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From Tim Gowers' blog:

The following story arrived in my email inbox (and those of many others) this morning. Apparently a paper was submitted to the Taylor and Francis journal Dynamical Systems, and was accepted. The published version was prepared, and it had got to the stage where a DOI had been assigned. Then the author received a letter explaining that “following internal sanctions process checks” the article could not after all be published because one of the authors was based in Iran.

(Found in a private stream.)
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The joys of agent-based modeling: you get exactly the commonsensical conclusions that you have implicitly built into the model by chosing commonsensical parameters, and debugging your model against results that look nonsensical.
An Agent-Based Model of Wikipedia Edit Wars : How and When Consensus is Reached

A very strange but interesting paper which tries to model how quickly consensus is established by editors of controversial Wikipedia articles. I can't help feeling that there's an awful lot of complex modelling gone in to producing conclusions which for the most part are obvious and common-sense. At the same time, trying to model consensus-formation is very interesting, even if this particular case is oddly specific. It does have the option of calibrating against well-documented examples though.

The model includes a bunch of different parameters :
- The ability of agents to commit changes or reversions to articles, which can be both positive or negative in favour of a given viewpoint (hence four possible actions they can take)
- The credibility of different agents
- A probability that agents will actually take one of the possible actions
- A "payoff" given to agents for taking actions, which varies in a highly complex way based on the agent's stance and the other agent's actions and credibility
- A desired level of payoff for each agent
- The ability for agents to "learn", in the sense that the probability of the actions they take vary based on their results, though I can't make head nor tail as to how this is actually implemented

All of this results in the rather uninteresting conclusions :
- The more likely an agent is to make a revision, the longer it takes to establish consensus
- Consensus is established more rapidly when credibility of the agents involved is higher, up to a point
- Consensus is established most rapidly when everyone agrees and most slowly when opposing sides are about equal (well, blow me down with a feather (!))

It's still an interesting idea. I'd like to see it applied to more general situations.

Via +Event Horizon, naturally.
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The state of British academia in times of Brexit. Uncertainty in UK funding, uncertainty in EU funding, uncertain student fee income, rising competition from the continent with courses taught in English, prowling headhunters, and anti-intellectual Brexiters. Apart from all that, the picture looks rosy.
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Whether Noah Carl's research is valid is not the point. The point is that his "mobbing" is both immoral and scientifically repugnant. Let the evidence decide the value of Carl's work, not the wet dreams of a bunch of assholes.
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"Mathematics may be defined as the subject in which we never know what we are talking about, nor whether what we are saying is true."

Bertrand Russell
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Warren Ellis, on trying to ride the hype train.

You remember Shingy. David Shing. “Digital prophet” for Oath, bats around the world as a brand ambassador, talking, talking, talking, making little sense and making no cultural mark.

During a half-awake session of link-surfing while full of flu meds the other week, I happened across the blog of one of those guys who was always doing talks and camps and streams and conferences and all the fucking rest of it. He’s in his fifties now. On his blog, he notes that he has tiny savings and even after downsizing he and his wife both need full-time income streams to keep the lights on and the kids fed.

Put another way — even a year ago, before his business hit some self-inflicted disasters, he would have had jack shit to show for that Shingy life.

Reminds me of a couple of people in academia. Some make it, and they still live the Shingy life.

Now, said guy has always been a braying idiot who was wrong about everything. But I worry for the other people.

I worry for younger academics.

A thought for the new year: try to stay home for a bit and make some things that might last, please?
That Shingy Life
That Shingy Life
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This resonates with me. I never got this craze of teaching children how to code. Mostly because, apparently, nobody teaches children to code. Instead they teach children syntax, which is about as backwards as you get. Might as well teach Latin grammar to an eight year old.

Further observations, all of them trivial:

1) Most people won't code, and thats good, because most people shouldn't. Thats right, they really should not. Most people are absolutely terrible at coding, and that includes a good number of programmers.

2) Solutions to all easy problems have been implemented already. Whats left are the hard problems.

3) To help children cope with item 2, we better teach them problem-solving skills and the joy of discovery.

4) With regards to item 3, better teach children how to cook. As a side effect, the world would get more good cooks, and we are in dire need of them as well.

(Via +George Station.)
People go from one extreme to another. The coding frenzy is an example of that. Yes, you want your child to know what coding is and to understand computational thinking; no, you do not want him/her to focus on it after school, on the weekends and during the summer. Kids need to PLAY and have fun. That is more important than anything else.
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Vegemite is more useful than Marmite? Heresy, I say!

(Via +Rhys Taylor)
So it turns out that Vegemite is conductive, and also perfect for 3D printing food or edible circuits (it works better than Marmite).

Half my twitter list is currently verifying the first fact (yeah, it works); no one is willing to risk their printer for the second.
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Meanwhile, the Chinese aim at the Moon.
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