Yet another attempt to create a social network.  This one’s called Mastodon.  It is analogous to Twitter, i.e. short status updates with following, liking, comments.    Web UI, and apps for assorted devices.   It’s usenet like in with a user accounts residing on nodes and then the nodes stitched together into an exchange network.  Open source with ties to the FSF/Gnu community.

We wish them the best of luck, this is hard rabbit to pull out the damn hat.

Here are some charts based on data taken from this page enumerating some of the nodes in the network.  These are log log charts, and each point is for a single node.  Their equivalent of Twiter’s tweet is being called a toot.  Though in these charts it’s called a status.

A not unusual distribution for an unregulated social networks.  It’s always delightful make up little stories about why there is a node who’s users have made an huge number of toots per user.

The Backfire Effect

You may have noticed that sometimes: you argue with somebody and you come away thinking: “My that backfired!”   Rather than loosening their attachment to their foolish belief they have become more committed.

In years since the effect was named studies have revealed that the effect is common and potent.   They have discovered that some public health advertising campaigns backfire. The target audiences become much less likely to change behavior.  Even bizarrely after the audience admitted that they accepted the facts.

With a public health mindset you can then start to wonder what dosage of facts and information is optimal to change a person’s mind.  Studies that attempted to start to get a handle on that (see links below).  But slight spoiler – it’s really hard! – but not too hot, not too cold.

So what’s going here?  Naturally we all labor to keep a consistent world view.  Whenever new information comes over the transom our minds devote some calories to folding it into that world view.   Let’s call that work skepticism.  It can be defensive, curious, even light hearted  skepticism – smart people take pride in this work.    If the information is at odds with our current world view we are motivated to take the exercise more seriously.  The name for that syndrome is “motivated skepticism.”

It’s not actually that surprising that engaging in the exercise would often strength the existing world view.

That all reminded me of what in back in the 70s the AI community used to call truth maintenance.   Failure to keep the software’s model of truth well maintained was treated as an existential threat to the system.  Because, it’s well known that in simple sets of equations a single mistake doesn’t just lead to bad results; it lets you prove that anything is true.

Here are three podcasts (123) about this.   Part of David McRaney’s the “Your not so smart” series.   David’s turf is around questions of what social science can tell us about discourse, debate, and changing people’s minds.  If you are not into podcasts you can skim the posts enumerated above for an overview and links to other materials.

Sleeper cells

I’ve recently been enjoying a podcast on microbiology.

They recently mentioned that some bacterial infections include a tiny fraction of hibernating cells.   The sleepers are unaffected if somebody tries to murder with an antibiotic.  Later when they awaken the antibiotic is gone and the infection returns.

Bad faddish ideas are like this too.


Amazon’s AWS has a message queue system, aka SQS, to which they have recently started adding a variant which assures that your messages are delivered in the same order that they got sent.  I.e. first in first out.

If you are surprised that they don’t do that by default you may enjoy thinking about what would be involved if the Post Office was to decide to offer this feature.

That said, I’ve been surprised that it took so long for this to show up and I remain surprised how slowly they are rolling it out.

So it is with some amusement I read in their doc an example of why you might want this feature.

“Display the correct product price by sending price modifications in the right order.”

Which I think helps explain why Seattle is one of the few AWS sites that supports it so far.

Democracy for Realists – space and time

Some more about this book, Democracy for Realists: …

If we accept that voters do not vote for their policy preferences (and you can read the book if you want to see the evidence) then what is driving their voting behavior.

Here are two models that Political Scientists have put forward – space and time.  Both model presume that voters, being humans, lack the time or talent to engage in a very subtle or complex analysis of what to do with their vote; so they simplify things.  They approximate.

The spacial model: all of politics is boiled down to some simple metric: left-wing v.s. right-wing say.  Or maybe a few two,  like both an economic and social variant of left/right.  The voter then “merely” asks the question how close are these candidates’ metrics to my personal metrics. He then votes for the one closest to him.

In the time based model the voter need only look at his personal experience over time.  He then aligns that with who ever is change during various time frames and votes for the candidates that deliver better outcomes.  It’s feedback loop, and presumably the statistics of large numbers of voters might make this work out nicely.

Again this is Science.  A theory is only interesting if we can proceed to try and disprove it.

The spacial theory is easy to disprove.  You just ask.   Compare the voter and the candidate he selects on the metric.   Questionnaires can dependably tease out where they are on the scales.  For example: Support for lower taxes verse more government services? What the data shows is only the lightest correlation.  In fact in some cases voters do the opposite of what they prefer.  So this theory isn’t helping us.

The problem with the time based theory is two fold.

The first problem: The usual ones found in feedback based systems.  These systems only work if (a) the signal the feedback is based on is accurate and (b) the feedback’s timing is adjusted correctly.  In Engineering school I spent a few years learning how to get that right for simple electronic systems like amplifiers.  In that context if you get it wrong you get nothing or horrific feedback noise.  Big social systems are even harder.  So first off voters get a signal (they lose their job, the weather is lousy, the crop fails, the town has an awesome fair,  the kid gets a lovely teacher) and they sum that up and vote for against the current candidate.   Then we have timing.  This model rewards the politicians for taking actions that have short term benefits; i.e. they show up in the voter’s impression before the next election.   Worse, long term benefits will accrue to the account of some other guy.

Like the spacial model voters have a very noisy model of the candidates.  In this case the their model of credit/blame is very poor.

So what are two models worth anything?  Turns out yes.

The spacial model is the gold standard for understanding legislatures.  While it’s useless for discovering how a voter will pick his candidate, it useful for predicting how Bob, your legislator, will choose to vote on any given bill.   This is good news:  Bob is fairly well informed about the position taken by the bill.  On the other the voters who elected Bob do not have a good model of Bob.

The time based model is actually quite predictive of how voters will behave.   But, oh my, they are largely miss informed about blame/credit and their sample is narrow minded.  They only look back a few months.  This is not good if you want responsive government.   It is useful if your placing bets on an election.  You can do a damn good job of predicting the outcome of elections by measuring just GDP growth over the last few months.

While these models are not as useless as the folklore model ( i.e. that voters give their votes to candidates who reflect their personal policy preferences).   But if your goal is to explain how Democratic governance is responsive to the voters preferences; they they aren’t going to help you.

More to follow…

Democracy for Realists – acting on falacies

Part 2 – So let’s step into this book a bit.

The reason to prefer a realistic view of politics is fear.  Fear that your unrealistic premises will lead to unfortunate outcomes.  So political scientists have spun up models for voter behavior. And then, tested them!  if you want to win elections it’s probably best to pay attention.

Personally my thinking about politics was entirely up-ended by the work on the voting patterns in Congress.   This book may be forcing a major resorting in my head.  I’m not sure how that will settle out.   It’s very discomforting to think that the model I took on board from that book might be wrong, that I’ve been extremely deluded.

Books that are attempting to force a painful dose of realism into their audience probably need to spend a lot of time addressing their audience’s bogus beliefs.  Scientists to this with studies, data, statistics.  It takes years to convince people that the world is not flat, the sun doesn’t spin around us, that punishment is effective, that bleeding out the bad blood doesn’t help.

So let’s start with the most most popular model of how democracy works.  It’s widely presumed that voters vote their preferences.  Say Sam is extremely concerned about Global Warming.  We’d assume he’d seek out the candidate who is most aligned with his concerns and then vote for him.   What the data say?  The data says:  NO!

If you take that to heart you really need to stop taking seriously sentence like:  “The voters, outraged about X, voted for Mr. P.”  Because it’s not true!  Talk of the “will of the people” is aspirational, but it too is not true.  The whole idea of a mandate splits thru your fingers like sand.

Good science is all about disconfirming models   Postulate a theory/model and then see if you can prove it’s wrong.   The audience may hate that, they may love the model, but science doesn’t care.

So this first model of politics in the democratic states is wrong.  The authors call this the folklore theory.

Once it became clear that the folklore theory doesn’t fit the data the political scientists went looking for other theories.  But that’s a story for another day.

<X> for Realists

I’m currently reading a book titled “Democracy for Realists: …”   It’s triggered a bemused fantasy about a series of “… for Realists: …” books.  In the tradition of those “… for Idiots: …”

I remember books stores.  They had lots of shelf space for self help books.  A popular genre. Let’s imagine some titles:   Schooling for Realists, Vacations for Realists, Project management for Realists, Home brewing for Realists, Gardening for Realists.

So’s why not?  I have my theories.  For example picking up a book of this title would seem to signal one’s appetite for disconfirmation.  Where’s the fun in that?  Or possible like the Monty Python argument skit it implies your shopping for a scolding or abuse.  At minimum it would seem to signal that the author is war weary, scarred, old, cranky?

One take on self help books is that they are selling a treatment for stress.   Realism doesn’t sound like a miracle cure, more like chemo.



I think the #1 thing i’m embarrassed about is that I didn’t take seriously the one in three chance that the best pollsters gave Trump of winning.   As John Hobo wrote: “I’ve never played Russian roulette – don’t intend to – but I think I know enough of tabletop games to know that sometimes a six-sided die comes up 6.”

So I really didn’t have a contingency plan; still don’t.  I’d chatted about hedging.  I.e. placing a largish bet that Trump would win, so then at least I’d have some winnings – either way.  But the consensus was that it’s difficult to hedge against an existential threat.

Back around the turn of the century I read “Congress: A Political-Economic History of Roll Call Voting.”   Which revealed the shocking trend in polarization.  Back then it was all on the Right.  Still is, to first order.

So, I came to form opinions about how that was likely to unfold over time.  Models of possible destinations.  For example the last time this happened we got the Civil War.

My best case scenario was (maybe still is) that the party of the right would implode; go insane.  That the voters would look at that and run away.  The George W. Bush administration gave some confirmation to that hope.   But, also a taste of what a terrifying journey that would be.

What I didn’t know until recently is that that political scientists tend to think about voter behavior and preferences.   For example, voter preferences flow from the party to the voters, mostly.  Not the other way around.  It’s unsurprising when you think about it.  How is the typical person to form an opinion about complex issues of governance except to turn to those around them.

It’s not as simple as to say the consensus of the party members flows top down.  It’s a social network thing.  But for a party  member to step away from the consensus accepting a huge about of collateral damage.  He has shred his entire social network.