philosopher bagpiper

true, woo and false

truth

silly happy pipes again, this time some bagrock

this is just a short post on the three levels of truth i use in this blog and introduce the concept of woo. every now and then, and more and more, people tend to focus on this whenever any rational subject is brought up. “yes, but how do you know true is true“. this is the usual comment after a rational claim is described: the usual counter-argument against the validity of rationality itself. maybe it’s just that i’ve been meeting more humanities majors lately, i don’t know.

so, summarizing the premises of my first more theoretical articles (i’m leaving development of minds and above part for later):

  • reality is accepted as fact, to avoid the flying spaghetti monster kind of stories
  • reality is composed of  N things with  X properties (sub-things) which are atomic (cannot be broken down into smaller things)
  • things are arranged according to a specific subset of macro-states versus all possible states (i.e., reality has low entropy or high information)
  • things act on other things (for example, forces of nature), which lead to local clumping of information (gravity for example)
  • this dynamic allows for a specific macro arrangement of things to be replicated (accurately or inaccurately). this process of information replication is seen in most forms of working agents thanks to evolution (molecules that don’t reproduce don’t survive for example), which leads to copies of the same arrangements of things over time
  • an arrangement of things has information about other things by the simple fact that it is affected by them (for example, if a charge creates an electrostatic force, its charge counterpart, by consequence of the effects of the force, has sufficient information to know the other charge by its very properties). the mere interaction creates exchange of information
  • the human brain, like many other structured things, has information in it encoded using the same principle: reality acts on this thing, and it creates a complementary, biased, factual or fictional representation (it is known that brains have input from the senses but also from random internal noise sources), meaning, brains are both emitters and receivers of information, as is reality
  • as a specific collection of information, a thing can only possess a representation of a subset of the possible symbols, i.e., if a thing is made of less things than reality, its total information (or arrangement) must be smaller than the arrangement of the whole reality (if a thing is made of n things and a thing exists inside a reality, then n << N), i.e., subjectivity is a consequence of limited representational power of things
  • the degree of truth is the difference between the representation(s) of reality and reality, since reality (to date) has only been approached by things inside it, its representations cannot fully represent the entire reality. in numbers, if the whole reality has information  I , then the sum (removing mutual information) of all representations is  i = \{ i_1 \cup i_2 - i_1 \cap i_2 \dots i_1 \cup i_x - i_1 \cap i_x \dots \} << I . i’m working on a better formulation of this
  • the higher the number of representations with low mutual information of the same reality, the better the total representation, or higher degree of truth. truth can therefore be defined as  T = \frac{i}{I} \in [0,1] . 1 is absolutely true (and impossible), 0 there is no information to assert it’s true (very possible and very frequent). so T is how how certain we can be of any truth.

so to observers, truth is subjective but the more observers we add, the bigger the local collective representation i of reality I. observers are defined as things capable of obtaining and representing information coming from reality, so it includes humans, but also information machines, sensors, animals, aliens and physical and chemical changes that reveal information. for example, if we find a hair in an archaeological site and find certain compounds that only appear during the fusion and work with copper, the hair has information about the activity that went on while it was on the corpse’s hair and counts as an observation of a certain event whose truth strength is being asserted.

so this settles truth. falsehood is just the logical negation of true, so it is also subject to T confidence, but instead of asserting a certain hypothesis is true we assert that it is false with T strength. they are similar and must respond to reality (as we defined above, the global source of information).

so basically i accept things as true and false with different degrees of confidence depending on how well they have been observed and tested. so asking if something is true or false must always be seen, in everything i write, as a transitory true/false state of a thing whose confidence by repeated scrutiny is maximum versus every other hypothesis for that same thing

so what about woo? what is this third value of truth? woo, piggybacking on what it means in english, is when something either has no sufficient confidence (very low T) or its negation has very high T, meaning, it is known to be false, but by perpetuating itself through multiple copies it then causes effects as if it was true with high T. this might seem confusing, but it is quite simple.

let’s say you believe in god. god is false with high T using these premises, meaning, it doesn’t exist in this sense. but since false representations (false observations) have been copied over and over in things (people’s minds), it then creates effects that make it seem it was true with high T. it creates a halo of true effects whose cause is false. a false observation builds up copies, enough to cause measurable effects.

this is the situation i described in my post about astrology, and recently on the one about economics. both of them rely on woo, but since their practitioners do not acknowledge it, then they cause real effects that might seem to prove woo is true. but if we apply the scrutiny we described above, it isn’t.

it is key to separate true from woo because one is what we call scientific facts, and the other are what we could call social facts. have no doubt woo is more powerful than truth, since most of the time, we are wooed into believing things that aren’t true using wonderful and often very rich and elaborate metaphors about reality.

using wooing concepts is exactly how marketing sells us false goods, politics sells us false laws, economy sells us false money and above all, how we lie to ourselves so naturally, driven by our desires. so whenever some new conversation about astrology springs up, i’ll just say it’s not true, it’s just woo.

membrane reed pipes, part two

diy

another diy segment. i went on, after the first reed construction, to tune a proper pipe. unfortunately, i relied on nothing more than instinct and made the holes randomly. i tuned the length so it would sound as the intended note (Bb in my case), and then made a hole in the middle to do the 5th. actually, it was wrong, but i got it working. check out the video to see it.

i designed it so there would be no holes open on the lowest note, which means you can stop all sound by touching your knee. this is like the uillean pipes, whose last hole is the actual tube opening. i’m planning on building a proper Bb minor like this, so i can play at home.

probably the most fun part is that this kind of pipe sounds like and 8bit sound card, so playing tetris tunes is much more fun. i’m working on the design, and soon i’ll post it with a working bag (something like a glovepipe).

losing wages for commutes and other monetary issues

economy emergence

today i will be writing about economics, kind of.

consider a regular company. worker  A is the employer.  A is accountable to stockholders, which pressure him to increase profits of the company. let’s say it is a very simple company, whose profits  P is just  P=I-E-R , where  I is income,  E is the expenses except  R , the office rent.

so  A proceeds to make an honest, informed decision based on this new fact: there is a new office whose  R_n < R , i.e., has a smaller rent. since there are no plans on changing expenses or profits, we can solve  d=P - P_n and if  d < 0 , we should choose  P_n . so  d = I - E - R - I + E + R_n \leadsto d=R_n - R \leadsto d<0 . this comes from  R_n < R . we should choose  P_n .

so the company sees an increase in profits of  P_r = P - P_n . good management and business as usual.

but in the math above there was no account for worker loss, i.e., how much of the workers’ wage is used to pay the commute. let’s now imagine the new location has longer commutes to get to work, making all workers spend more on the trip. if each employer spends  C_i extra on the new commute, to a total of  C , even though the company had positive  P_r , for the workers, they have just lost a part of their salary. in fact, considering wages remained constant, each worker just had a “demotion” of  \frac{C_i} {W_i} \% where  W_i is the worker’s wage.

here we see a perfectly lucid, valid management decision flawed in principle, by the very definition of company profits. this would fall in the emergent theory of how a company can be evil, without anyone in the network wanting it to be so. where is the flaw? let’s look at how we defined the company profit. we assumed  E , expenses, was constant, because they are the company expenses. but since a worker’s commute time is not considered a company expense (depends on the company, obviously), a more realistic expense definition would be  E_r = E + C . but if we do it this way, we now know that we will only have profits if  R_n - C_n > R - C , i.e., only if what the company saves in rent makes up for what the workers pay extra for the commute. this is similar to giving everyone a raise equal to the difference in commute cost. good for the workers, worse for profits of the company.

but it’s the very definition of profit that biases decisions towards less privileges for the workers that are highly affected by this. let’s see a concrete example.

  1. worker makes 500€, boss makes 5000€
  2. worker commute costs 50€, boss commute costs 50€
  3. company changes location, increases all commute costs by 100€
  4. worker now makes a net 500 – 50 – 100 = 350€, boss now makes 5000 – 50 – 100 = 4850€

this is equivalent to causing a “demotion” of 450€ to 350€ of the worker (-22%) and a “demotion” of 4950€ to 4850€ of the boss (2%). for the boss it might seem like “peanuts” and a “worthy sacrifice”. for the worker, it might be the difference between affording rent or not.

simultaneously, in this simple everyday example that i’ve lived through already, we can see two properties of a company-as-network that, for each individual, are not usually obvious.

on one hand, we see how management decisions can be done “correctly” and cause harm beyond the realm of decision, and provide whoever is deciding with a fake “solid” answer to a question (or a way in which economics successfully induces self delusion). since there were hidden variables in the calculation, it was flawed from the start. and the fact that “equations” are used to obtain answers (i put double quotes because they are completely arbitrary), just reinforces the fact that we’re dealing with a lot of nonsense (just like the math astrologers do, oblivious to the fact that astrology is bullshit). the best decision might be flawed by its own what is best definition. nothing that the humanities didn’t know, but something that economists avoid, when their field is, fundamentally, a field of humanities.

on another hand, how personal sensitivity to income is biased tremendously by one’s on income, and with it, empathy and understanding towards other, lower income, workers. 20% is a lot, and some workers might even consider changing jobs because of the commute. this might sound silly, but even if they accepted a job for 10% less, they would be making net 10% more than in their current situation. a boss might deem acceptable a change that might be tremendous for a worker, and nowhere in this network any one of the nodes needs to be aware of this. i.e., the apparent lack of empathy towards issues doesn’t need to be explained with greed. it can simply be explained by incompetence, just like the above example.

but if a network has too many incompetent nodes, it might obtain characteristics that its nodes wouldn’t anticipate (note that this is almost a tautology).

in my case, i sold my car and bike/public transit to work, which gave me an equivalent to a pay rise, since my employer would never do such a thing. i have no doubt my company is making more profit in this new location, but i know some workers now make less because of that. and i also bet nobody in the company consciously wanted this. it’s a conspiracy without any conspirators. also similar to one of my favorite quotes, Hanlon’s razor, never attribute to malice that which is adequately explained by stupidity.

false alarm

we sounded the alarm too soon. all the missing goods showed up, so i can maintain that in over 800 people nobody ever stole anything. though this is somewhat fishy (turning up in someone’s bag some days later), it maintains the tit for tat negotiation that i think is the core of security in these hospitality networks.

so, so far, no violence or theft in over 800 guests from all over the world. that’s definitely something.

guests, country and GDP

economy hospitality studies

i’m moving closer and closer to a normalized database, and with it, many new stats. one of the ones i wanted to see was the distribution of guests by country. i noticed early on that i seemed to get guests mostly from rich countries and no guests from africa for example. so i also cross referenced it with the GDP of each country. there is a relation, no doubt.

these are the results for the total amount of guests. i didn’t do stats on uncertain origins.

guests/country

zoomed in:

guests/country (detail 1) guests/country (detail 2) guests/country (detail 3)

these are a bit more interesting, how they relate to GDP (sorry, had to put the legend in the middle so it wouldn’t cover points, and it’s so big it didn’t fit).

GDP/guests

GDP per capita/guests

in both cases we can see that there is a great “divide” between the high GDP – high traveling countries and a lot of poor visitors on the bottom.

you can get the R source code and the source data and replicate my results. remember the data is licensed (see license on the bottom of the page). i will progressively provide more stats while i normalize the database.

what i see here is just another obvious fact. rich people travel more, poor people just can’t do it. couchsurfing might enable people to travel using less money, but it’s failing at getting poor people to join it. think about it, who has access to the internet and enough money to travel? i don’t want to be simplistic, but i do think this is food for thought. in a way, it is a hospitality network not for those that need it, but for those that don’t. just think about that taboo on couchsurfing: never say you’re short on cash! i guess you can’t be poor and acknowledge it.

this is apropos, we had our first money theft in a house (at _42). i guess it was only a matter of time until it would happen.

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