Interesting, I'm curious where you see that idea expressed in mainstream cog sci.
A theory makes predictions and explanations, models are a loose subset with overlap of that where they may make predictions that are wrong
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in essence, ie outside the theory. For example using just a model one might assume things have to be implemented as in the model whereas the
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theory might have a loose allowance. Can go deeper but I've written a bit about this off twitter, if you're interested?
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For example you can within the same theory produce different models.
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This is my understanding and I'm sure others have their own ideas about differences. Same as differences between theory and hypothesis.
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You can also accidentally create models which do stuff outside the theoretical framework because it was underspecfied.
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More than here if you're interested http://dx.doi.org/10.1016/j.cogsys.2013.05.001 …
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