@UlrikeHahn @dcm@bookwyrm.social @NicoleCRust @dsmith @uh not me! I don't think Juarrero made a good case for those examples, and I still don't quite understand what she means by constraint, let alone the many different kinds of constraint she identifies.

@dcm@social.sunet.se @dcm@bookwyrm.social @NicoleCRust @dsmith @uh

I’m confused by the terminology too, but I’m thinking more and more that one’s opinion on both the notion and on the examples is going to be determined by how one thinks about possibilities or possibility spaces. If you start with those, then the notion of a constraint seems natural, and if you think of those possibilities in some sense as ‘real’, then constraints will be ‘real’ to that extent also.

@UlrikeHahn @dcm@bookwyrm.social @NicoleCRust @dsmith @uh I agree, I just don't quite get why we should take that as competition to the familiar causal picture: constraints may capture patterns in nature, which are though underlain by familiar kinds of causal relations. So explanatorily useful in some cases, and capturing something real (as those patterns are real), but still no threat to the mainstream causal view, as J. seems to think.

@dcm@social.sunet.se @dcm@bookwyrm.social @NicoleCRust @dsmith @uh

Maybe it would help to articulate ‘the mainstream picture’, causal or otherwise, on the buttons example as you see it? What is the story with respect to “a connected network emerged”, and it “emerged when there were x many links”?

@UlrikeHahn @dcm@bookwyrm.social @NicoleCRust @dsmith @uh that sort of behaviour of the buttons depends on how they interact causally with each other, I would imagine, and this in some cases and under certain conditions generates a sort of network pattern, which just is the ensemble of those causal interactions. Something along these lines would be the typical causal picture?

@UlrikeHahn @dcm@bookwyrm.social @NicoleCRust @dsmith @uh I see, then I don't think I understand the example: don't they interact through weight, friction, etc., once they are connected by the string?

@dcm@social.sunet.se @dcm@bookwyrm.social @NicoleCRust @dsmith @uh they do, but the thing that’s at issue is why they are suddenly all connected. What ‘caused’ that?

@UlrikeHahn @dcm@bookwyrm.social @NicoleCRust @dsmith @uh I looked for videos of this experiment to try and understand it better, but I don't seem to have found one.
I would think that the idea would be that what causes that is just the ensemble of causal relations between the buttons: weight, friction, etc with just the right values to make that happen. But my grasp of the case is not great, so I'm not sure.

@dcm@social.sunet.se @dcm@bookwyrm.social @NicoleCRust @dsmith @uh it’s just a thought experiment, Dimitri. You could replace it with anything that can be described with a network: say a bunch of new people move into a neighbourhood, they bump into each other randomly, two at a time, and become acquainted. When they meet an acquaintance, they pass on new information about the neighbourhood. At some point, when enough of them have become acquainted (ie formed pairwise ties) info will spread to everyone

@UlrikeHahn @dcm@bookwyrm.social @NicoleCRust @dsmith @uh ah, the description on the book seemed to suggest it was an actual experiment/demonstration, since it talks about connecting physical elements to each other and then mentions, implying a partial contrast, results from a simulation of the scenario.
But in the neighbourhood case, what is the puzzle? Information spreads by people meeting each other, right?