Solving for Pattern: An Analysis

Solving for Pattern: An Analysis
Source: https://www.christies.com/en/stories/m-c-escher-collecting-guide

I have finished sharing some thoughts regarding courage and discipline, and am ready to return to the main themes of this blog, namely, Solving for Pattern, Trust-Based Relational Intervention® (TBRI®), and Cultural-Historical Activity Theory (CHAT). What I would like to do in this post, before picking up where I left off with The Wilco Story, is share an analysis of the general concept of Solving for Pattern. In my experience, the understanding most people have of this concept – including myself – is somewhat vague. However, it is too important a concept to leave fuzzy, so hopefully I can sharpen the focus a little bit.

It seems to me that there are three main aspects to Wendell Berry's concept of Solving for Pattern: Solving, Pattern, and Context. As you can see, two of these are explicitly stated (found in the title), and the other is implicit (found only in the text of Berry's article). In this blog post, I will discuss the first of these, Solving, in subsequent posts I will discuss Pattern and Context.

Solving

"Solving" refers to the intentional act of finding a solution to some problem. (You will recall that kinds of solutions, two of which are "bad," and one that is "good.").It is apparent from the example of Earl Spencer's dairy farm (see Earl Spencer's Farm), that "solving," for Wendell Berry, is fundamentally a cybernetic process, involving various forms of learning from experience. We know that Berry was fully aware of the work being done by Gregory Bateson, and we can use one of Bateson's core concepts to examine Berry's notion of Solving for Pattern. In Steps to an Ecology of Mind (Aronson, 1972), Bateson proposed four levels of learning, three of which are relevant for present purposes (my analysis relies on a paper by Will McWhinney – see footnote below):

Zero Order Learning

Learning Zero is specificity of response, which – right or wrong – is not subject to correction or change (e.g., traditional computer programs, which always respond to the same input in the same way). With Learning Zero, there is no correction, change, or actual learning.

First Order Learning

Learning One, according to Bateson, is "change in specificity of response by correction of error of choices within an unchanged set of alternatives; that which is learned is how to select the most rewarding alternatives from an available set." Examples include trial-and-error learning, classical conditioning, and operant conditioning. McWhinney notes that Morris Berman (1981) offered a simple definition of Learning One: "the simple solution to a specific problem." Learning One is depicted in Figure 1, which was (crudely) copied from McWhinney's article.

A "cybernet" depicting the processes of Level One learning. An organism (rat, child, farmer) acts on the environment, and then compares the actual outcome (feedback) to the desired outcome (goal). For example, a dairy farmer might try different types or amounts of fertilizer, in order to see which ones worked best on his or her fields. If the farmer (actor) is not satisfied with the result, he or she might try something different next time.

Second Order Learning

Learning Two, according to Bateson, is "change in the process of Learning One, e.g., a corrective change in the set of alternatives from which a choice is made." Morris Berman's version is "Progressive change in the rate of Learning One." Here I quote McWhinney at some length:

Lars Qvortrup (2004) as well as Bateson viewed Learning Two as reflective knowledge. Learning Two follows from reflecting on the self-constructed or externally given sets of alternatives. In terms of the cybernet, the selection process begins with a search among comparators (or its assumptions) and a confrontation with the paradoxes presented by the reflection on their variety (Figure 2) . The learning follows when one is able to reflect among approaches to the problem, to select among schema for resolving the situation.
A Level Two cybernet, which introduces a reflective process into the problem solving situation. The Level One cybernet sets out to learn, through trial-and-error, which of the available actions are most effective in the current situation. The Level Two cybernet reviews (through a reflective process) the actions and outcomes of the Level One cybernet, which may lead to a change in the set of actions (schema) of the Level One cybernet. In Earl Spencer's case, a weather event prompted reflection on the current (L1a) cybernet, and led to the development of a second cybernet (L1b); L1a reflected the "conventional" plan, L1b reflected the "unconventional" plan.
Learning Two begins with a search for assumptions of the schemata-in-use, reflecting on their appropriate in the present situation, then identifies a new schema and selects an alternative favored by a reflective schema – in effect selecting a new cybernet where the action agent is the first cybernet. It is a hierarchical arrangement, in which the reflective second cybernet redirects the first, which in turn selects the action.

Returning to the example of Earl Spencer's farm, what we can now see is that his transition from a "conventional" plan to an "unconventional" plan – which was inspired by a season of unusually wet weather – can be viewed as an example of Learning Two. Wendell Berry describes various reflective processes that led Earl Spencer to radically transform the nature of his Learning One schema, which, in Berry's view, is a transition from an "industrial" mindset (schema) to an "organic" mindset (schema). Berry alludes to the Learning Two schema when he says: "He [Earl Spencer] chose to sell half his herd – a very unconventional choice, which in itself required a lot of independent intelligence. [italics added]

Earl Spencer's transition from a "conventional" plan to an "unconventional" plan reflected, at the outset, Second Order Learning; once the new schema was identified, there followed a few seasons of First Order Learning, based on the new schema. The old schema was based on a "conventional" plan that reflected an industrial mindset; the new schema – derived through Learning Two – was based on an "unconventional" plan that reflected an organic (or relational) mindset.


Will McWhinney, "The White Horse: A Reformulation of Bateson's Typology of Learning. Cybernetics & Human Knowing, Vol. 12, nos. 1-3, pp. 22-35.

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