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commented on Context Changes Everything by Alicia Juarrero

Alicia Juarrero: Context Changes Everything (2023, MIT Press, The MIT Press) 1 star

#JuarreroBook Chapter 6 Part 2

so, moving on... The examples were meant to illustrate the notion of context dependent constraint, specifically context dependent enabling constraints:

"Enabling constraints (Pattee 1973; Salthe 1985; Juarrero 1999) are context-dependent constraints that irreversibly link and couple previously separate and entities at the same scale as the constraints."

e.g., "The rolling columns of fluid that constitute a Bénard cell are nothing other than interdependent, coherent dynamics generated by enabling constraints"

such " coordinated and coherent dynamics have emergent proper-ties their components severally do not, not least of which is their capacity to affect the properties and behaviors of those components that make them up. Phase locking, resonance, synchronization, and entrainment are emergent properties of coherently organized interdependent dynamics.Enabling context-dependent constraints are therefore constraints that make the probability of one event conditional upon another. "

"They irreversibly generate emergent and coherent, metastable patterns of matter and energy …

@uh Thanks for this summary, @UlrikeHahn!

I confess I didn't get anything from this 2nd part (I stopped on p.79): it struck me as a mix of platitudes that are no challenge to current scientific approaches, and baffling passages that I failed to understand. There is also a problematic conflation of artefacts, intentionally built in certain ways because we planned them that way, and 'natural' constraints. (And characteristically, no argument for why those should be treated in the same way).

@dcm @uh I think the bit I struggled most with is understanding why time is uniquely important here. A Markov chain or process also has „a history“ and generated states have an indexical ordering, but there is, by definition independence from earlier states.

For the kinds of complex systems I deal with (simulated societies of communicating agents) that seems directly analogous: only the current state is relevant for what happens next 1/2

@dcm @uh 2/2 and it doesn‘t matter by which trajectory the system got to the current state….

is that the case only because of something about the nature of the specific things I‘m simulating (they are still complex systems, though, on my understanding of the term…)? what am I missing?