Paradigm

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Paradigm is a set of rules that are used to make inferences about reality. A good paradigm results, within its scope, in a coherent world view, i.e. different details that are believed to be true do not lead into paradoxes.

Question

What are important paradigms in open policy practice, what rules do they contain, and how should they be implemented?

Answer

Scientific paradigm
A priori, any statement about reality may be true. Statements are falsified (invalidated) by showing that they are inconsistent with observations about the world. Every statement must be consistent with all other valid statements. Because of uncertainty in observations, there are several possible worlds that are internally consistent but have conflicts between them (i.e. any two possible worlds cannot both be true but we do not have enough data to tell which of them is not.) Paradigm is operationalised using discussion rules, especially attacking arguments that are backed up by observations or logical reasoning. All other arguments are considered invalid.
Popularity paradigm
The more popular a statement is, the more likely it is to be true. #: . It is not yet clear whether this paradigm also uses the concept of internally consistent possible worlds. Maybe there is a need for strict and loose versions, which do and do not require is, respectively. --Jouni (talk) 05:06, 4 July 2018 (UTC) (type: truth; paradigms: science: relevant comment)
Belief paradigm
If an archetype really really really believes that a statement is true, then it is. If a statement is not backed up by the archetype, it is considered indeterminate. There is no requirement for internally consistent possible worlds.

It is important to notice that paradigms can be used in combination, so that one paradigm is used with some kinds of statements and another with some others. Typically, belief paradigms do not give validity evaluations for any possible statement, and then other paradigms must be used. In contrast, the scientific paradigm has validity evaluation for everything: a statement with no observations is "possible but very unlikely" and an argument with no backup is "invalid".

Rationale

Paradigms are collections of rules to make inferences from data in the system. For example, scientific paradigm has rules about criticism and priority over hypotheses that are in accordance with data and rational reasoning. However, participants are free to develop paradigms with any rules of their choosing, as long as they can be documented and operationalised within the system. For example, a paradigm may state that in a conflict, priority is given to the opinion presented in a holy book. And in a hypothetical case where there is disagreement about what the holy book says, separate sub-paradigms may be developed for each interpretation. Mixture paradigms are also allowed. For example, a political party may follow the scientific paradigm in most cases but when economic assessments are ambiguous, the party will choose an interpretation that emphasises the importance of an economically active state (or alternatively market approach with a passive state).

This work is based on an idea that although the number of possible values and reasoning rules is very large, most of people's thinking can be covered with a fairly small amount of archetypes and paradigms. As a comparison, there are usually from two to a dozen parties in a democratic country rather than hundreds. In other words, it is putatively an efficient system. If this is true, resources can be used to get the critical issues precise and informative, and then apply these information objects in numerous practical cases.

It should be emphasised that although we have used wording such as "make inferences in the system", this approach does not need to rely on artificial intelligence. Rather, numerous contributors who co-create content and make inferences based on the rules described in paradigms, are the "system" we refer to. Parts of the work described here may be automated in the future, but the current system is mostly based on human work.

By now it seems clear that information in a description of shared understanding is very complex and often very large. So, a new research question emerges: how can all this information be written down and organised in such a way that it can easily be used and searched by both a human and a computer? A descriptive book would be too long for busy decision makers and unintelligible for computers. An encyclopedia would miss relevant links between items. A computer model would be a black box for humans.

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