitors, indexed by cookie, and produce as (eventual) output a list of which ads to buy, when, and how much to bid for them.

Here the same anti-signal concept could apply.

Instead of thinking, What are some damned good characteristics in this space? or Should I try another algorithm? This other paper says RandomForests aren’t as good as Breiman says. , think What data is the AI really failing on? You can remove those data from the training set and decline to make recommendations about cookies within that hull.

Say you are scanning a number of text resumes on a site like Indeed <aff link> and trying to figure out whose application you should invite for a geomodelling job. Just as much as searching for positive keywords like “Petrel”, you might want to filter out negative keywords like “definately”.

Say you are training your machine to learn when tweets will be effective and when not. Instead of shoving every tweet through the lingpipe, first filter out the non-English-language tweets.

OK, that last example is really obvious. I am not claiming that anti-signals are novel. It’s just a word I made up for something that’s common sense. But coining the word reminds me when I look at a modelling problem, to turn the problem upside-down and ask if there’s any low-hanging fruit on the other side.

One must be very naïve or dishonest to imagine that men choose their beliefs independently of their situation.

Claude Levi-Strauss, Tristes Tropiques

(via hollovv, matryoshhka)