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experience can be found in the field known as systems sciences, with a focus on the
underlying models, feedback loops, reflection, and anticipation that goes by the label of
systems thinking. In the social science modeling embraced by systems science, apparent
inconsistencies raised by the inclusion of the observer are replaced by a need to pay close
attention to processes and to multiple adjacent possibles. Once participants are admitted as
part of the process being modeled and their decision-making and design abilities are taken
into account, then the multiple possibilities to which they give rise must also be taken into
account and not seen as contradictory. The broad applicability of context dependence and
observer questions throughout the anticipatory sciences demands the exploration of both
logical foundations and narrative application. The possibility for implementation or “action”
lies in the reconciliation of experience and models in the “anticipatory” science.
The inability of Science 1 models adequately to capture the essence of Science 2
events has been well documented. For example, consider social science domains where
reflexivity and reflexive anticipation are characteristic traits of actors. Actors can become
reflexive by learning and by modifying their cognitive repertoire. More advanced forms of
reflexive anticipation at the actor’s level occur when actor A possesses an image of actor B’s
image of A, actor B an image of actor A’s image of B, and so on (the explicit basis of
interaction in Gordon Pask’s (1976) Conversation Theory). Learning and the acceptance of
error as part of context add to the recursive reflexive loop. For example, the dual function of
DNA in a cell as a machine for maintaining and reproducing an organism and as a code for
reproducing an organism makes it highly self-reflexive. Likewise, the neural networks in the
brain are also self-organized in a reflexive manner. A challenge arises whenever a researcher
becomes part of the domain of investigation itself. Observing systems observing systems
pose a series of challenges in terms of interactions, in terms of consensus-building, and in
terms of results.
Concurrent but Orthogonal – How the Domains of Science 1 and Science 2 Entwine
“If we start from a puzzling action, the story we tell places that action in a temporal
continuum, relating it to previous actions and events that led up to it; and it places the
action also in relation to a future scenario or set of possible futures. The original
action was puzzling in part because we didn’t have its temporal context. … we
illuminate the unfamiliar by relating it to the familiar. … Causality, however, with
which the early covering-law theorists tried to link the elements of a narrative, is
totally out of place here. A perceived situation, an emotional reaction, taking on a
goal and initiating a plan for reaching it, these do not cause the action but serve to
motivate it. … the causal account leaves out a conscious agent whose relation to the
antecedent situation is at least a subjective and practical, if not a deliberative, one. …
Common-sense discourse about human behavior is thus seen as a kind of aspiring but
deficient explanatory endeavor, trying hard but failing to do what real science is now
presumably able – or soon will be able – to do, namely to explain, predict, and control
human behavior. … One thing that seems not to be considered is that the context of