jeugdjournaal - Dutch tolerance and contrasts

Yesterday I saw a bit of the jeugdjournaal, a sort of "news for kids".

One section showed a very boyish ~11yo girl, who does her hair and dress like a boy, and is very convincing as one. People always tell her to go to the boys' bathroom. Remarkably, her classmates think that she's ok. She doesn't get bullied at all, and has a "normal" social life.

I thought to myself "Oh, Holland, what a civilized place..."

-

Next scene: you see a ~13 year old schoolgirl, Aliya from Azerbaijan, from a family of refugees, and who speaks perfect Dutch. Unfortunately, her whole family is scheduled to be deported from the Netherlands in the middle of the schoolyear. Her friends were upset at the news, so they started collecting signatures to beg for the right to *at least* let her finish the schoolyear.

The show crew interviews minister Rita Verdonk, asking if she would accept the plea: "Aliya's classmates are very upset. Shouldn't she be allowed to at least finish the school-year? What would you tell her classmates?"
Verdonk - "I would explain to her classmates that this country has laws, and that unfortunately Aliya has to leave."

I thought to myself "fucked up!"
How can the same country be so inhumane when it comes to immigrants and refugees?

health update

Exercise: I went running today and yesterday morning. I really feel great afterwards... yesterday I was tired enough to go to bed at 10pm. My right ankle complains a bit, but I haven't heard from my left knee at all (where I had a Baker's cyst), and no news is good news. I was bothered a bit by air pollution on the roads.

Nose: the tissue inside my nose is, as always, swollen. This is worse in the mornings. It really sucks, but I live with it. I'll eventually investigate this problem in detail.

Eating: I hadn't had milk (of any kind) in a month. Yesterday and the day before I had a glass. I'm not responding well, so maybe I've become lactose intolerant... I still eat plenty of cheese though. Is it possible to buy delactosated milk?
I'd also not had chocolate in a month... then I tried a brownie or two, and I didn't like it very much anymore. Am I still a chocoholic?
I've also tried sprouts, namely "bieslook" and a sort of onion-flavoured grass (thanks darkjewelz) which were ok. I also started mushrooms (thanks to jmmorton), which I sort of like and I'm sticking with it. Yay, grass & mushrooms in Amsterdam.
I'm still buying just brown bread, with the occasional white tortilla.

primacy effects / pigeonholing

One thing that's weird in this country is how long it takes some people to update their beliefs.

For example, many people will pigeonhole me as a foreigner (whether by my appearance or by seeing me speaking English), and insist on speaking English to me, and will not believe that I speak Dutch *even*after* I speak several sentences of good Dutch. Maybe this is due to confirmation bias: people only hear what they want to hear.

On the other hand, if people pigeonhole me as a Dutch person (by hearing my accentless speech), they won't believe me when I say that I don't understand something... and will have no pity on my poor understanding, and speak too fast.

Why don't people have an in-between category?

personality questionnaires & data mining

How meaningful are the MBTI dimensions?

Wouldn't we be better off doing data mining on personality questionnaires, in order to find an optimal set of personality dimensions?

If we have a questionnaire with k questions, the space of possible answers is A^k, where A is the set of admissible answers for an individual question. We could simplify this and say that A = {0,1} (yes-or-no questions). The consequence is that the possible answers form a (discrete) hypercube.

A personality dimension would be a linear combination of these answers.
A subspace of A^k is a collection of personality dimensions.

The interesting question is:

Given an integer n, and a sample of completed questionnaires, how do you find the optimal linear subspace in n dimensions? In general, you would define a set of variables that you want to predict. But let's say we want to predict all the variables equally, i.e. we want the subspace that provides the least-lossy compression of the data (measured by say, least-squares). Since we're maximizing meaningful information over all possible n-dimensional subspaces, I wonder if this corresponds to minimizing entropy. But it seems that maximizing entropy would just maximize noise.

Of course, the approach of linear combinations ignores complex interactions between the variables (e.g. given Q1, Q2 is positively correlated with Q3; but given ~Q1, Q2 are Q3 are negatively correlated). But we can always solve this problem by adding extra variables (e.g. a variable that equals "NOT (Q2 XOR Q3)", which measures their correlation): I wonder if all the logical relationships remain preserved when you do the linear regression (under the Boolean extension from {0,1} to [0,1] where "AND" becomes multiplication). Another interesting question is "which logical dependencies are expressible with a set of conjunctions?".

I'm now imagining that a good algorithm would be to create a graph with questions as nodes, and edges as strongly positive pairwise correlations. Good dimensions will show up as clusters (dense subgraphs), i.e. just let the dimension be the sum of all questions in the cluster. Good subspaces can be found by finding partitions that cut through the fewest edges (sort of similar to min-cut) while still being more or less balanced in the size of the clusters.

-

Conclusion: I need to take a machine learning class.

And by "class", I mean a good book.

And by "good", I mean "a book that answers my questions, without too much reading effort required".

early bedtime

10:30pm and my body is telling me it's bedtime. I don't know if this healthy lifestyle is for me!