Penny Tompkins and James Lawley

Stage 3: Constructing Your Model

When modelling multiple exemplars for a class of experience, one process for constructing your general model is to:

1. Describe how each exemplar does what they do to get the required results from their perspective and in their words; i.e. construct a model using their representations.

2. Evaluate each model (to know what extra information to gather) for:

Completeness - It has all necessary distinctions/components (it's 'full')

It answers 'what else?' questions with ... "nothing ".

Coherency - The relationships between components adhere to an internal logic (they 'cling together').

It answers 'why?' questions from within its own logic.

Consistency - It does its job across a range of contexts and acquirers (it 'stands firm').

It can answer 'what if?' questions.

3. Compare and contrast individual models component-by-component, step-by-step and function-by-function.

4. Design your own model by one or more of the following methods.

(At this point you must separate the information gathered from the exemplar: It is no longer their model, it becomes your model because you will represent the information in a different way.)

a. Identify similarities across exemplars and construct a composite model based on similarities.

b. Use one of the models as a prototype and improve it by adding/substituting distinctions/components/steps from the other models.

c. Deconstruct the individual models into the function of each component/stage and construct a new model from the bottom-up.

d. Adapt existing models from other contexts that are compatible with the model you are constructing, and use them as the framework for your model (e.g. 'transformational grammar' was the basis for the Meta Model, and 'self-organising systems theory' formed the framework for Symbolic Modelling).

5. Evaluate and improve your model based on the degree to which it is:

Effective - It gets similar results to the exemplar.

Efficient - It requires the least number of steps/components

(use Occum's Razor to make it "as simple as possible, but no simpler ").

Elegant - It is code congruent - the content of the model and the manner in which it is presented/coded are congruent.

6. Test, get feedback, adjust model, test again, get feedback, adjust ...

More on Model Construction

Evaluate whether distinctions/components go into the model by the degree to which each is:

Effective - contributes to the overall outcome of the model

Efficient - serves multiple functions

Elegant - fits into the overall coherency (internal code congruency) and enhances the consistency (external code congruency) of the model.

Evaluate the completeness of your model by the degree to which it shows 'Operational closure':

• When no new components or patterns emerge and the client's descriptions add no further information about how that operational unit works.
• When new components or examples continue to appear but they are isomorphic (have the same function or organisation) as previously identified patterns.
• When the logic of the client's description encompasses an entire configuration, a complete sequence or a coherent set of premises (with no logical gaps).
• When the model enables you to predict ways of dealing with unexpected situations, difficulties, interference or distractions that have yet to be mentioned by the exemplar.
• When you repeat or demonstrate the operational unit to the exemplar, they acknowledge that's it, you got it .

Evaluate your model for its congruency with:

Stage 2: The exemplar(s)

Stage 3: Itself

Stage 4: The context where it will be tested

Stage 5: The acquirer(s)

Exemplar's cannot not do their patterns of excellence

A key aspect of modelling is to determine how an exemplar keeps achieving the same results. How is it that they cannot not do it? How come they don't forget to do it? How do they adjust for unfavourable circumstances so that they consistently get excellent results? In other words, how come it's habitual? This information will not be in any of the components, but in the pattern of relationships between perceptual components. It will be the circular chains (Bateson) of relationships that keep the pattern repeating. And your model needs to have comparable circular chains.

Except when ..

Conditions are 'extreme' or 'over thresholds' or 'off the scale' and the pattern breaks down. What are those conditions and what do exemplars do then? Considering 'Is there any way I can I run this model and do something else?' and 'Under what circumstances would I not get the required results? '. Then adapting your model to take these circumstances into account will make it more robust, more consistent.