So let us, we happy plants, forget the rage of the volcano. — fdrake

I have a feeling this whole story is a parable or a metaphor, but I can’t see what of. However seems far more germane to a biology forum than a philosophy forum.

There is no relevant information nature cannot access, nature unfolds according to its own sense of relevance, but its sub-processes learn to contextualise. Perhaps it could even be phrased like the origin of sub-process is a context of development. Like the canopy trees never become immune to lava. Causal histories get absorbed into intermediaries until they become relevant again. — fdrake

Here's what I think is at stake here (let me know if it's different): are you trying to account for the autonomy of systems without at the same time trying to entirely disengage that system from it's wider environment? That is, trying to account for a relative autonomy of systems within (variable) threshold values that when crossed (under equally variable conditions), make it so that the environment now bears upon the system in question?

One thing your descriptions reminds me of - at a totally different scale of time and space - are vesicles, which are like little sheltered chambers formed by fat molecules, which provide something of a micro-environment within the bodies for different kind of chemical reactions that would not take place without them. And of course the coherence of a vesicle is itself dependant on it's own environmental factors, even as it shelters and separates what takes place inside from what takes place outside.

A different question: what's the enemy here? Are they accounts which can't provide such an account? And what do they look like? Trying to triangulate the motives here.

The relevant thing to look for in here is how expanding the 'state space' (available information which is incorporated to process dynamics) can reduce the dependence on the unobserved past (unavailable information that is implicitly unincorporated). — fdrake

Any relationship to the ‘arche-fossil’? Am I getting warm?

Hence there wouldn't be the interaction between the environment and the volcano.
— ssu

So long as you can get this bit from it, that's all I care about. — fdrake

Now there’s a clue.

I have a feeling this whole story is a parable or a metaphor, but I can’t see what of. However seems far more germane to a biology forum than a philosophy forum. — Wayfarer

I think I'm doing philosophy, though I don't think the topics and questions are particularly well posed yet. It's somewhere in the intersection of assemblage theory (philosophy);Deleuze, DeLanda (and Bryant); causal network theory (statistics) and cybernetics or system control theory (which I haven't included yet but will).

Any relationship to the ‘arche-fossil’? Am I getting warm? — Wayfarer

No actually. Hasn't entered my head while writing this.

Here's what I think is at stake here (let me know if it's different): are you trying to account for the autonomy of systems without at the same time trying to entirely disengage that system from it's wider environment? That is, trying to account for a relative autonomy of systems within (variable) threshold values that when crossed (under equally variable conditions), make it so that the environment now bears upon the system in question? — StreetlightX

I'm trying to see where a knot of ideas I've had leads.

So that's one thread in it. I think this is related to a previous discussion we had (in "I Am An Ecology") about how nature learns what to care about; and how that might be fleshed out in terms of the becoming-relevant of a parameter in a dynamical model. Here, temperature, moisture, sunlight vs the rest of the environment for the seed germination process. An 'answer' I'm striving towards here is that nature (can) learn what to care about by the development of subprocesses (say, dormancy) which have signalling structures (seed sensory capacities) that somehow embed the salient features of larger system dynamics (reproductive success rates based on environmental parameters) for the subsystem.

Another thread is about system history. I've been quite meticulous to only use the word 'time' internally to a system level description; like germinating times in wild barley. (Except when describing stochastic processes, but I did also phrase the indexical nature of time in them as an 'interaction' first!). All the other 'orders' in my posts here are actually system orders (like $\text{Volcano}\rightarrow\text{Soil}$), directions of causal influence, rather than relations of temporal antecedence. To be sure, there are relationships of temporal antecedence in the posts, like the reproductive system of plants being older than the dormancy adaptation of their seeds, but these only occur when one system is a developmental trajectory of another.

These two questions are related. When a system learns to care about stuff, it learns not to care about other stuff that might be relevant. There's a mathematical feature of models in evolution (which holds for the deterministic dynamical systems that I'm aware of too) that the next time step depends only on the current one. Let that sink in and take it seriously. If our descriptions of reality are accurate and have an assumption in them that only the recent past matters, where does the relevance of all this bloody history come from? In the first post I referenced that you can 'restore' the next->current (Markov) dependence property of a model by making the state space of the model bigger; by including more relevant information. A corollary is, if you exclude relevant information, you allow more history. As Rovelli put it in the Order of Time "time is ignorance".

The last thread is one I've not written much about yet, it's in the details of the seed germination mechanism 'models' its environment. I plan to leverage:

Though they may have functional sortals embedded in their germination patterns; temperature ranges which are amenable to growth, light levels amenable to growth, moisture levels amenable to growth; switches that say germinate or do not germinate, with fuzzy boundaries depending on the seed and the plant and all sorts of other things. The variation on the individual level manifests in a distribution of germination times on the originator plant level; of probabilities of germinating given (environmental condition) and on the plant community level. — fdrake

the idea of a sortal induced by germinating/not germinating on the individual plant level ("is this environment right for germination?" check thresholds...) to show one way one system (seed germination) can model another (environmental influences on reproductive success rates of seeds) through a discussion of the good regulator principle in cybernetics.

Since you've read The Order of Time, I'm trying to tease out a sense in which an approximation of one system by another might be immanent to their relation; and this approximation is a 'forgetting' of irrelevant parameters, which induces 'history' to their relationship through unobserved relevance. Another thing I'm being inspired by here is the brief discussion of wasps and orchids in A Thousand Plateaus; one being a 'map' of another.

though I don't think the topics and questions are particularly well posed yet. — fdrake

Is that why you didn't really address my posts? Because they weren't in topic? I was wondering about that.

Is that why you didn't really address my posts? Because they weren't in topic? I was wondering about that. — frank

No no you helped me. The thought/being criticism is wack, though.

But you didn't adress the thing about how you were using probability. Your answer made me wonder at you especially since youre all immersed in math. How could you think probability bears on any sort of "blurred data"?

I didn't bring up thought/being. It was just about causality. Causality is a kind of relationship. We use the concept. We project the idea on events. Didn't Rovelli say something along the same lines?

We project the idea on events. Didn't Rovelli say something along the same lines? — frank

Yes. I would love to be able to talk without the word "cause", but it is so convenient. I'm trying to think of causes systemically, as they are distributed over networks of interaction. I would prefer to do away with it all and just talk in terms of interactions and sensitivities, but if I did that everyone would recognise what I'm writing here as the schizoid scientific philosophy conspiracy theory it is rather than being enticed to follow me down a rabbit hole they might get stuck in too.

...schizoid scientific philosophy... — fdrake

So, very soon this will morph into "volcano souls" and we'll be talking Xenu and hydrogen bombs. *Grabs popcorn*.

I see. Carry on then.

A different question: what's the enemy here? Are they accounts which can't provide such an account? And what do they look like? Trying to triangulate the motives here. — StreetlightX

I don't really know. Someone who conceived of nature as one big undifferentiated glut, or one big self differentiating glut probably would be anathema here; if they refused the ability to take on the perspective of subsystems. I'm not certain I really have any direct targets here, since I seem to be out on such a limb. I'm carrying my general prejudices with me though; no to reductive notions of causality, yes to thinking in terms of becoming.

A model of a system typically contains parameters; variables of interest which capture dynamics within it. Parameters are directions of variation of a system. For seed germination, these parameters are moisture level, temperature and sunlight level. But how do seeds become sensitive to changes in and levels of these parameters in terms of their germination?

One part of the story conceives a seed as an evolutionary machine in an environment which affords seeds different reproductive successes based on its conditions. But the seed is in an entire environment, from the molecule to the climate, a complex system saturated with causal flows. The reproductive success rates of seeds benefit from internalising indicators of the flows that matter for their reproductive success; a seed becomes a map of its environment insofar as the environment interacts with the sensitivities of the seed.

But those sensitivities are distinguished somehow; how an environment interacts with a seed in terms of reproductive success is a constrained story told with few of the directions of variation available to the environment. These directions of variation embed themselves in the seed in an indicative form through modifying their reproductive success rates; a seed has attuned and will attune to what is relevant in its environment through the population level reproductive successes. It dances on the stage of its environment like a green idiot to music beyond its reckoning, but like us it learns to tell stories of its environment. So too for the bodies of their ancestors. Which parameters are relevant for them are those which are contained in the stories.

Relevance and irrelevance to reproductive success induces a sortal on the environment; a partition of its behaviour into that which counts-as relevant for the seed's reproductive success and that which does not. We can imagine an environment as a series of cycles; seasons, diurnal patterns of animals, weather in those seasons, rain crystallising in spider webs; some are sensitive to others, some are not. We should take from the seed example that something can only become relevant to the dynamics of a system when a causal flow can take something in the background as a given; a flow not in friction with something that varies sufficiently slowly with it. The subtended land soil forms over, those tectonic ingresses surrounded by water; is bedrock both literally and metaphorically for the cycles of the environment it subtends. It is not without change, just without change relative to the processes it supports. It is that relative changelessness which supports the ability for a system to separate itself from its environment; when a butterfly flaps its wings tornados move more than light.

The same can be said for the seed-bearing organismal sensitivity to light, moisture, temperature, it is a slower direction of variation relative to the sensory innovations of seeds to those sensitivities. When one follows a cladistic tree back in time, one sees not what is unchanging and essential, but what perturbations become reproduced; what contingencies are embedded in a flow of biomass reproduction that can become its moving (really becoming) parts. Essence is stability reified as given in a being; essence as a property forgets the becoming of its subtended sortal; it unasks the questions of what and how flows become partitioned into relevance and irrelevance for that being.

But when one treats not even essence as a given; and conceives it as a stability born from a partition of flows into relevant (learned sensitivity, destructive ignorance) and irrelevant (true causal isolation, statistical independence of flows) for a given flow; one therefore has to ask where in the flow does the capacity for such partition arise.

Relevance is a contour of interactive intensity; sensitivities are sites of intense interaction. Sensitivities are directions of variation which matter.

Relevance and irrelevance to reproductive success induces a sortal on the environment; a partition of its behaviour into that which counts-as relevant for the seed's reproductive success and that which does not. We can imagine an environment as a series of cycles; seasons, diurnal patterns of animals, weather in those seasons, rain crystallising in spider webs; some are sensitive to others, some are not. — fdrake

I quite like this vocabulary of 'inducing a sortal on the environment': I read it as a way (at a first approximation) of qualifying causality. So rather than the linear indifference of 'cause -> effect -> cause -> effect', this kind of approach forces a proper empiricism of bodies ('descend' from causes to bodies): not just 'what caused it?', but also: 'is that (kind of) body open to that cause?/Does it have that capacity to be so affected?". It 'materializes' cause, it makes of bodies not just a mere vector for causes - as though their particular constitution were irrelevant, and as though bodies were mere carriers or chora for causes - but as something worthy (necessary) of study in their own right. And this in turn allows one to think of 'natural discontinuities', in a way that challenges some approaches to nature as continuous and Whole - a nature full of gaps and forgetting, as it were.

I have in mind in particular some passages in Deleuze (and Guattari) on Markov chains, which they speak about in relation to order arising out of discontinuity, which this discussion has helped me make sense of. I quote a commentary: "For Deleuze, it is a question of thinking about chains in a way that does not rely on causal or final succession, or structure. Markov provides the concept for this kind of chain, which is distinct from both continuity and the absence of order.... Like Markov, Deleuze maintains a dimension of order that operates randomly through discontinuous junction that is comprised of divisions, and also determined sections. In Deleuze, the nature of order is, then, semi-random. Furthermore, the connected elements do not signify and are not homogeneous. In other words, they are nonsignifying and heterogeneous" (Anne Sauvagnargues, Deleuze and Art).

In Anti-Oedipus they explicitly link the Markov chain with the wasp and the orchid: "Each chain captures fragments of other chains from which it "extracts" a surplus value, just as the orchid code "attracts" the figure of a wasp : both phenomena demonstrate the surplus value of a code. It is an entire system of shuntings along certain tracks, and of selections by lot, that bring about partially dependent, aleatory phenomena bearing a close resemblance to a Markov chain". One way in which I think of this is that this elaboration of links between selection (of relevance), forgetting (of what is not relevant) and production (of the new) contains in it a whole 'naturalist' philosophy of nature, which I think is really cool.

When one follows a cladistic tree back in time, one sees not what is unchanging and essential, but what perturbations become reproduced; what contingencies are embedded in a flow of biomass reproduction that can become its moving (really becoming) parts. Essence is stability reified as given in a being; essence as a property forgets the becoming of its subtended sortal; it unasks the questions of what and how flows become partitioned into relevance and irrelevance for that being.

This is also a gorgeous way of thinking about cladistics as well - it's the kind of thing that ought to be thought to every first year bio student, if not in high school bio class in general.

This post was originally titled "Enzymatic catalysis as a model of causality". A rough description of how enzymes work in general is that they're:

(1) A bunch of proteins in a certain shape.
(2) The shape has a cavity called an 'active site'.
(3) The shape only fits things resembling it closely.

What an active site does is temporarily bond to some chemical to induce a chemical reaction to it. The chemical can make the enzyme fit to it by how it interacts with it, but that doesn't matter much here. A canonical example in humans is amylase in saliva, which takes starches; long chain polymers of carbohydrates; and acts at the carbohydrate-carbohydrate bonds to produce smaller carbohydrates to start their digestion.

The amylase is just there in human saliva. The starch is just there in food. When we chew, the proximity of the starches in our food and the amylase induces the breakdown reaction.

Amylase has sensitivity to the presence of certain carbohydrate bonds; it then acts on them when they are close. The internal dynamics of the amylase molecule facilitate the breakdown of starches into smaller carbohydrates. From the point of view of digestion, what matters is the efficiency of the breakdown relative to evolutionary-ecological-amylase productive constraints rather than the specifics of the molecular structure of amylase. They are a machine which solves the initial problem of starch digestion.

When giving a description of the amylase-starch system, however, what matters is the active site-chemical interaction. From that you can consider the various molecular and geometric structures that an enzyme may have as directions of variation which may be selected for; the specifics blur out, what matters is the feed forward of simple carbohydrates from complex carbohydrates.

But what of amylases that are not currently omnomnoming their starch? They are sensitive and specific to the presence of starches. Consistent with the previous themes in this thread; causality is always an interactive process, sensitivities are open feed forwards, but now we have enzymatic specificity; they only work on one thing, their mechanism as enzymes is sensitive only to starch presence, they have a single developmental trajectory in terms of starch - the production of smaller carbohydrates. (though stuff sufficiently similar can block enzyme functioning!)

When a system has a sensitivity, the system can be controlled or influenced by manipulating that sensitivity. Like a bridge to torsion (so make structures which resist it), inside temperature of a fridge to outside temperature of the room (make thermometers and variable cooling mechanisms). A sensitivity is a direction of variation which is open to (active site) the presence of a feed forward (starch presence); and a feed forward is the name of a realised interaction from some external system.

If we consider amylase itself as a self maintaining process; of folded proteins with their movements constrained to a geometry induced by their intermolecular forces; the amylase part of the amylase-starch system, going down from the amylase starch interaction catalysis renders the amylase just a bearer of an active site. The proximity of amylase and starch is what initiates their interaction, but they both are sensitive to the presence of the other.

$\text{Amylase} \leftrightarrow \text{Starch}$ (enzymatic catalysis of starch breakdown)
$\text{Amylase} \leftarrow ...$ (presence of active site)

Prosaically, the wisdom in the phrase "3/4 of success is just showing up" is reflected in the causal structure of enzymes; when amylase shows up at the starch of the day, they do their job simply by proximity to it.

Any relationship to the ‘arche-fossil’? Am I getting warm? — Wayfarer

Maybe the only relation to the arche-fossil is that it tries to be a ground-clearing for thought like this. A demystification device, an impetus from idealism or correlationism to materialist thought.

If we consider amylase itself as a self maintaining process; of folded proteins with their movements constrained to a geometry induced by their intermolecular forces; the amylase part of the amylase-starch system, going down from the amylase starch interaction catalysis renders the amylase just a bearer of an active site. The proximity of amylase and starch is what initiates their interaction, but they both are sensitive to the presence of the other. — fdrake

Cashing out this idea of sensitivity could be done in a few ways. If we're looking at the molecular dynamics of a distribution of amylase in solution binding to starch molecules in solution, an appropriate model would probably look something like:

$P(\text{amylase enzyme}_i\text{ binds with }\text{starch molecule}_j) = \exp(-d(i,j)^2)$, the probability depends on how near the active site is to the appropriate bit of the starch molecule. It would also probably depend on other things, like the relative velocities of the enzyme and the starch, the relative orientation of the two... Ideally this would capture all the dynamical variables of interest. But there's still the amylase-starch system to talk about in terms of its relationship to digestion (glucose metabolism), in which case what matters is the aggregate and presence of the interactive system of their molecular dynamics.

On this level, what matters is the enzyme's capacity to act as an environmental filter for starch molecules, and how efficiently (energetically/productively) it can catalyse their breakdown. What matters is the 'on/off' property of 'has this produced simpler sugars?' and what is selected over reproductively are the protein configurations of the enzymes which facilitate this transformation. The specifics of those protein configurations are blurred; the sigma algebra of amylase producing events realises into the aggregate variable of (more or less efficiently produced) simpler sugars. That is, they are selected for as a system of interacting with starch unto themselves. In other words; selection acts upon the interaction between amylase and starch by modifying amylase's open feed forward that becomes closed by starch's presence; a potential for a feed-forward (starch presence->amylase) becomes interactive feedback (starch <-> amylase catalysis).

So a cool trick with thinking is the interplay between procedural descriptions and diagrammatic representations of them.

Condensing a decision process into a flow chart lets you think about the tasks involved in each arrow.
Writing down required inputs and outputs for an algorithm helps you code it.

The same is true for mathematical ideas. But a relatively unique (I think) thing about such diagrammatic representations of processes in math is that you can ask mathematical questions about the diagram to analyse the original idea. Leonhard Susskind invented the idea of the "world-sheet" in string theory by drawing two Feynmann diagrams up on a board at right angles to each other, then started analysing what it would even mean to rotate them like that and treat them as sides of a shape.

The same seems to be true when wrestling with the mathematisation of ideas, and using math to study ideas and lend them precision. So I drew a diagram of some of the ideas I've been ranting about.



Two systems $S$ and $T$ have some parameters associated with them $C(S)$ and $C(T)$. The black arrows take the underlying systems to the salient features of their dynamics. Then the red and blue arrows link the parameters through functional relationships. The actual structure of the relationships there is arbitrary, it's just supposed to be a reasonably general picture of what's going on.

For a specific (overly simple) system, we can look at the Lotka-Volterra equations in predator-prey dynamics:



The system $S$ is the behaviour of the wolves, the system $T$ is the behaviour of the rabbits. These map to the number of wolves $w$ and the number of rabbits $r$ through $C$ (the black arrows).

Then we have the relationships of these parameters, how to get from $w$ to $r$ on the graph. The blue $dw$ arrow and the red $dr$ arrow correspond to the equations:

$\begin{align}dw=aw-br\\dr=cr-ew\end{align}$

An insight that can be gained from this portrayal is the distinction between two problems; the parameter emergence problem and the parameter interaction problem. The black arrows take systems and coalesce them into parameters; parameter emergence. The red and blue arrows take coalescences of parameters and describe the effect of one system on another through their functional dependence; the parameter interaction problem.

Parameter emergence in a system is the question of how a system congeals into distinct flows with characteristic features, parameter interaction is the question of how the characteristic features of complex systems interact with each other.

Specific instances of parameter interaction are the usual domain of mathematical models and natural laws, $F=ma$, $y=mx+c$. Rarely do we consider how complex systems obtain the directions of variation that allow their sub-systems to couple.