Scientific Revolutions in Ventity

I’ve long wanted to translate the Sterman-Wittenberg model of Kuhnian paradigm revolutions to Ventity. The original was in Dynamo, and I translated that to Vensim, but neither is really satisfactory, because both require provisioning array space for new paradigms statically, before it’s needed. This means simulating lots of useless 0s, and even worse, looking at them in the output.

The model is about the lifecycle of scientific paradigms, so a central feature is the occasional introduction and evolution of new paradigms, which eventually accumulate enough anomalies to erode confidence, making them vulnerable to the next great idea. So ideally, you’d like to introduce new paradigms dynamically and delete them when they no longer have many adherents. Dynamic creation and deletion of entities is of course a core feature of Ventity – it’s the tool this model has been waiting for all those years.

I finally got around to translating my Vensim version to Ventity recently. It works beautifully:

Above, paradigm confidence, showing eight dominant paradigms as well as many smaller paradigms that never rise to dominance. They disappear when they run out of adherents. Below, puzzles under attack for the same paradigms.

Links to the source papers and more notes on the model are in the Vensim library entry. I think the dynamics are generalizable to other aspects of thinking in paradigms, like filter bubbles. The model is also a bit ‘meta’: Ventity as a distinct modeling paradigm that’s neither in the classical array-based world nor the code-based discrete agent world has struggled to win mindshare.

A minor note on use: the Run Config includes two setups: “replicate” and “random”. The “replicate” setup, which is inactive by default, launches paradigms at fixed times given by initialization data from a run of the Vensim version. This makes it possible to compare the simulations without divergence from randomness. However, the randomized run will normally be the more interesting way to work with this model.

The model (requires Ventity, which has a free trial license):

SciRev 15.zip

Computer Collates Climate Contrarian Claims

Coan et al. in Nature have an interesting text analysis of climate skeptics’ claims.

I’ve been at this long enough to notice that a few perennial favorites are missing, perhaps because they date from the 90s, prior to the dataset.

The big one is “temperature isn’t rising” or “the temperature record is wrong.” This has lots of moving parts. Back in the 90s, a key idea was that satellite MSU records showed falling temperatures, implying that the surface station record was contaminated by Urban Heat Island (UHI) effects. That didn’t end well, when it turned out that the UAH code had errors and the trend reversed when they were fixed.

Later UHI made a comeback when the SurfaceStations project crowdsourced an assessment of temperature station quality. Some turned out to be pretty bad. But again, when the dust settled, it turned out that the temperature trend was bigger, not smaller, when poor sites were excluded and TOD was corrected. This shouldn’t have been a surprise, because windy day analsyses and a dozen other things already ruled out UHI, but …

I consider this a reminder of the fact that part of the credibility of mainstream climate science arises not from the fact that models are so good, but because so many alternatives have been tried, and proved so bad, only to rise again and again.